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Essentials of Investments Information Center: Table of Contents

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Essentials of Investments, 5/e Zvi Bodie, Boston University Alex Kane, University of California, San Diego Alan J. Marcus, Boston College ISBN: 0072510773 Copyright year: 2004

Table of Contents

Part ONE Elements of Investments 1

Investments: Background and Issues

2

Financial Instruments

First Time Users

3

How Securities Are Traded

Student Edition

4

Mutual Funds and Other Investment Companies

Instructor Edition

Part TWO Portfolio Theory 5

Risk and Return: Past and Prologue

6

Efficient Diversification

7

Capital Asset Pricing and Arbitrage Pricing Theory

8

The Efficient Market Hypothesis

Part THREE Debt Securities 9 10

Bond Prices and Yields Managing Bond Portfolios

Part FOUR Security Analysis 11

Macroeconomic and Industry Analysis

12

Equity Valuation

13

Financial Statement Analysis

Part FIVE Derivative Markets 14

Options Markets

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Essentials of Investments Information Center: Table of Contents

15

Option Valuation

16

Futures Markets

Part SIX Active Investment Management 17

Investors and the Investment Process

18

Taxes, Inflation, and Investment Strategy

19

Behavioral Finance and Technical Analysis

20 Performance Evaluation and Active Portfolio Management 21

International Investing

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Bodie−Kane−Marcus: Essentials of Investments, Fifth Edition

Front Matter

A Note from the Authors

© The McGraw−Hill Companies, 2003

A Note from the Authors . . .

The last decade has been one of rapid, profound, and ongoing change in the investments industry. This is due in part to an abundance of newly designed securities, in part to the creation of new trading strategies that would have been impossible without concurrent advances in computer and communications technology, and in part to continuing advances in the theory of investments. Of necessity, our text has evolved along with the financial markets. In this edition, we address many of the changes in the investment environment. At the same time, many basic principles remain important. We continue to organize our book around one basic theme—that security markets are nearly efficient, meaning that most securities are usually priced appropriately given their risk and return attributes. There are few free lunches found in markets as competitive as the financial market. This simple observation is, nevertheless, remarkably powerful in its implications for the design of investment strategies, and our discussions of strategy are always guided by the implications of the efficient markets hypothesis. While the degree of market efficiency is, and will always be, a matter of debate, we hope our discussions throughout the book convey a good dose of healthy criticism concerning much conventional wisdom. This text also continues to emphasize asset allocation more than most other books. We prefer this emphasis for two important reasons. First, it corresponds to the procedure that most individuals actually follow when building an investment portfolio. Typically, you start with all of your money in a bank account, only then considering how much to invest in something riskier that might offer a higher expected return. The logical step at this point is to consider other risky asset classes, such as stock, bonds, or real estate. This is an asset allocation decision. Second, in most cases the asset allocation choice is far more important xviii

than specific security-selection decisions in determining overall investment performance. Asset allocation is the primary determinant of the risk-return profile of the investment portfolio, and so it deserves primary attention in a study of investment policy. Our book also focuses on investment analysis, which allows us to present the practical applications of investment theory, and to convey insights of practical value. In this edition of the text, we have continued to expand a systematic collection of Excel spreadsheets that give you tools to explore concepts more deeply than was previously possible. These spreadsheets are available through the World Wide Web, and provide a taste of the sophisticated analytic tools available to professional investors. In our efforts to link theory to practice, we also have attempted to make our approach consistent with that of the Institute of Chartered Financial Analysts (ICFA). The ICFA administers an education and certification program to candidates for the title of Chartered Financial Analyst (CFA). The CFA curriculum represents the consensus of a committee of distinguished scholars and practitioners regarding the core of knowledge required by the investment professional. This text will introduce you to the major issues currently of concern to all investors. It can give you the skills to conduct a sophisticated assessment of current issues and debates covered by both the popular media as well as more specialized finance journals. Whether you plan to become an investment professional, or simply a sophisticated individual investor, you will find these skills essential. Zvi Bodie Alex Kane Alan J. Marcus

Bodie−Kane−Marcus: Essentials of Investments, Fifth Edition

I. Elements of Investments

© The McGraw−Hill Companies, 2003

Introduction

PA RT

ONE

ELEMENTS OF INVESTMENTS

ven a cursory glance at The Wall Street Journal reveals a bewildering collection of securities, markets, and financial institutions. Although it may appear so, the financial environment is not chaotic: There is a rhyme or reason behind the vast array of financial instruments and the markets in which they trade. These introductory chapters provide a bird’s-eye view of the investing environment. We will give you a tour of the major types of markets in which securities trade, the trading process, and the major players in these arenas. You will see that both markets and securities have evolved to meet the changing and complex needs of different participants in the financial system. Markets innovate and compete with each other for traders’ business just as vigorously as competitors in other industries. The competi-

E

>

tion between the National Association of Securities Dealers Automatic Quotation System (Nasdaq), the New York Stock Exchange (NYSE), and a number of non-U.S. exchanges is fierce and public. Trading practices can mean big money to investors. The explosive growth of online trading has saved them many millions of dollars in trading costs. Even more dramatically, new electronic communication networks will allow investors to trade directly without a broker. These advances promise to change the face of the investments industry, and Wall Street firms are scrambling to formulate strategies that respond to these changes. These chapters will give you a good foundation with which to understand the basic types of securities and financial markets as well as how trading in those markets is conducted.

1

Investments: Background and Issues

2

Global Financial Instruments

3

How Securities Are Traded

4

Mutual Funds and Other Investment Companies

www.mhhe.com/bkm

Bodie−Kane−Marcus: Essentials of Investments, Fifth Edition

I. Elements of Investments

1. Investments: Background and Issues

© The McGraw−Hill Companies, 2003

1 INVESTMENTS: BACKGROUND AND ISSUES

AFTER STUDYING THIS CHAPTER YOU SHOULD BE ABLE TO:

> > > > >

2

Define an investment. Distinguish between real assets and financial assets. Describe the major steps in the construction of an investment portfolio. Identify major participants in financial markets. Identify types of financial markets and recent trends in those markets.

Bodie−Kane−Marcus: Essentials of Investments, Fifth Edition

I. Elements of Investments

1. Investments: Background and Issues

Related Websites http://www.ceoexpress.com This site provides a list of links related to all aspects of business, including extensive sites related to finance and investment.

© The McGraw−Hill Companies, 2003

research from the various banks is available online. The Federal Reserve Economic Database, or FRED, is available through the St. Louis Federal Reserve Bank. A search engine for all of the Bank’s research articles is available at the San Francisco Federal Reserve Bank.

http://www.corpgov.net

http://www.cob.ohio-state.edu/fin/journal/ jofsites.htm

Dedicated to corporate governance issues, this site has extensive coverage and numerous links to other sites related to corporate governance.

This site contains a directory of finance journals and associations related to education in the financial area.

http://www.finpipe.com

http://finance.yahoo.com

This is an excellent general site that is dedicated to finance education. It contains information on debt securities, equities, and derivative instruments.

This investment site contains information on financial markets. Portfolios can be constructed and monitored at no charge. Limited historical return data is available for actively traded securities.

http://www.financewise.com

http://moneycentral.msn.com/home.asp

This is a thorough finance search engine for other financial sites.

Similar to Yahoo! Finance, this investment site contains comprehensive information on financial markets.

http://www.federalreserve.gov/otherfrb.htm This site contains a map that allows you to access all of the Federal Reserve Bank sites. Most of the economic

n investment is the current commitment of money or other resources in the expectation of reaping future benefits. For example, an individual might purchase shares of stock anticipating that the future proceeds from the shares will justify both the time that her money is tied up as well as the risk of the investment. The time you will spend studying this text (not to mention its cost) also is an investment. You are forgoing either current leisure or the income you could be earning at a job in the expectation that your future career will be sufficiently enhanced to justify this commitment of time and effort. While these two investments differ in many ways, they share one key attribute that is central to all investments: You sacrifice something of value now, expecting to benefit from that sacrifice later. This text can help you become an informed practitioner of investments. We will focus on investments in securities such as stocks, bonds, or options and futures contracts, but much of what we discuss will be useful in the analysis of any type of investment. The text will provide you with background in the organization of various securities markets, will survey the valuation and risk-management principles useful in particular markets, such as those for bonds or stocks, and will introduce you to the principles of portfolio construction. Broadly speaking, this chapter addresses three topics that will provide a useful perspective for the material that is to come later. First, before delving into the topic of “investments,” we consider the role of financial assets in the economy. We discuss the relationship between securities and the “real” assets that actually produce goods and services for consumers, and we consider why financial assets are important to the functioning of a developed economy. Given this background, we then take a first look at the types of decisions that confront investors as they assemble a portfolio of

A

Bodie−Kane−Marcus: Essentials of Investments, Fifth Edition

I. Elements of Investments

1. Investments: Background and Issues

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4

Part ONE Elements of Investments

investment

assets. These investment decisions are made in an environment where higher returns usually can be obtained only at the price of greater risk, and in which it is rare to find assets that are so mispriced as to be obvious bargains. These themes—the risk-return trade-off and the efficient pricing of financial assets—are central to the investment process, so it is worth pausing for a brief discussion of their implications as we begin the text. These implications will be fleshed out in much greater detail in later chapters. Finally, we conclude the chapter with an introduction to the organization of security markets, the various players that participate in those markets, and a brief overview of some of the more important changes in those markets in recent years. Together, these various topics should give you a feel for who the major participants are in the securities markets as well as the setting in which they act. We close the chapter with an overview of the remainder of the text.

Commitment of current resources in the expectation of deriving greater resources in the future.

1.1 real assets Assets used to produce goods and services.

financial assets Claims on real assets or the income generated by them.

REAL ASSETS VERSUS FINANCIAL ASSETS

The material wealth of a society is ultimately determined by the productive capacity of its economy, that is, the goods and services its members can create. This capacity is a function of the real assets of the economy: the land, buildings, machines, and knowledge that can be used to produce goods and services. In contrast to such real assets are financial assets, such as stocks and bonds. Such securities are no more than sheets of paper or, more likely, computer entries and do not contribute directly to the productive capacity of the economy. Instead, these assets are the means by which individuals in well-developed economies hold their claims on real assets. Financial assets are claims to the income generated by real assets (or claims on income from the government). If we cannot own our own auto plant (a real asset), we can still buy shares in General Motors or Toyota (financial assets) and, thereby, share in the income derived from the production of automobiles. While real assets generate net income to the economy, financial assets simply define the allocation of income or wealth among investors. Individuals can choose between consuming their wealth today or investing for the future. If they choose to invest, they may place their wealth in financial assets by purchasing various securities. When investors buy these securities from companies, the firms use the money so raised to pay for real assets, such as plant, equipment, technology, or inventory. So investors’ returns on securities ultimately come from the income produced by the real assets that were financed by the issuance of those securities. The distinction between real and financial assets is apparent when we compare the balance sheet of U.S. households, shown in Table 1.1, with the composition of national wealth in the United States, shown in Table 1.2. Household wealth includes financial assets such as bank accounts, corporate stock, or bonds. However, these securities, which are financial assets of households, are liabilities of the issuers of the securities. For example, a bond that you treat as an asset because it gives you a claim on interest income and repayment of principal from General Motors is a liability of General Motors, which is obligated to make these payments to you. Your asset is GM’s liability. Therefore, when we aggregate over all balance sheets, these claims cancel out, leaving only real assets as the net wealth of the economy. National wealth consists of structures, equipment, inventories of goods, and land. We will focus almost exclusively on financial assets. But you shouldn’t lose sight of the fact that the successes or failures of the financial assets we choose to purchase ultimately depend on the performance of the underlying real assets.

Bodie−Kane−Marcus: Essentials of Investments, Fifth Edition

I. Elements of Investments

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1. Investments: Background and Issues

1

5

Investments: Background and Issues

TA B L E 1.1 Balance sheet of U.S. households

Assets

$ Billion

% Total

Real assets Real estate Durables Other

$12,567 2,820 117

26.7% 6.0 0.2

$15,504

32.9%

Total real assets Financial assets Deposits Live insurance reserves Pension reserves Corporate equity Equity in noncorp. business Mutual funds shares Personal trusts Debt securities Other

$ 4,698 817 8,590 5,917 5,056 2,780 949 2,075 746

Total financial assets

31,628

67.1

$47,132

100.0%

Total

Liabilities and Net Worth

$ Billion

% Total

Mortgages Consumer credit Bank & other loans Other

$ 5,210 1,558 316 498

11.1% 3.3 0.7 1.1

Total liabilities

$ 7,582

16.1%

10.0% 1.7 18.2 12.6 10.7 5.9 2.0 4.4 1.6 Net worth

39,550

83.9

$47,132

100.0%

Note: Column sums may differ from total because of rounding error. Source: Flow of Funds Accounts of the United States, Board of Governors of the Federal Reserve System, June 2001.

TA B L E 1.2

Assets

$ Billion

Domestic net worth

Real estate Plant and equipment Inventories

$17,438 18,643 1,350

Total

$37,431

Note: Column sums may differ from total because of rounding error. Sources: Flow of Funds Accounts of the United States, Board of Governors of the Federal Reserve System, June 2001; Statistical Abstract of the United States: 2000, US Census Bureau.

1. Are the following assets real or financial? a. Patents b. Lease obligations c. Customer goodwill d. A college education e. A $5 bill

1.2

A TAXONOMY OF FINANCIAL ASSETS

It is common to distinguish among three broad types of financial assets: fixed income, equity, and derivatives. Fixed-income securities promise either a fixed stream of income or a stream

24

Distinguish among the major assets that trade in money markets and in capital markets. Describe the construction of stock market indexes. Calculate the profit or loss on investments in options and futures contracts.

Bodie−Kane−Marcus: Essentials of Investments, Fifth Edition

I. Elements of Investments

2. Global Financial Instruments

Related Websites http://www.ceoexpress.com This site provides a list of links related to all aspects of business, including extensive sites related to finance and investment.

http://www.finpipe.com This is an excellent general site that is dedicated to finance education. It contains information on debt securities, equities, and derivative instruments.

http://www.nasdaq.com http://www.nyse.com http://www.bloomberg.com http://finance.yahoo.com These sites contain information on equity securities.

http://www.investinginbonds.com/ This site has extensive information on bonds and interest rates.

© The McGraw−Hill Companies, 2003

http://www.bondsonline.com/docs/bondprofessorglossary.html http://www.investorwords.com These two sites contain extensive glossaries of financial terms.

http://www.amex.com http://www.cboe.com/education http://www.cme.com http://www.commoditytrader.net http://www.erisk.com http://www.erivativesreview.com http://www.appliederivatives.com http://www.isda.org/index.html http://www.fiafii.org The above sites contain information on derivative securities

his chapter covers a range of financial securities and the markets in which they trade. Our goal is to introduce you to the features of various security types. This foundation will be necessary to understand the more analytic material that follows in later chapters. We first describe money market instruments. We then move on to debt and equity securities. We explain the structure of various stock market indexes in this chapter because market benchmark portfolios play an important role in portfolio construction and evaluation. Finally, we survey the derivative security markets for options and futures contracts. A summary of the markets, instruments, and indexes covered in this chapter appears in Table 2.1.

T

TA B L E 2.1 Financial markets and indexes

The money market Treasury bills Certificates of deposit Commercial paper Bankers’ acceptances Eurodollars Repos and reverses Federal funds Brokers’ calls Indexes Dow Jones averages Standard & Poor’s indexes Bond market indicators International indexes

The bond market Treasury bonds and notes Federal agency debt Municipal bonds Corporate bonds Mortgage-backed securities Equity markets Common stocks Preferred stocks Derivative markets Options Futures and forwards

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Part ONE Elements of Investments

2.1 money markets Include short-term, highly liquid, and relatively low-risk debt instruments.

capital markets Include longer-term, relatively riskier securities.

F I G U R E 2.1 Rates on money market securities Source: From The Wall Street Journal, October 19, 2001. Reprinted by permission of Dow Jones & Company, Inc. via Copyright Clearance Center, Inc. © 2001 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

THE MONEY MARKET

Financial markets are traditionally segmented into money markets and capital markets. Money market instruments include short-term, marketable, liquid, low-risk debt securities. Money market instruments sometimes are called cash equivalents, or just cash for short. Capital markets, in contrast, include longer-term and riskier securities. Securities in the capital market are much more diverse than those found within the money market. For this reason, we will subdivide the capital market into four segments: longer-term debt markets, equity markets, and the derivative markets for options and futures. The money market is a subsector of the debt market. It consists of very short-term debt securities that are highly marketable. Many of these securities trade in large denominations and so are out of the reach of individual investors. Money market mutual funds, however, are easily accessible to small investors. These mutual funds pool the resources of many investors and purchase a wide variety of money market securities on their behalf. Figure 2.1 is a reprint of a money rates listing from The Wall Street Journal. It includes the various instruments of the money market that we describe in detail below. Table 2.2 lists outstanding volume in 2000 of the major instruments of the money market.

Bodie−Kane−Marcus: Essentials of Investments, Fifth Edition

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Global Financial Instruments

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U.S. Treasury bills (T-bills, or just bills, for short) are the most marketable of all money market instruments. T-bills represent the simplest form of borrowing. The government raises money by selling bills to the public. Investors buy the bills at a discount from the stated maturity value. At the bill’s maturity, the holder receives from the government a payment equal to the face value of the bill. The difference between the purchase price and the ultimate maturity value represents the investor’s earnings. T-bills with initial maturities of 28, 91, and 182 days are issued weekly. Sales are conducted by an auction where investors can submit competitive or noncompetitive bids. A competitive bid is an order for a given quantity of bills at a specific offered price. The order is filled only if the bid is high enough relative to other bids to be accepted. If the bid is high enough to be accepted, the bidder gets the order at the bid price. Thus, the bidder risks paying one of the highest prices for the same bill (bidding at the top), against the hope of bidding “at the tail,” that is, making the cutoff at the lowest price. A noncompetitive bid is an unconditional offer to purchase bills at the average price of the successful competitive bids. The Treasury ranks bids by offering price and accepts bids in order of descending price until the entire issue is absorbed by the competitive plus noncompetitive bids. Competitive bidders face two dangers: They may bid too high and overpay for the bills or bid too low and be shut out of the auction. Noncompetitive bidders, by contrast, pay the average price for the issue, and all noncompetitive bids are accepted up to a maximum of $1 million per bid. Individuals can purchase T-bills directly at the auction or on the secondary market from a government securities dealer. T-bills are highly liquid; that is, they are easily converted to cash and sold at low transaction cost and with little price risk. Unlike most other money market instruments, which sell in minimum denominations of $100,000, T-bills sell in minimum denominations of only $10,000. While the income earned on T-bills is taxable at the Federal level, it is exempt from all state and local taxes, another characteristic distinguishing T-bills from other money market instruments.

Treasury bills

2

Treasury Bills

Certificates of Deposit A certificate of deposit (CD) is a time deposit with a bank. Time deposits may not be withdrawn on demand. The bank pays interest and principal to the depositor only at the end of the $ Billion

TA B L E 2.2 Components of the money market

Repurchase agreements Small-denomination time deposits* Large-denomination time deposits† Bankers’ acceptances Eurodollars Treasury bills Commercial paper Savings deposits Money market mutual funds

354.3 1,037.8 766.0 7.8 196.1 682.1 1,539.0 1,852.6 1,657.1

*

Small denominations are less than $100,000.

†

Large denominations are greater than or equal to $100,000.

Source: Economic Report of the President, U.S. Government Printing Office, 2001; and Flow of Funds Accounts: Flows and Outstandings, Board of Governors of the Federal Reserve System, June 2000.

Short-term government securities issued at a discount from face value and returning the face amount at maturity.

certificate of deposit A bank time deposit.

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Part ONE Elements of Investments

fixed term of the CD. CDs issued in denominations larger than $100,000 are usually negotiable, however; that is, they can be sold to another investor if the owner needs to cash in the certificate before its maturity date. Short-term CDs are highly marketable, although the market significantly thins out for maturities of three months or more. CDs are treated as bank deposits by the Federal Deposit Insurance Corporation, so they are insured for up to $100,000 in the event of a bank insolvency.

Commercial Paper

commercial paper Short-term unsecured debt issued by large corporations.

The typical corporation is a net borrower of both long-term funds (for capital investments) and short-term funds (for working capital). Large, well-known companies often issue their own short-term unsecured debt notes directly to the public, rather than borrowing from banks. These notes are called commercial paper (CP). Sometimes, CP is backed by a bank line of credit, which gives the borrower access to cash that can be used if needed to pay off the paper at maturity. CP maturities range up to 270 days; longer maturities require registration with the Securities and Exchange Commission and so are almost never issued. CP most commonly is issued with maturities of less than one or two months in denominations of multiples of $100,000. Therefore, small investors can invest in commercial paper only indirectly, through money market mutual funds. CP is considered to be a fairly safe asset, given that a firm’s condition presumably can be monitored and predicted over a term as short as one month. It is worth noting, though, that many firms issue commercial paper intending to roll it over at maturity, that is, issue new paper to obtain the funds necessary to retire the old paper. If lenders become complacent about monitoring a firm’s prospects and grant rollovers willy-nilly, they can suffer big losses. When Penn Central defaulted in 1970, it had $82 million of commercial paper outstanding—the only major default on commercial paper in the past 40 years. CP trades in secondary markets and so is quite liquid. Most issues are rated by at least one agency such as Standard & Poor’s. The yield on CP depends on the time to maturity and the credit rating.

Bankers’ Acceptances bankers’ acceptance An order to a bank by a customer to pay a sum of money at a future date.

A bankers’ acceptance starts as an order to a bank by a bank’s customer to pay a sum of money at a future date, typically within six months. At this stage, it is like a postdated check. When the bank endorses the order for payment as “accepted,” it assumes responsibility for ultimate payment to the holder of the acceptance. At this point, the acceptance may be traded in secondary markets much like any other claim on the bank. Bankers’ acceptances are considered very safe assets, as they allow traders to substitute the bank’s credit standing for their own. They are used widely in foreign trade where the creditworthiness of one trader is unknown to the trading partner. Acceptances sell at a discount from the face value of the payment order, just as T-bills sell at a discount from par value.

Eurodollars Eurodollars Dollar-denominated deposits at foreign banks or foreign branches of American banks.

Eurodollars are dollar-denominated deposits at foreign banks or foreign branches of American banks. By locating outside the United States, these banks escape regulation by the Federal Reserve Board. Despite the tag “Euro,” these accounts need not be in European banks, although that is where the practice of accepting dollar-denominated deposits outside the United States began.

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Most Eurodollar deposits are for large sums, and most are time deposits of less than six months’ maturity. A variation on the Eurodollar time deposit is the Eurodollar certificate of deposit. A Eurodollar CD resembles a domestic bank CD except it is the liability of a non-U.S. branch of a bank, typically a London branch. The advantage of Eurodollar CDs over Eurodollar time deposits is that the holder can sell the asset to realize its cash value before maturity. Eurodollar CDs are considered less liquid and riskier than domestic CDs, however, and so offer higher yields. Firms also issue Eurodollar bonds, that is, dollar-denominated bonds outside the U.S., although such bonds are not a money market investment by virtue of their long maturities.

Repos and Reverses Dealers in government securities use repurchase agreements, also called repos, or RPs, as a form of short-term, usually overnight, borrowing. The dealer sells securities to an investor on an overnight basis, with an agreement to buy back those securities the next day at a slightly higher price. The increase in the price is the overnight interest. The dealer thus takes out a oneday loan from the investor. The securities serve as collateral for the loan. A term repo is essentially an identical transaction, except the term of the implicit loan can be 30 days or more. Repos are considered very safe in terms of credit risk because the loans are backed by the government securities. A reverse repo is the mirror image of a repo. Here, the dealer finds an investor holding government securities and buys them with an agreement to resell them at a specified higher price on a future date.

repurchase agreements (repos) Short-term sales of government securities with an agreement to repurchase the securities at a higher price.

Brokers’ Calls Individuals who buy stocks on margin borrow part of the funds to pay for the stocks from their broker. The broker in turn may borrow the funds from a bank, agreeing to repay the bank immediately (on call) if the bank requests it. The rate paid on such loans is usually about one percentage point higher than the rate on short-term T-bills.

Federal Funds Just as most of us maintain deposits at banks, banks maintain deposits of their own at the Federal Reserve Bank, or the Fed. Each member bank of the Federal Reserve System is required to maintain a minimum balance in a reserve account with the Fed. The required balance depends on the total deposits of the bank’s customers. Funds in the bank’s reserve account are called Federal funds or Fed funds. At any time, some banks have more funds than required at the Fed. Other banks, primarily big New York and other financial center banks, tend to have a shortage of Federal funds. In the Federal funds market, banks with excess funds lend to those with a shortage. These loans, which are usually overnight transactions, are arranged at a rate of interest called the Federal funds rate. While the Fed funds rate is not directly relevant to investors, it is used as one of the barometers of the money market and so is widely watched by them.

Federal funds Funds in the accounts of commercial banks at the Federal Reserve Bank.

The LIBOR Market The London Interbank Offer Rate (LIBOR) is the rate at which large banks in London are willing to lend money among themselves. This rate has become the premier short-term interest rate quoted in the European money market and serves as a reference rate for a wide range of transactions. A corporation might borrow at a rate equal to LIBOR plus two percentage points, for example. Like the Fed funds rate, LIBOR is a statistic widely followed by investors.

LIBOR Lending rate among banks in the London market.

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Part ONE Elements of Investments

5.0

OPEC I

4.5 4.0 Percentage points

3.5

OPEC II Penn Square

3.0 2.5

Market Crash

2.0

LTCM

1.5 1.0 0.5 0 1970

1975

1980

1985

1990

1995

2000

F I G U R E 2.2 Spread between three-month CD and T-bill rates

Yields on Money Market Instruments Although most money market securities are of low risk, they are not risk-free. As we noted earlier, the commercial paper market was rocked by the Penn Central bankruptcy, which precipitated a default on $82 million of commercial paper. Money market investments became more sensitive to creditworthiness after this episode, and the yield spread between low- and high-quality paper widened. The securities of the money market do promise yields greater than those on default-free T-bills, at least in part because of greater relative riskiness. Investors who require more liquidity also will accept lower yields on securities, such as T-bills, that can be more quickly and cheaply sold for cash. Figure 2.2 shows that bank CDs, for example, consistently have paid a risk premium over T-bills. Moreover, that risk premium increases with economic crises such as the energy price shocks associated with the Organization of Petroleum Exporting Countries (OPEC) disturbances, the failure of Penn Square Bank, the stock market crash in 1987, or the collapse of Long Term Capital Management in 1998.

2.2

THE BOND MARKET

The bond market is composed of longer-term borrowing or debt instruments than those that trade in the money market. This market includes Treasury notes and bonds, corporate bonds, municipal bonds, mortgage securities, and federal agency debt. These instruments are sometimes said to comprise the fixed-income capital market, because most of them promise either a fixed stream of income or stream of income that is determined according to a specified formula. In practice, these formulas can result in a flow of

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F I G U R E 2.3 Listing of Treasury issues Source: From The Wall Street Journal, October 19, 2001. Reprinted by permission of Dow Jones & Company, Inc. via Copyright Clearance Center, Inc. © 2001 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

income that is far from fixed. Therefore, the term “fixed income” is probably not fully appropriate. It is simpler and more straightforward to call these securities either debt instruments or bonds.

Treasury Notes and Bonds The U.S. government borrows funds in large part by selling Treasury notes and bonds. T-note maturities range up to 10 years, while T-bonds are issued with maturities ranging from 10 to 30 years. The Treasury announced in late 2001 that it would no longer issue bonds with maturities beyond 10 years. Nevertheless, investors often refer to all of these securities collectively as Treasury or T-bonds. They are issued in denominations of $1,000 or more. Both bonds and notes make semiannual interest payments called coupon payments, so named because in precomputer days, investors would literally clip a coupon attached to the bond and present it to an agent of the issuing firm to receive the interest payment. Aside from their differing maturities at issuance, the only major distinction between T-notes and T-bonds is that Tbonds may be callable during a given period, usually the last five years of the bond’s life. The call provision gives the Treasury the right to repurchase the bond at par value. While callable T-bonds still are outstanding, the Treasury no longer issues callable bonds. Figure 2.3 is an excerpt from a listing of Treasury issues in The Wall Street Journal. The highlighted bond matures in August 2009. The coupon income or interest paid by the bond is 6% of par value, meaning that for a $1,000 face value bond, $60 in annual interest payments will be made in two semiannual installments of $30 each. The numbers to the right of the colon in the bid and ask prices represent units of 1⁄32 of a point.

Treasury notes or bonds Debt obligations of the federal government with original maturities of one year or more.

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The bid price of the highlighted bond is 110 6⁄32, or 110.1875. The ask price is 110 9⁄32, or 110.28125. Although bonds are sold in denominations of $1,000 par value, the prices are quoted as a percentage of par value. Thus, the ask price of 110.28125 should be interpreted as 110.28125% of par or $1,102.8125 for the $1,000 par value bond. Similarly, the bond could be sold to a dealer for $1,101.875. The ⫺3 change means the closing price on this day fell 3⁄32 (as a percentage of par value) from the previous day’s closing price. Finally, the yield to maturity on the bond based on the ask price is 4.43%. The yield to maturity reported in the last column is a measure of the annualized rate of return to an investor who buys the bond and holds it until maturity. It is calculated by determining the semiannual yield and then doubling it, rather than compounding it for two half-year periods. This use of a simple interest technique to annualize means that the yield is quoted on an annual percentage rate (APR) basis rather than as an effective annual yield. The APR method in this context is also called the bond equivalent yield. We discuss the yield to maturity in detail in Chapter 9.

Federal Agency Debt Some government agencies issue their own securities to finance their activities. These agencies usually are formed for public policy reasons to channel credit to a particular sector of the economy that Congress believes is not receiving adequate credit through normal private sources. Figure 2.4 reproduces listings of some of these securities from The Wall Street Journal. The major mortgage-related agencies are the Federal Home Loan Bank (FHLB), the Federal National Mortgage Association (FNMA, or Fannie Mae), the Government National Mortgage Association (GNMA, or Ginnie Mae), and the Federal Home Loan Mortgage Corporation (FHLMC, or Freddie Mac). Freddie Mac, Fannie Mae, and Ginnie Mae were organized to provide liquidity to the mortgage market. Until establishment of the pass-through securities sponsored by these government agencies, the lack of a secondary market in mortgages hampered the flow of investment

F I G U R E 2.4 Listing of government agency securities Source: From The Wall Street Journal, October 19, 2001. Reprinted by permission of Dow Jones & Company, Inc. via Copyright Clearance Center, Inc. © 2001 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

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funds into mortgages and made mortgage markets dependent on local, rather than national, credit availability. The pass-through financing initiated by these agencies represents one of the most important financial innovations of the 1980s. Although the debt of federal agencies is not explicitly insured by the federal government, it is assumed the government will assist an agency nearing default. Thus, these securities are considered extremely safe assets, and their yield spread over Treasury securities is usually small. 1. Using Figures 2.3 and 2.4, compare the yield to maturity on one of the agency bonds with that of the T-bond with the nearest maturity date.

> > > >

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Describe the role of investment bankers in primary issues. Identify the various security markets. Compare trading practices in stock exchanges with those in dealer markets. Describe the role of brokers. Compare the mechanics and investment implications of buying on margin and short selling.

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Related Websites http://www.nasdaq.com www.nyse.com http://www.amex.com These sites contain information and listing requirements for each of the markets. They also provide substantial data on equities.

http://www.spglobal.com This site contains information on construction of Standard & Poor’s Indexes and has links to most major exchanges.

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http://www.ipo.com http://www.unlockdates.com http://www.123jump.com/ipomaven.htm http://moneycentral.msn.com/investor/market/ipo main.asp These sites contain information on initial public offerings.

http://www.sec.gov/index.htm http://www.nasdr.com These sites provide information on market regulation and trading.

he first time a security trades is when it is issued. Therefore, we begin our examination of trading with a look at how securities are first marketed to the public by investment bankers, the midwives of securities. Then, we turn to the various exchanges where already-issued securities can be traded among investors. We examine the competition among the New York Stock Exchange, regional exchanges, Nasdaq, and several foreign markets for the patronage of security traders. Next, we turn to the mechanics of trading in these various markets. We describe the role of the specialist in exchange markets and the dealer in over-the-counter markets. We also touch briefly on block trading and the SuperDot system of the NYSE for electronically routing orders to the floor of the exchange. We discuss the costs of trading and consider the ongoing debate between the NYSE and its competitors over which market provides the lowest-cost trading arena. Finally, we describe the essentials of specific transactions, such as buying on margin and selling stock short and discuss relevant regulations governing security trading. In the process, we will see that some regulations, such as those governing insider trading, can be difficult to interpret in practice.

T

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Market for new issues of securities.

secondary market Market for alreadyexisting securities.

initial public offering (IPO) First sale of stock by a formerly private company.

underwriters Underwriters purchase securities from the issuing company and resell them.

prospectus A description of the firm and the security it is issuing.

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3.1 primary market

I. Elements of Investments

HOW FIRMS ISSUE SECURITIES

When firms need to raise capital they may choose to sell or float securities. These new issues of stocks, bonds, or other securities typically are marketed to the public by investment bankers in what is called the primary market. Trading of already-issued securities among investors occurs in the secondary market. There are two types of primary market issues of common stock. Initial public offerings, or IPOs, are stocks issued by a formerly privately owned company that is going public, that is, selling stock to the public for the first time. Seasoned new issues are offered by companies that already have floated equity. For example, a sale by IBM of new shares of stock would constitute a seasoned new issue. In the case of bonds, we also distinguish between two types of primary market issues, a public offering and a private placement. The former refers to an issue of bonds sold to the general investing public that can then be traded on the secondary market. The latter refers to an issue that usually is sold to one or a few institutional investors and is generally held to maturity.

Investment Banking Public offerings of both stocks and bonds typically are marketed by investment bankers who in this role are called underwriters. More than one investment banker usually markets the securities. A lead firm forms an underwriting syndicate of other investment bankers to share the responsibility for the stock issue. Investment bankers advise the firm regarding the terms on which it should attempt to sell the securities. A preliminary registration statement must be filed with the Securities and Exchange Commission (SEC), describing the issue and the prospects of the company. This preliminary prospectus is known as a red herring because it includes a statement printed in red, stating that the company is not attempting to sell the security before the registration is approved. When the statement is in final form, and approved by the SEC, it is called the prospectus. At this point, the price at which the securities will be offered to the public is announced. In a typical underwriting arrangement, the investment bankers purchase the securities from the issuing company and then resell them to the public. The issuing firm sells the securities to the underwriting syndicate for the public offering price less a spread that serves as compensation to the underwriters. This procedure is called a firm commitment; the underwriters receive the issue and assume the risk that the shares cannot be sold to the public at the stipulated offering price. Figure 3.1 depicts the relationships among the firm issuing the security, the lead underwriter, the underwriting syndicate, and the public. An alternative to the firm commitment is the best-efforts agreement. In this case, the investment banker does not actually purchase the securities but agrees to help the firm sell the issue to the public. The banker simply acts as an intermediary between the public and the firm and does not bear the risk of not being able to resell purchased securities at the offering price. The best-efforts procedure is more common for initial public offerings of common stock, where the appropriate share price is less certain. Corporations engage investment bankers either by negotiation or competitive bidding, although negotiation is far more common. In addition to the compensation resulting from the spread between the purchase price and the public offering price, an investment banker may receive shares of common stock or other securities of the firm. As part of its marketing of the firm’s securities, the underwriting syndicate typically takes out advertisements in the financial press to announce the prospective sale. An example of

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F I G U R E 3.1

Issuing firm

Relationship among a firm issuing securities, the underwriters, and the public

Lead underwriter Underwriting syndicate Investment Banker A

Investment Banker B

Investment Banker C

Investment Banker D

Private investors

these so-called tombstone advertisements is given in Figure 3.2. The underwriters plan to sell 115 million shares of stock at a price of $18.50 each, to raise $2,127.5 million for the Principal Financial Group. The four lead underwriters are presented in larger type; the firms taking a smaller role in marketing the securities are presented below in smaller type. Most of the shares will be sold in the U.S., but 15% of the issue will be sold abroad. Notice that the underwriters for the non-U.S. portion of the issue have far greater international representation.

Shelf Registration An important innovation in the issuing of securities was introduced in 1982 when the SEC approved Rule 415, which allows firms to register securities and gradually sell them to the public for two years following the initial registration. Because the securities are already registered, they can be sold on short notice, with little additional paperwork. Moreover, they can be sold in small amounts without incurring substantial flotation costs. The securities are “on the shelf,” ready to be issued, which has given rise to the term shelf registration. 1. Why does it make sense for shelf registration to be limited in time?

Private Placements Primary offerings also can be sold in a private placement rather than a public offering. In this case, the firm (using an investment banker) sells shares directly to a small group of institutional or wealthy investors. Private placements can be far cheaper than public offerings. This is because Rule 144A of the SEC allows corporations to make these placements without preparing the extensive and costly registration statements required of a public offering. On the other hand, because private placements are not made available to the general public, they generally will be less suited for very large offerings. Moreover, private placements do not trade in secondary markets like stock exchanges. This greatly reduces their liquidity and presumably reduces the prices that investors will pay for the issue.

Initial Public Offerings Investment bankers manage the issuance of new securities to the public. Once the SEC has commented on the registration statement and a preliminary prospectus has been distributed to

The third market refers to trading of exchange-listed securities on the over-the-counter market. In the past, members of an exchange were required to execute all their trades of exchangelisted securities on the exchange and to charge commissions according to a fixed schedule. This procedure was disadvantageous to large traders when it prevented them from realizing economies of scale on large trades. Because of this restriction, brokerage firms that were not members of the NYSE and so not bound by its rules, established trading in the OTC market of large NYSE-listed stocks. These trades could be accomplished at lower commissions than would have been charged on the NYSE, and the third market grew dramatically until 1972, when the NYSE allowed negotiated commissions on orders exceeding $300,000. On May 1, 1975, frequently referred to as “May Day,” commissions on all NYSE orders became negotiable, and they have been ever since. 2. Look again at Table 3.1, which gives the history of seat prices on the NYSE. Interpret the data for 1975 in light of the changes instituted on May Day. The fourth market refers to direct trading between investors in exchange-listed securities without the benefit of a broker. The direct trading among investors that characterizes the fourth market has exploded in recent years due to the advent of electronic communication networks, or ECNs. ECNs are an alternative to either formal stock exchanges like the NYSE or dealer markets like Nasdaq for trading securities. These ECNs allow members to post buy or sell orders and to have those orders matched up or “crossed” with orders of other traders in

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the system. Both sides of the trade benefit because direct crossing eliminates the bid–ask spread that otherwise would be incurred. Early versions of ECNs were available exclusively to large institutional traders. In addition to cost savings, systems such as Instinet and Posit allowed these large traders greater anonymity than they could otherwise achieve. This was important to the traders since they did not want to publicly signal their desire to buy or sell large quantities of shares for fear of moving prices in advance of their trades. Posit also enabled trading in portfolios as well as individual stocks. ECNs have captured about 30% of the trading volume in Nasdaq-listed stocks. They must be certified by the SEC and registered with the National Association of Security Dealers to participate in the Nasdaq market. Table 3.5 is a list of registered ECNs at the start of 2001. While small investors today typically do not access an ECN directly, they can send orders through their brokers, including online brokers, who can then have the order executed on the ECN. Eventually, individuals will likely have direct access to most ECNs through the Internet. In fact, several financial firms (Goldman, Sachs; Merrill Lynch; Salomon Smith Barney; Morgan Stanley; and Bernard Madoff) have combined to build an electronic trading network called Primex, which is open to NASD broker/dealers, who in turn have the ability to offer public access to the market. Other ECNs, such as Instinet, which have traditionally served institutional investors, are considering opening up their services to retail brokerages. The advent of ECNs is putting increasing pressure on the NYSE to respond. In particular, big brokerage firms such as Goldman, Sachs and Merrill Lynch are calling for the NYSE to beef up its capabilities to automate orders without human intervention. Moreover, as they push the NYSE to change, these firms are hedging their bets by investing in ECNs on their own. The NYSE also has announced its intention to go public. In its current organization as a member-owned cooperative, it needs the approval of members to institute major changes. However, many of these members are precisely the floor brokers who will be most hurt by electronic trading. This has made it difficult for the NYSE to respond flexibly to the challenge of electronic trading. By converting to a publicly held for-profit corporate organization, it hopes to be able to compete more vigorously in the marketplace of stock markets.

fourth market

3

TA B L E 3.5 Registered Electronic Communication Networks (ECNs)

Archipelago Attain B-Trade Services The BRASS Utility Instinet Corporation The Island ECN Market XT NexTrade REDIbook

Source: Nasdaq in Black & White, Nasdaq, 2001.

The National Market System The Securities Act Amendments of 1975 directed the Securities and Exchange Commission to implement a national competitive securities market. Such a market would entail centralized reporting of transactions and a centralized quotation system, with the aim of enhanced competition among market makers. In 1975, Consolidated Tape began reporting trades on the NYSE, Amex, and major regional exchanges, as well as trades of Nasdaq-listed stocks. In 1977, the Consolidated Quotations Service began providing online bid and ask quotes for NYSE securities also traded on various other exchanges. This has enhanced competition by allowing market participants, including

Direct trading in exchange-listed securities between one investor and another without the benefit of a broker.

electronic communication networks (ECNs) Computer networks that allow direct trading without the need for market makers.

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brokers or dealers who are at different locations, to interact and for orders to be directed to the market in which the best price can be obtained. In 1978, the Intermarket Trading System (ITS) was implemented. ITS currently links nine exchanges by computer (NYSE, Amex, Boston, Cincinnati, Pacific, Philadelphia, Chicago, Nasdaq, and the Chicago Board Options Exchange). Nearly 5,000 issues are eligible for trading on the ITS; these account for most of the securities that are traded on more than one exchange. The system allows brokers and market makers to display and view quotes for all markets and to execute cross-market trades when the Consolidated Quotation System shows better prices in other markets. For example, suppose a specialist firm on the Boston Exchange is currently offering to buy a security for $20, but a broker in Boston who is attempting to sell shares for a client observes a superior bid price on the NYSE, say $20.12. The broker should route the order to the specialist’s post on the NYSE, where it can be executed at the higher price. The transaction is then reported on the Consolidated Tape. Moreover, a specialist who observes a better price on another exchange is also expected either to match that price or route the trade to that market. While the ITS does much to unify markets, it has some important shortcomings. First, it does not provide for automatic execution in the market with the best price. The trade must be directed there by a market participant, who might find it inconvenient (or unprofitable) to do so. Moreover, some feel that the ITS is too slow to integrate prices off the NYSE. A logical extension of the ITS as a means to integrate securities markets would be the establishment of a central limit order book. Such an electronic “book” would contain all orders conditional on both prices and dates. All markets would be linked and all traders could compete for all orders. While market integration seems like a desirable goal, the recent growth of ECNs has led to some concern that markets are in fact becoming more fragmented. This is because participants in one ECN do not necessarily know what prices are being quoted on other networks. ECNs do display their best-priced offers on the Nasdaq system, but other limit orders are not available. Only stock exchanges may participate in the Intermarket Trading System, which means that ECNs are excluded. Moreover, during the after-hours trading enabled by ECNs, trades take place on these private networks while other larger markets are closed, and current prices for securities are harder to access. In the wake of growing concern about market fragmentation, some big Wall Street brokerage houses have called for an electronically driven central limit order book. But full market integration has proven to be elusive.

Bond Trading The New York Stock Exchange also operates a bond exchange where U.S. government, corporate, municipal, and foreign bonds may be traded. The centerpiece of the NYSE bond market is the Automated Bond System (ABS), which is an automated trading system that allows trading firms to obtain market information, to enter and execute trades over a computer network, and to receive immediate confirmations of trade execution. However, the vast majority of bond trading occurs in the OTC market among bond dealers, even for bonds that are actually listed on the NYSE. This market is a network of bond dealers such as Merrill Lynch, Salomon Smith Barney, or Goldman, Sachs that is linked by a computer quotation system. However, because these dealers do not carry extensive inventories of the wide range of bonds that have been issued to the public, they cannot necessarily offer to sell bonds from their inventory to clients or even buy bonds for their own inventory. They may instead work to locate an investor who wishes to take the opposite side of a trade. In practice, however, the corporate bond market often is quite “thin,” in that there may be few investors interested in trading a bond at any particular time. As a result, the bond market is subject to a type of liquidity risk, for it can be difficult to sell one’s holdings quickly if the need arises.

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WEBMA STER Electronic Communication Networks Go to the New York Federal Reserve’s website, http://www.ny.frb.org/rmaghome/ curr_iss/ci6-12. html, to read “The Emergence of Electronic Communication Networks (ECNs) in the U.S. Equity Markets,” by James McAndrews and Chris Stefanadis, researchers at the Federal Reserve Bank of New York. After reading this article, answer the following questions: 1.

What is an ECN and how does it differ from a traditional market such as the NYSE?

2.

List and briefly describe the four potential advantages of an ECN as identified by the authors.

3.

What risk is related to the fragmentation that may accompany the development of the ECNs?

Listing Requirements Go to www.nasdaq.com/sitemap/sitemap.stm. On the sitemap there is an item labeled listing information. Select that item and identify the following items in Initial Listing Standards for the National Market System 1, 2, and 3 and the Nasdaq SmallCap Market for domestic companies: 1.

Public float in millions of shares.

2.

Market value of public float.

3.

Shareholders of round lots.

Go to www.nyse.com and select the listed company item or information bullet. Under the bullet select the listing standards tab. Identify the same items for NYSE (U.S. Standards) initial listing requirements. 4.

3.3

In what two categories are the listing requirements most significantly different?

TRADING ON EXCHANGES

Most of the information in this section applies to all securities traded on exchanges. Some of it, however, applies just to stocks, and in such cases we use the specific words, stocks or shares.

The Participants We begin our discussion of the mechanics of exchange trading with a brief description of the potential parties to a trade. When an investor instructs a broker to buy or sell securities, a number of players must act to consummate the deal. The investor places an order with a broker. The brokerage firm for which the broker works, and which owns a seat on the exchange, contacts its commission broker, who is on the floor of the exchange, to execute the order. When the firm’s commission brokers are overloaded and have too many orders to handle, they will use the services of floor brokers, who are independent members of the exchange (and own seats), to execute orders. The specialist is central to the trading process. All trading in a given stock takes place at one location on the floor of the exchange called the specialist’s post. At the specialist’s post is a monitor called the Display Book that presents all the current offers from interested traders to buy or sell shares at various prices as well as the number of shares these quotes are good for.

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The specialist manages the trading in the stock. The market making responsibility for each stock is assigned by the NYSE to one specialist firm. There is only one specialist firm per stock but most firms will have responsibility for trading in several stocks. The specialist firm also may act as a dealer in the stock, trading for its own account. We will examine the role of the specialist in more detail shortly.

Types of Orders Market orders Market orders are simply buy or sell orders that are to be executed immediately at current market prices. For example, an investor might call his broker and ask for the market price of IBM. The retail broker will wire this request to the commission broker on the floor of the exchange, who will approach the specialist’s post and ask the specialist for best current quotes. Finding that the current quotes are $98 per share bid, and $98.10 asked, the investor might direct the broker to buy 100 shares “at market,” meaning that he is willing to pay $98.10 per share for an immediate transaction. Similarly, an order to “sell at market” will result in stock sales at $98 per share. (Until 2001, when U.S. markets adopted decimal pricing, the minimum possible bid–ask spread was “one tick,” which on the NYSE was $ 1⁄8 until 1997 and $ 1⁄16 thereafter. With decimal pricing, the spread can be far lower.) When a trade is executed, the specialist’s clerk will fill out an order card that reports the time, price, and quantity of shares traded and the transaction will be reported on the exchange’s ticker tape. There are two potential complications to this simple scenario, however. First, as noted earlier, the posted quotes of $98 and $98.10 actually represent commitments to trade up to a specified number of shares. If the market order is for more than this number of shares, the order may be filled at multiple prices. For example, if the asked price is good for orders up to 600 shares and the investor wishes to purchase 1,000 shares, it may be necessary to pay a slightly higher price for the last 400 shares than the quoted asked price. The second complication arises from the possibility of trading “inside the quoted spread.” If the broker who has received a market buy order for IBM meets another broker who has received a market sell order for IBM, they can agree to trade with each other at a price of $98.05 per share. By meeting in the middle of the quoted spread, both the buyer and the seller obtain “price improvements,” that is, transaction prices better than the best quoted prices. Such “meetings” of brokers are more than accidental. Because all trading takes place at the specialist’s post, floor brokers know where to look for counterparties to take the other side of a trade.

Limit orders Investors also may choose to place a limit order, where they specify prices at which they are willing to buy or sell a security. If IBM is selling at $98 bid, $98.10 asked, for example, a limit buy order may instruct the broker to buy the stock if and when the share price falls below $97. Correspondingly, a limit sell order instructs the broker to sell as soon as the stock price goes above the specified limit. Figure 3.5 is a portion of the limit order book for shares in Intel on the Island exchange on one day in 2001. Notice that the best orders are at the top of the list: the offers to buy at the highest price and to sell at the lowest price. The buy and sell orders at the top of the list— $27.88 and $27.93—are called the inside quotes; they are the buy and sell orders with the closest prices. For Intel, the inside spread is only 5 cents per share. What happens if a limit order is placed in between the quoted bid and ask prices? For example, suppose you have instructed your broker to buy IBM at a price of $98.05 or better. The order may not be executed immediately, since the quoted asked price for the shares is $98.10, which is more than you are willing to pay. However, your willingness to buy at $98.05 is better than the quoted bid price of $98 per share. Therefore, you may find that there are traders who were unwilling to sell their shares at the currently quoted $98 bid price but are happy to sell shares to you at your higher bid price of $98.05.

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refresh

island home

disclamer

help GET STOCK INTC go

INTC LAST MATCH Price 27.8900 Time 14:24:45

TODAY’S ACTIVITY Orders 16,774 Volume 4,631,778

BUY ORDERS Shares Price 100 27.8800 500 27.8500 200 27.8500 1,000 27.8200 3,300 27.8100 300 27.8000 75 27.7500 101 27.7300 5,000 27.7200 1,000 27.72 (416 more)

SELL ORDERS Shares Price 1,000 27.9300 1,000 27.9690 1,000 27.9800 1,000 27.9900 1,000 28.0000 1,800 28.0600 1,000 28.0800 1,000 28.1000 2,000 28.1100 1,000 28,1800 (395 more)

Condition Price below Price above the limit the limit

Limit buy order

Stop-buy order

Sell

Stop-loss order

Limit sell order

Action

Buy

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Stop-loss orders are similar to limit orders in that the trade is not to be executed unless the stock hits a price limit. Here, however, the stock is to be sold if its price falls below a stipulated level. As the name suggests, the order lets the stock be sold to stop further losses from accumulating. Similarly, stop-buy orders specify that a stock should be bought when its price rises above a limit. These trades often accompany short sales (sales of securities you don’t own but have borrowed from your broker) and are used to limit potential losses from the short position. Short sales are discussed in greater detail later in this chapter. Figure 3.6 organizes these types of trades in a convenient matrix. Orders also can be limited by a time period. Day orders, for example, expire at the close of the trading day. If it is not executed on that day, the order is canceled. Open or good-tillcanceled orders, in contrast, remain in force for up to six months, unless canceled by the customer.

F I G U R E 3.5 The limit order book for Intel on the Island exchange, November 9, 2001.

F I G U R E 3.6 Limit orders

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Specialists and the Execution of Trades specialist A trader who makes a market in the shares of one or more firms and who maintains a “fair and orderly market” by dealing personally in the market.

A specialist “makes a market” in the shares of one or more firms. This task may require the specialist to act as either a broker or a dealer. The specialist’s role as a broker is simply to execute the orders of other brokers. Specialists also may buy or sell shares of stock for their own portfolios. When no other broker can be found to take the other side of a trade, specialists will do so even if it means they must buy for or sell from their own accounts. The NYSE commissions these companies to perform this service and monitors their performance. Part of the specialist’s job as a broker is simply clerical. The specialist maintains a “book” listing all outstanding unexecuted limit orders entered by brokers on behalf of clients. Actually, the book is now a computer console. When limit orders can be executed at market prices, the specialist executes, or “crosses,” the trade. The specialist is required to use the highest outstanding offered purchase price and the lowest outstanding offered selling price when matching trades. Therefore, the specialist system results in an auction market, meaning all buy and all sell orders come to one location, and the best orders “win” the trades. In this role, the specialist acts merely as a facilitator. The more interesting function of the specialist is to maintain a “fair and orderly market” by acting as a dealer in the stock. In return for the exclusive right to make the market in a specific stock on the exchange, the specialist is required by the exchange to maintain an orderly market by buying and selling shares from inventory. Specialists maintain their own portfolios of stock and quoted bid and ask prices at which they are obligated to meet at least a limited amount of market orders. If market buy orders come in, specialists must sell shares from their own accounts at the ask price; if sell orders come in, they must stand willing to buy at the listed bid price.4 Ordinarily, however, in an active market, specialists can match buy and sell orders without using their own accounts. That is, the specialist’s own inventory of securities need not be the primary means of order execution. Sometimes, the specialist’s bid and ask prices are better than those offered by any other market participant. Therefore, at any point, the effective ask price in the market is the lower of either the specialist’s ask price or the lowest of the unfilled limit-sell orders. Similarly, the effective bid price is the highest of the unfilled limit buy orders or the specialist’s bid. These procedures ensure that the specialist provides liquidity to the market. In practice, specialists participate in approximately one-quarter of the transactions on the NYSE. By standing ready to trade at quoted bid and ask prices, the specialist is exposed to exploitation by other traders. Larger traders with ready access to superior information will trade with specialists when the specialist’s quotes are temporarily out of line with assessments of value based on that information. Specialists who cannot match the information resources of large traders will be at a disadvantage when their quoted prices offer profit opportunities to more advantaged traders. You might wonder why specialists do not protect their interests by setting a low bid price and a high ask price. Specialists using that strategy would protect themselves from losses in a period of dramatic movements in the stock price. In contrast, specialists who offer a narrow spread between the bid and ask price have little leeway for error and must constantly monitor market conditions to avoid offering other investors advantageous terms. Large bid–ask spreads are not viable options for the specialist for two reasons. First, one source of the specialist’s income is frequent trading at the bid and ask prices, with the spread as a trading profit. A too-large spread would make the specialist’s quotes uncompetitive with the limit orders placed by other traders. If the specialist’s bid and asked quotes are consistently 4

The specialist’s published quotes are valid only for a given number of shares. If a buy or sell order is placed for more shares than the quotation size, the specialist has the right to revise the quote.

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worse than those of public traders, the specialist will not participate in any trades and will lose the ability to profit from the bid–ask spread. An equally important reason that specialists cannot use large bid–ask spreads to protect their interests is that they are obligated to provide price continuity to the market. To illustrate the principle of price continuity, suppose the highest limit buy order for a stock is $30, while the lowest limit sell order is $32. When a market buy order comes in, it is matched to the best limit sell at $32. A market sell order would be matched to the best limit buy at $30. As market buys and sells come to the floor randomly, the stock price would fluctuate between $30 and $32. The exchange authorities would consider this excessive volatility, and the specialist would be expected to step in with bid and/or ask prices between these values to reduce the bid–ask spread to an acceptable level, typically less than $.15 for large firms. When a firm is newly listed on an exchange, specialist firms vigorously compete to be awarded the rights by the exchange to maintain the market in those shares. Since specialists are evaluated on their past performance in maintaining price continuity, they have considerable incentive to maintain tight spreads. Specialists earn income both from commissions for acting as brokers for orders and from the spreads at which they buy and sell securities. Some believe specialists’ access to their “books” of limit orders gives them unique knowledge about the probable direction of price movement over short periods of time. However, these days, interested floor traders also have access to the Display Books of outstanding limit orders. For example, suppose the specialist sees that a stock now selling for $45 has limit buy orders for over 100,000 shares at prices ranging from $44.50 to $44.75. This latent buying demand provides a cushion of support, in that it is unlikely that enough sell pressure will come in during the next few hours to cause the price to drop below $44.50. If there are very few limit sell orders above $45, in contrast, some transient buying demand could raise the price substantially. The specialist in such circumstances realizes that a position in the stock offers little downside risk and substantial upside potential. Such access to the trading intentions of other market participants seems to allow a specialist and agile floor traders to earn profits on personal transactions and for selected clients. One can easily overestimate such advantages, however, because ever more of the large orders are negotiated “upstairs,” that is, as fourth-market deals.

Block Sales Institutional investors frequently trade blocks of tens of thousands of shares of stock. Table 3.6 shows that block transactions of over 10,000 shares now account for about half of all trading. The larger block transactions are often too large for specialists to handle, as they do not wish to hold such large blocks of stock in their inventory. For example, the largest block transaction in the first half of 2001 was for 34 million shares of USX-Marathon stock.

TA B L E 3.6 Block transactions on the New York Stock Exchange

block transactions Large transactions in which at least 10,000 shares of stock are bought or sold.

Year

Shares (millions)

% Reported Volume

Average Number of Block Transactions per Day

1965 1970 1975 1980 1985 1990 1995 2000

48 451 779 3,311 14,222 19,682 49,737 135,772

3.1% 15.4 16.6 29.2 51.7 49.6 57.0 51.7

9 68 136 528 2,139 3,333 7,793 21,941

Source: Data from the New York Stock Exchange Fact Book, 2001.

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“Block houses” have evolved to aid in the placement of larger block trades. Block houses are brokerage firms that specialize in matching block buyers and sellers. Once a buyer and a seller have been matched, the block is sent to the exchange floor where specialists execute the trade. If a buyer cannot be found, the block house might purchase all or part of a block sale for its own account. The block house then can resell the shares to the public.

The SuperDot System

program trade Coordinated sale or purchase of a portfolio of stocks.

SuperDot enables exchange members to send orders directly to the specialist’s Display Book over computer lines. The largest market order that can be handled is 30,099 shares. In 2000, SuperDot processed an average of 1.5 million orders per day; the average time to execute market orders submitted through SuperDot was 15 seconds. SuperDot is especially useful to program traders. A program trade is a coordinated purchase or sale of an entire portfolio of stocks. Many trading strategies (such as index arbitrage, a topic we will study in Chapter 16) require that an entire portfolio of stocks be purchased or sold simultaneously in a coordinated program. SuperDot is the tool that enables many trading orders to be sent out at once and executed almost simultaneously. The vast majority of all orders are submitted through SuperDot. However, these tend to be smaller orders and account for only a bit more than half of total share volume.

Settlement Since June 1995, an order executed on the exchange must be settled within three working days. This requirement is often called T ⫹ 3, for trade date plus three days. The purchaser must deliver the cash, and the seller must deliver the stock to the broker, who in turn delivers it to the buyer’s broker. Frequently, a firm’s clients keep their securities in street name, which means the broker holds the shares registered in the firm’s own name on behalf of the client. This convention can speed security transfer. T ⫹ 3 settlement has made such arrangements more important: It can be quite difficult for a seller of a security to complete delivery to the purchaser within the three-day period if the stock is kept in a safe deposit box. Settlement is simplified further by the existence of a clearinghouse. The trades of all exchange members are recorded each day, with members’ transactions netted out, so that each member need transfer or receive only the net number of shares sold or bought that day. An exchange member then settles with the clearinghouse instead of individually with every firm with which it made trades.

3.4

TRADING ON THE OTC MARKET

On the exchanges, all trading occurs through a specialist. On the over-the-counter (OTC) market, however, trades are negotiated directly through dealers who maintain an inventory of selected securities. Dealers sell from their inventories at ask prices and buy for them at bid prices. An investor who wishes to purchase or sell shares engages a broker who tries to locate the dealer offering the best deal on the security. This is in contrast to exchange trading, where all buy or sell orders are negotiated through the specialist, who arranges for the best bids to get the trade. In the OTC market, brokers must search the offers of dealers directly to find the best trading opportunity. In this sense, Nasdaq is a price quotation system, not a trading system. While bid and ask prices can be obtained from the Nasdaq computer network, the actual trade still requires direct negotiation (often over the phone) between the broker and the dealer in the security. However, in the wake of the stock market crash of 1987, Nasdaq instituted a Small Order Execution System (SOES), which is in effect a trading system. Under SOES, market makers

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in a security who post bid or ask prices on the Nasdaq network may be contacted over the network by other traders and are required to trade at the prices they currently quote. Dealers must accept SOES orders at their posted prices up to a limit which may be 1,000 shares, but usually is smaller, depending on factors such as trading volume in the stock. Because the Nasdaq system does not use a specialist, OTC trades do not require a centralized trading floor as do exchange-listed stocks. Dealers can be located anywhere they can communicate effectively with other buyers and sellers. One disadvantage of the decentralized dealer market is that the investing public is vulnerable to trading through, which refers to the possibility that dealers can trade with the public at their quoted bid or asked prices even if other customers have offered to trade at better prices. A dealer who posts $20 bid and $20.15 asked prices for a stock may continue to fill market buy orders at the ask price and fill market sell orders at the bid price—even if there are limit orders by public customers “inside the spread,” for example, limit orders to buy at $20.05 or limit orders to sell at $20.10. This practice harms the investor whose limit order is not filled (is “traded through”) as well as the investor whose market buy or sell order is not filled at the best available price. Trading through on Nasdaq sometimes results from imperfect coordination among dealers. A limit order placed with one broker may not be seen by brokers for other traders because computer systems are not linked and only the broker’s own bid and asked prices are posted on the Nasdaq system. In contrast, trading through is strictly forbidden on the NYSE or Amex, where “price priority” requires that the specialist fill the best-priced order first. Moreover, because all traders in an exchange market must trade through the specialist, the exchange provides true price discovery, meaning that market prices reflect the prices at which all participants at that moment are willing to trade. This is the advantage of a centralized auction market. In October 1994, the Justice Department announced an investigation of the Nasdaq Stock Market regarding possible collusion among market makers to maintain spreads at artificially high levels. In 1996, the Justice Department settled with the Nasdaq dealers. The dealers agreed to refrain from pressuring any other market maker to maintain wide spreads and from refusing to deal with other traders who try to undercut an existing spread. Also in 1996, the SEC settled with the National Association of Securities Dealers (NASD) as well as with the Nasdaq stock market. The settlement called for NASD to take steps to prohibit market makers from colluding on spreads. In addition, the SEC mandated the following three rules on Nasdaq dealers: 1. Publicly display all limit orders. Limit orders from all investors that exceed 100 shares must now be displayed. Therefore, the quoted bid or ask price for a stock must now be the best price quoted by any investor, not simply the best dealer quote. This shrinks the effective spread on the stock. 2. Make best dealer quotes public. Nasdaq dealers must now disclose whether they have posted better quotes in private trading systems or ECNs such as Instinet than they are quoting in the Nasdaq market. 3. Reveal the size of best customer limit orders. For example, if a dealer quotes an offer to buy 1,000 shares of stock at a quoted bid price and a customer places a limit buy order for 500 shares at the same price, the dealer must advertise the bid price as good for 1,500 shares.

Market Structure in Other Countries The structure of security markets varies considerably from one country to another. A full cross-country comparison is far beyond the scope of this text. Therefore, we will instead

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briefly review three of the biggest non-U.S. stock markets: the London, Euronext, and Tokyo exchanges. Figure 3.7 shows the volume of trading in major world markets.

London Until 1997, trading arrangements in London were similar to those on Nasdaq. Competing dealers who wished to make a market in a stock would enter bid and ask prices into the Stock Exchange Automated Quotations (SEAQ) system. As in the U.S., London security firms acted as both dealers and as brokerage firms, that is, both making a market in securities and executing trades for their clients. In 1997, the London Stock Exchange introduced an electronic trading system dubbed SETS (Stock Exchange Electronic Trading Service). This is an electronic clearing system similar to ECNs in which buy and sell orders are submitted via computer networks and any buy and sell orders that can be crossed are executed automatically. Most trading in London equities is now conducted using SETS, particularly for shares in larger firms. However, SEAQ continues to operate and may be more likely to be used for the “upstairs market” in large block transactions or other less liquid transactions.

Euronext Euronext was formed in 2000 by a merger of the Paris, Amsterdam, and Brussels exchanges. Euronext, like most European exchanges, uses an electronic trading system. Its system, called NSC (for Nouveau Système de Cotation, or New Quotation System), has fully automated order routing and execution. In fact, investors can enter their orders directly without contacting their brokers. An order submitted to the system is executed immediately if it can be crossed against an order in the public limit order book; if it cannot be executed, it is entered into the limit order book. Euronext is in the process of establishing cross-trading agreements with several other European exchanges such as Helsinki or Luxembourg. In 2001, it also purchased LIFFE, the London International Financial Futures and Options Exchange.

22,500

Dollar volume of equity trading in major world markets, 2000

20,000

12,500 10,000 7,500 5,000

Toronto

Switzerland

Amsterdam*

Amex

Madrid

Taiwan

Italy

Germany

Tokyo

0

Paris*

2,500 London

The Paris and Amsterdam exchanges have (together with the Brussels exchange) merged to form the Euronext exchange. Although the exchanges have been integrated, trading continues to be conducted in each of these cities.

15,000

New York

*

17,500

Nasdaq

Source: International Federation of Stock Exchanges, www.fibv.com.

Annual trading volume ($ billion)

F I G U R E 3.7

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Tokyo The Tokyo Stock Exchange (TSE) is the largest stock exchange in Japan, accounting for about 80% of total trading. There is no specialist system on the TSE. Instead, a saitori maintains a public limit order book, matches market and limit orders, and is obliged to follow certain actions to slow down price movements when simple matching of orders would result in price changes greater than exchange-prescribed minimums. In their clerical role of matching orders, saitoris are somewhat similar to specialists on the NYSE. However, saitoris do not trade for their own accounts, and therefore they are quite different from either dealers or specialists in the United States. Because the saitori performs an essentially clerical role, there are no market making services or liquidity provided to the market by dealers or specialists. The limit order book is the primary provider of liquidity. In this regard, the TSE bears some resemblance to the fourth market in the United States, in which buyers and sellers trade directly via networks such as Instinet or Posit. On the TSE, however, if order imbalances result in price movements across sequential trades that are considered too extreme by the exchange, the saitori may temporarily halt trading and advertise the imbalance in the hope of attracting additional trading interest to the “weak” side of the market. The TSE organizes stocks into two categories. The First Section consists of about 1,200 of the most actively traded stocks. The Second Section is for about 400 of the less actively traded stocks. Trading in the larger First Section stocks occurs on the floor of the exchange. The remaining securities in the First Section and the Second Section trade electronically.

Globalization of Stock Markets All stock markets have come under increasing pressure in recent years to make international alliances or mergers. Much of this pressure is due to the impact of electronic trading. To a growing extent, traders view stock markets as computer networks that link them to other traders, and there are increasingly fewer limits on the securities around the world that they can trade. Against this background, it becomes more important for exchanges to provide the cheapest and most efficient mechanism by which trades can be executed and cleared. This argues for global alliances that can facilitate the nuts and bolts of cross-border trading and can benefit from economies of scale. Moreover, in the face of competition from electronic networks, established exchanges feel that they eventually need to offer 24-hour global markets. Finally, companies want to be able to go beyond national borders when they wish to raise capital. Merger talks and international strategic alliances blossomed in the late 1990s. We have noted the Euronext merger as well as its alliance with other European exchanges. The Stockholm, Copenhagen, and Oslo exchanges formed a “Nordic Country Alliance” in 1999. In the last few years, Nasdaq has instituted a pilot program to co-list shares on the Stock Exchange of Hong Kong; has launched Nasdaq Europe, Nasdaq Japan, and Nasdaq Canada markets; and has entered negotiations on joint ventures with both the London and Frankfurt exchanges. The NYSE and Tokyo Stock Exchange are exploring the possibility of common listing standards. The NYSE also is exploring the possibility of an alliance with Euronext, in which the shares of commonly listed large multinational firms could be traded on both exchanges. In the wake of the stock market decline of 2001–2002, however, globalization initiatives have faltered. With less investor interest in markets and a dearth of initial public offerings, both Nasdaq Europe and Nasdaq Japan have been less successful, and Nasdaq reportedly was considering pulling out of its Japanese venture. Meanwhile, many markets are increasing their international focus. For example, Nasdaq and the NYSE each list over 400 non-U.S. firms, and foreign firms account for about 10% of trading volume on the NYSE.

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3.5

TRADING COSTS

Part of the cost of trading a security is obvious and explicit. Your broker must be paid a commission. Individuals may choose from two kinds of brokers: full-service or discount brokers. Full-service brokers who provide a variety of services often are referred to as account executives or financial consultants. Besides carrying out the basic services of executing orders, holding securities for safekeeping, extending margin loans, and facilitating short sales, brokers routinely provide information and advice relating to investment alternatives. Full-service brokers usually depend on a research staff that prepares analyses and forecasts of general economic as well as industry and company conditions and often makes specific buy or sell recommendations. Some customers take the ultimate leap of faith and allow a fullservice broker to make buy and sell decisions for them by establishing a discretionary account. In this account, the broker can buy and sell prespecified securities whenever deemed fit. (The broker cannot withdraw any funds, though.) This action requires an unusual degree of trust on the part of the customer, for an unscrupulous broker can “churn” an account, that is, trade securities excessively with the sole purpose of generating commissions. Discount brokers, on the other hand, provide “no-frills” services. They buy and sell securities, hold them for safekeeping, offer margin loans, and facilitate short sales, and that is all. The only information they provide about the securities they handle is price quotations. Discount brokerage services have become increasingly available in recent years. Many banks, thrift institutions, and mutual fund management companies now offer such services to the investing public as part of a general trend toward the creation of one-stop “financial supermarkets.” The commission schedule for trades in common stocks for one prominent discount broker is as follows:

bid–ask spread The difference between a dealer’s bid and asked price.

Transaction Method

Commission

Online trading Automated telephone trading Orders desk (through an associate)

$20 or $0.02 per share, whichever is greater $40 or $0.02 per share, whichever is greater $45 ⫹ $0.03 per share

Notice that there is a minimum charge regardless of trade size and cost as a fraction of the value of traded shares falls as trade size increases. Note also that these prices (and most advertised prices) are for the cheapest market orders. Limit orders are more expensive. In addition to the explicit part of trading costs—the broker’s commission—there is an implicit part—the dealer’s bid–ask spread. Sometimes the broker is a dealer in the security being traded and charges no commission but instead collects the fee entirely in the form of the bid–ask spread. Another implicit cost of trading that some observers would distinguish is the price concession an investor may be forced to make for trading in any quantity that exceeds the quantity the dealer is willing to trade at the posted bid or asked price. One continuing trend is toward online trading either through the Internet or through software that connects a customer directly to a brokerage firm. In 1994, there were no online brokerage accounts; only five years later, there were around 7 million such accounts at “e brokers” such as Ameritrade, Charles Schwab, Fidelity, and E*Trade, and roughly one in five trades was initiated over the Internet. While there is little conceptual difference between placing your order using a phone call versus through a computer link, online brokerage firms can process trades more cheaply since they do not have to pay as many brokers. The average commission for an online trade is now less than $20, compared to perhaps $100–$300 at full-service brokers.

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SEC Prepares for a New World of Stock Trading What should our securities markets look like to serve today’s investor best? Congress addressed this very question a generation ago, when markets were threatened with fragmentation from an increasing number of competing dealers and exchanges. This led the SEC to establish the national market system, which enabled investors to obtain the best quotes on stocks from any of the major exchanges. Today it is the proliferation of electronic exchanges and after-hours trading venues that threatens to fragment the market. But the solution is simple, and would take the intermarket trading system devised by the SEC a quarter century ago to its next logical step. The highest bid and the lowest offer for every stock, no matter where they originate, should be displayed on a screen that would be available to all investors, 24 hours a day, seven days a week. If the SEC mandated this centralization of order flow, competition would significantly enhance investor choice and the quality of the trading environment. Would brokerage houses or even exchanges exist, as we now know them? I believe so, but electronic communication networks would provide the crucial links between buyers and sellers. ECNs would compete by providing far more sophisticated services to the investor than are currently available—not only the entering and execution of standard limit and market orders, but the execution of contingent orders, buys and sells dependent on the levels of other stocks, bonds, commodities, even indexes. The services of brokerage houses would still be in much demand, but their transformation from commission-based to flat-fee or asset-based pricing would be accelerated. Although ECNs will offer almost

costless processing of the basic investor transactions, brokerages would aid investors in placing more sophisticated orders. More importantly, brokers would provide investment advice. Although today’s investor has access to more and more information, this does not mean that he has more understanding of the forces that rule the market or the principles of constructing the best portfolio. As the spread between the best bid and offer price has collapsed, some traditional concerns of regulators are less pressing than they once were. Whether to allow dealers to step in front of customers to buy or sell, or allow brokerages to cross their orders internally at the best price, regardless of other orders at the price on the book, have traditionally been burning regulatory issues. But with spreads so small and getting smaller, these issues are of virtually no consequence to the average investor as long as the integrity of the order flow information is maintained. None of this means that the SEC can disappear once it establishes the central order-flow system. A regulatory authority is needed to monitor the functioning of the new systems and ensure that participants live up to their promises. The rise of technology threatens many established power centers and has prompted some to call for more controls and a go-slow approach. By making clear that the commission’s role is to encourage competition to best serve investors, not to impose or dictate the ultimate structure of the markets, the SEC is poised to take stock trading into the new millennium. SOURCE: Abridged from Jeremy J. Siegel, “The SEC Prepares for a New World of Stock Trading,” The Wall Street Journal, September 27, 1999. Reprinted by permission of Dow Jones & Company, Inc. via Copyright Clearance Center, Inc. © 1999 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

Moreover, these e-brokers are beginning to provide some of the same services offered by full-service brokers such as online company research and, to a lesser extent, the opportunity to participate in IPOs. The traditional full-service brokerage firms have responded to this competitive challenge by introducing online trading for their own customers. Some of these firms are charging by the trade; others charge for such trading through fee-based accounts, in which the customer pays a percentage of assets in the account for the right to trade online. An ongoing controversy between the NYSE and its competitors is the extent to which better execution on the NYSE offsets the generally lower explicit costs of trading in other markets. Execution refers to the size of the effective bid–ask spread and the amount of price impact in a market. The NYSE believes that many investors focus too intently on the costs they can see, despite the fact that quality of execution can be a far more important determinant of total costs. Many NYSE trades are executed at a price inside the quoted spread. This can happen because floor brokers at the specialist’s post can bid above or sell below the specialist’s quote. In this way, two public orders can cross without incurring the specialist’s spread. In contrast, in a dealer market, all trades go through the dealer, and all trades, therefore, are subject to a bid–ask spread. The client never sees the spread as an explicit cost, however. The

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price at which the trade is executed incorporates the dealer’s spread, but this part of the price is never reported to the investor. Similarly, regional markets are disadvantaged in terms of execution because their lower trading volume means that fewer brokers congregate at a specialist’s post, resulting in a lower probability of two public orders crossing. A controversial practice related to the bid–ask spread and the quality of trade execution is “paying for order flow.” This entails paying a broker a rebate for directing the trade to a particular dealer rather than to the NYSE. By bringing the trade to a dealer instead of to the exchange, however, the broker eliminates the possibility that the trade could have been executed without incurring a spread. In fact, the opportunity to profit from the bid–ask spread is the major reason that the dealer is willing to pay the broker for the order flow. Moreover, a broker that is paid for order flow might direct a trade to a dealer that does not even offer the most competitive price. (Indeed, the fact that dealers can afford to pay for order flow suggests that they are able to lay off the trade at better prices elsewhere and, possibly, that the broker also could have found a better price with some additional effort.) Many of the online brokerage firms rely heavily on payment for order flow, since their explicit commissions are so minimal. They typically do not actually execute orders, instead sending an order either to a market maker or to a stock exchange for listed stocks. Such practices raise serious ethical questions, because the broker’s primary obligation is to obtain the best deal for the client. Payment for order flow might be justified if the rebate is passed along to the client either directly or through lower commissions, but it is not clear that such rebates are passed through. Online trading and electronic communications networks have already changed the landscape of the financial markets, and this trend can only be expected to continue. The nearby box considers some of the implications of these new technologies for the future structure of financial markets.

3.6

margin Describes securities purchased with money borrowed in part from a broker. The margin is the net worth of the investor’s account.

BUYING ON MARGIN

When purchasing securities, investors have easy access to a source of debt financing called broker’s call loans. The act of taking advantage of broker’s call loans is called buying on margin. Purchasing stocks on margin means the investor borrows part of the purchase price of the stock from a broker. The margin in the account is the portion of the purchase price contributed by the investor; the remainder is borrowed from the broker. The brokers in turn borrow money from banks at the call money rate to finance these purchases; they then charge their clients that rate (defined in Chapter 2), plus a service charge for the loan. All securities purchased on margin must be maintained with the brokerage firm in street name, for the securities are collateral for the loan. The Board of Governors of the Federal Reserve System limits the extent to which stock purchases can be financed using margin loans. The current initial margin requirement is 50%, meaning that at least 50% of the purchase price must be paid for in cash, with the rest borrowed. The percentage margin is defined as the ratio of the net worth, or the “equity value,” of the account to the market value of the securities. To demonstrate, suppose an investor initially pays $6,000 toward the purchase of $10,000 worth of stock (100 shares at $100 per share), borrowing the remaining $4,000 from a broker. The initial balance sheet looks like this: Assets Value of stock

Liabilities and Owners’ Equity $10,000

Loan from broker Equity

$4,000 $6,000

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The initial percentage margin is Margin ⫽

Equity in account $6,000 ⫽ ⫽ .60, or 60% Value of stock $10,000

If the stock’s price declines to $70 per share, the account balance becomes: Assets Value of stock

Liabilities and Owners’ Equity $7,000

Loan from broker Equity

$4,000 $3,000

The assets in the account fall by the full decrease in the stock value, as does the equity. The percentage margin is now Margin ⫽

Equity in account $3,000 ⫽ ⫽ .43, or 43% Value of stock $7,000

If the stock value were to fall below $4,000, owners’ equity would become negative, meaning the value of the stock is no longer sufficient collateral to cover the loan from the broker. To guard against this possibility, the broker sets a maintenance margin. If the percentage margin falls below the maintenance level, the broker will issue a margin call, which requires the investor to add new cash or securities to the margin account. If the investor does not act, the broker may sell securities from the account to pay off enough of the loan to restore the percent age margin to an acceptable level. Margin calls can occur with little warning. For example, on April 14, 2000, when the Nasdaq index fell by a record 355 points, or 9.7%, the accounts of many investors who had purchased stock with borrowed funds ran afoul of their maintenance margin requirements. Some brokerage houses, concerned about the incredible volatility in the market and the possibility that stock prices would fall below the point that remaining shares could cover the amount of the loan, gave their customers only a few hours or less to meet a margin call rather than the more typical notice of a few days. If customers could not come up with the cash, or were not at a phone to receive the notification of the margin call until later in the day, their accounts were sold out. In other cases, brokerage houses sold out accounts without notifying their customers. The nearby box discussed this episode. An example will show how maintenance margin works. Suppose the maintenance margin is 30%. How far could the stock price fall before the investor would get a margin call? Answering this question requires some algebra. Let P be the price of the stock. The value of the investor’s 100 shares is then 100P, and the equity in the account is 100P ⫺ $4,000. The percentage margin is (100P ⫺ $4,000)/100P. The price at which the percentage margin equals the maintenance margin of .3 is found by solving the equation 100P ⫺ 4,000 ⫽ .3 100P which implies that P ⫽ $57.14. If the price of the stock were to fall below $57.14 per share, the investor would get a margin call. 3. Suppose the maintenance margin is 40%. How far can the stock price fall before the investor gets a margin call?

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Buying on Margin

The Excel spreadsheet model below is built using the text example for IBM. The model makes it easy to analyze the impacts of different margin levels and the volatility of stock prices. It also allows you to compare return on investment for a margin trade with a trade using no borrowed funds. The original price ranges for the text example are highlighted for your reference. You can learn more about this spreadsheet model using the interactive version available on our website at www.mhhe.com/bkm.

A 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

B

Buying on Margin Initial Equity Investment Amount Borrowed Initial Stock Price Shares Purchased Ending Stock Price Cash Dividends During Hold Per. Initial Margin Percentage Maintenance Margin Percentage

C

D

E

Ending St Price 10,000.00 10,000.00 100.00 200 130.00 0.00 50.00% 30.00%

Rate on Margin Loan Holding Period in Months

9.00% 12

Return on Investment Capital Gain on Stock Dividends Interest on Margin Loan Net Income Initial Investment Return on Investment

6000.00 0.00 900.00 5100.00 10000.00 51.00%

Margin Call: Margin Based on Ending Price Price When Margin Call Occurs

61.54% $71.43

Return on Stock without Margin

30.00%

30 40 50 60 70 80 90 100 110 120 130 140 150

F

Return on Investment 51.00% -149.00% -129.00% -109.00% -89.00% -69.00% -49.00% -29.00% -9.00% 11.00% 31.00% 51.00% 71.00% 91.00%

G

H

Ending St Price

Return with No Margin 30.00% -70.00% -60.00% -50.00% -40.00% -30.00% -20.00% -10.00% 0.00% 10.00% 20.00% 30.00% 40.00% 50.00%

30 40 50 60 70 80 90 100 110 120 130 140 150

The 200 shares will be worth $26,000. Paying off $10,900 of principal and interest on the margin loan leaves $15,100 (i.e., $26,000 ⫺ $10,900). The rate of return in this case will be $15,100 ⫺ $10,000 ⫽ 51% $10,000 The investor has parlayed a 30% rise in the stock’s price into a 51% rate of return on the $10,000 investment. Doing so, however, magnifies the downside risk. Suppose that, instead of going up by 30%, the price of IBM stock goes down by 30% to $70 per share. In that case, the 200 shares will be worth $14,000, and the investor is left with $3,100 after paying off the $10,900 of principal and interest on the loan. The result is a disastrous return of 3,100 ⫺ 10,000 10,000

⫽ ⫺69% 85

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Table 3.7 summarizes the possible results of these hypothetical transactions. If there is no change in IBM’s stock price, the investor loses 9%, the cost of the loan.

Concept CHECK

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4. Suppose that in the previous example, the investor borrows only $5,000 at the same interest rate of 9% per year. What will the rate of return be if the price of IBM goes up by 30%? If it goes down by 30%? If it remains unchanged?

3.7

short sale The sale of shares not owned by the investor but borrowed through a broker and later purchased to replace the loan.

TA B L E 3.7 Illustration of buying stock on margin

SHORT SALES

Normally, an investor would first buy a stock and later sell it. With a short sale, the order is reversed. First, you sell and then you buy the shares. In both cases, you begin and end with no shares. A short sale allows investors to profit from a decline in a security’s price. An investor borrows a share of stock from a broker and sells it. Later, the short-seller must purchase a share of the same stock in the market in order to replace the share that was borrowed. This is called covering the short position. Table 3.8 compares stock purchases to short sales. The short-seller anticipates the stock price will fall, so that the share can be purchased later at a lower price than it initially sold for; if so, the short-seller will reap a profit. Short-sellers must not only replace the shares but also pay the lender of the security any dividends paid during the short sale. In practice, the shares loaned out for a short sale are typically provided by the short-seller’s brokerage firm, which holds a wide variety of securities of its other investors in street name. Change in Stock Price

End-of-Year Value of Shares

Repayment of Principal and Interest*

Investor’s Rate of Return

30% increase No change 30% decrease

$26,000 20,000 14,000

$10,900 10,900 10,900

51% ⫺9 ⫺69

*Assuming the investor buys $20,000 worth of stock by borrowing $10,000 as an interest rate of 9% per year.

Purchase of Stock

TA B L E 3.8 Cash flows from purchasing versus short-selling shares of stock

Cash Flow*

Time

Action

0 1

Buy share Receive dividend, sell share

⫺ Initial price Ending price ⫹ Dividend

Profit ⫽ (Ending price ⫹ Dividend) ⫺ Initial price

Short Sale of Stock Time

Action

0 1

Borrow share: sell it Repay dividend and buy share to replace the share originally borrowed

Cash Flow ⫹ Initial price ⫺ (Ending price ⫹ Dividend)

Profit ⫽ Initial price ⫺ (Ending price ⫹ Dividend) *Note: A negative cash flow implies a cash outflow.

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The owner of the shares need not know that the shares have been lent to the short-seller. If the owner wishes to sell the shares, the brokerage firm will simply borrow shares from another investor. Therefore, the short sale may have an indefinite term. However, if the brokerage firm cannot locate new shares to replace the ones sold, the short-seller will need to repay the loan immediately by purchasing shares in the market and turning them over to the brokerage house to close out the loan. Exchange rules permit short sales only when the last recorded change in the stock price is positive. This rule apparently is meant to prevent waves of speculation against the stock. In essence, the votes of “no confidence” in the stock that short sales represent may be entered only after a price increase. Finally, exchange rules require that proceeds from a short sale must be kept on account with the broker. The short-seller cannot invest these funds to generate income, although large or institutional investors typically will receive some income from the proceeds of a short sale being held with the broker. Short-sellers also are required to post margin (cash or collateral) with the broker to cover losses should the stock price rise during the short sale. To illustrate the mechanics of short-selling, suppose you are bearish (pessimistic) on Dot Bomb stock, and its market price is $100 per share. You tell your broker to sell short 1,000 shares. The broker borrows 1,000 shares either from another customer’s account or from another broker. The $100,000 cash proceeds from the short sale are credited to your account. Suppose the broker has a 50% margin requirement on short sales. This means you must have other cash or securities in your account worth at least $50,000 that can serve as margin on the short sale. Let’s say that you have $50,000 in Treasury bills. Your account with the broker after the short sale will then be: Assets Cash T-bills

Liabilities and Owners’ Equity

$100,000 50,000

Short position in Dot Bomb stock (1,000 shares owed) Equity

$100,000 50,000

Your initial percentage margin is the ratio of the equity in the account, $50,000, to the current value of the shares you have borrowed and eventually must return, $100,000: Percentage margin ⫽

Equity $50,000 ⫽ ⫽ .50 Value of stock owed $100,000

Suppose you are right and Dot Bomb falls to $70 per share. You can now close out your position at a profit. To cover the short sale, you buy 1,000 shares to replace the ones you borrowed. Because the shares now sell for $70, the purchase costs only $70,000.5 Because your account was credited for $100,000 when the shares were borrowed and sold, your profit is $30,000: The profit equals the decline in the share price times the number of shares sold short. On the other hand, if the price of Dot Bomb goes up unexpectedly while you are short, you may get a margin call from your broker. Suppose the broker has a maintenance margin of 30% on short sales. This means the equity in your account must be at least 30% of the value of your short position at all times. How much can the price of Dot Bomb stock rise before you get a margin call? 5

Notice that when buying on margin, you borrow a given amount of dollars from your broker, so the amount of the loan is independent of the share price. In contrast, when short-selling you borrow a given number of shares, which must be returned. Therefore, when the price of the shares changes, the value of the loan also changes.

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E XCEL Applications

>

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Short Sale

This Excel spreadsheet model was built using the text example for Dot Bomb. The model allows you to analyze the effects of returns, margin calls, and different levels of initial and maintenance margins. The model also includes a sensitivity analysis for ending stock price and return on investment. The original price for the text example is highlighted for your reference. You can learn more about this spreadsheet model using the interactive version available on our website at www.mhhe.com/bkm. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

A Chapter 3 Short Sale Dot Bomb Short Sale

B

Initial Investment Beginning Share Price Number of Shares Sold Short Ending Share Price Dividends Per Share Initial Margin Percentage Maintenance Margin Percentage

50000.00 100.00 1000.00 70.00 0.00 50.00% 30.00%

Return on Short Sale Gain or Loss on Price Dividends Paid Net Income Return on Investment

30000.00 0.00 30000.00 60.00%

Margin Positions Margin Based on Ending Price

114.29%

Price for Margin Call

C

D

E

F

Ending Return on St Price Investment 60.00% 40 120.00% 50 100.00% 60 80.00% 70 60.00% 80 40.00% 90 20.00% 100 0.00% 110 -20.00% 120 -40.00% 130 -60.00%

115.38

Let P be the price of Dot Bomb stock. Then the value of the shares you must pay back is 1,000P, and the equity in your account is $150,000 ⫺ 1,000P. Your short position margin ratio is equity/value of stock ⫽ (150,000 ⫺ 1,000P)/1,000P. The critical value of P is thus Equity 150,000 ⫺1,000P ⫽ ⫽ .3 Value of shares owed 1,000P which implies that P ⫽ $115.38 per share. If Dot Bomb stock should rise above $115.38 per share, you will get a margin call, and you will either have to put up additional cash or cover your short position by buying shares to replace the ones borrowed.

Concept CHECK

88

>

5. a. Construct the balance sheet if Dot Bomb goes up to $110. b. If the short position maintenance margin in the Dot Bomb example is 40%, how far can the stock price rise before the investor gets a margin call? You can see now why stop-buy orders often accompany short sales. Imagine that you short sell Dot Bomb when it is selling at $100 per share. If the share price falls, you will profit from the short sale. On the other hand, if the share price rises, let’s say to $130, you will lose $30 per share. But suppose that when you initiate the short sale, you also enter a stop-buy order at $120. The stop-buy will be executed if the share price surpasses $120, thereby limiting your losses to $20 per share. (If the stock price drops, the stop-buy will never be executed.) The stop-buy order thus provides protection to the short-seller if the share price moves up.

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3.8

How Securities Are Traded

REGUL ATION OF SECURITIES MARKETS

Trading in securities markets in the United States is regulated by a myriad of laws. The major governing legislation includes the Securities Act of 1933 and the Securities Exchange Act of 1934. The 1933 Act requires full disclosure of relevant information relating to the issue of new securities. This is the act that requires registration of new securities and issuance of a prospectus that details the financial prospects of the firm. SEC approval of a prospectus or financial report is not an endorsement of the security as a good investment. The SEC cares only that the relevant facts are disclosed; investors must make their own evaluation of the security’s value. The 1934 Act established the Securities and Exchange Commission to administer the provisions of the 1933 Act. It also extended the disclosure principle of the 1933 Act by requiring periodic disclosure of relevant financial information by firms with already-issued securities on secondary exchanges. Of course, disclosure is valuable only if the information disclosed faithfully represents the condition of the firm; in the wake of the corporate reporting scandals of 2001 and 2002, confidence in such reports justifiably waned. Under legislation passed in 2002, CEOs and chief financial officers of public firms will be required to swear to the accuracy and completeness of the major financial statements filed by their firms. The 1934 Act also empowers the SEC to register and regulate securities exchanges, OTC trading, brokers, and dealers. While the SEC is the administrative agency responsible for broad oversight of the securities markets, it shares responsibility with other regulatory agencies. The Commodity Futures Trading Commission (CFTC) regulates trading in futures markets, while the Federal Reserve has broad responsibility for the health of the U.S. financial system. In this role, the Fed sets margin requirements on stocks and stock options and regulates bank lending to securities markets participants. The Securities Investor Protection Act of 1970 established the Securities Investor Protection Corporation (SIPC) to protect investors from losses if their brokerage firms fail. Just as the Federal Deposit Insurance Corporation provides depositors with federal protection against bank failure, the SIPC ensures that investors will receive securities held for their account in street name by a failed brokerage firm up to a limit of $500,000 per customer. The SIPC is financed by levying an “insurance premium” on its participating, or member, brokerage firms. It also may borrow money from the SEC if its own funds are insufficient to meet its obligations. In addition to federal regulations, security trading is subject to state laws, known generally as blue sky laws because they are intended to give investors a clearer view of investment prospects. State laws to outlaw fraud in security sales existed before the Securities Act of 1933. Varying state laws were somewhat unified when many states adopted portions of the Uniform Securities Act, which was enacted in 1956.

Self-Regulation and Circuit Breakers Much of the securities industry relies on self-regulation. The SEC delegates to secondary exchanges such as the NYSE much of the responsibility for day-to-day oversight of trading. Similarly, the National Association of Securities Dealers oversees trading of OTC securities. The Institute of Chartered Financial Analysts’ Code of Ethics and Professional Conduct sets out principles that govern the behavior of CFAs. The nearby box presents a brief outline of those principles. The market collapse of October 19, 1987, prompted several suggestions for regulatory change. Among these was a call for “circuit breakers” to slow or stop trading during periods of extreme volatility. Some of the current circuit breakers being used are as follows: • Trading halts. If the Dow Jones Industrial Average falls by 10%, trading will be halted for one hour if the drop occurs before 2:00 P.M. (Eastern Standard Time), for one-half hour if

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AIMR Standards of Professional Conduct STANDARD I: FUNDAMENTAL RESPONSIBILITIES Members shall maintain knowledge of and comply with all applicable laws, rules, and regulations including AIMR’s Code of Ethics and Standards of Professional Conduct.

STANDARD II: RESPONSIBILITIES TO THE PROFESSION • Professional misconduct. Members shall not engage in any professional conduct involving dishonesty, fraud, deceit, or misrepresentation, • Prohibition against plagiarism.

STANDARD III: RESPONSIBILITIES TO THE EMPLOYER • Obligation to inform employer of code and standards. Members shall inform their employer that they are obligated to comply with these Code and Standards. • Disclosure of additional compensation arrangements. Members shall disclose to their employer all benefits that they receive in addition to compensation from that employer.

STANDARD IV: RESPONSIBILITIES TO CLIENTS AND PROSPECTS • Investment process and research reports. Members shall exercise diligence and thoroughness in making investment recommendations . . . distinguish

between facts and opinions in research reports . . . and use reasonable care to maintain objectivity. • Interactions with clients and prospects. Members must place their clients’ interests before their own. • Portfolio investment recommendations. Members shall make a reasonable inquiry into a client’s financial situation, investment experience, and investment objectives prior to making appropriate investment recommendations . . . • Priority of transactions. Transactions for clients and employers shall have priority over transactions for the benefit of a member. • Disclosure of conflicts to clients and prospects. Members shall disclose to their clients and prospects all matters, including ownership of securities or other investments, that reasonably could be expected to impair the member’s ability to make objective recommendations.

STANDARD V: RESPONSIBILITIES TO THE PUBLIC • Prohibition against use of material nonpublic [inside] information. Members who possess material nonpublic information related to the value of a security shall not trade in that security. • Performance presentation. Members shall not make any statements that misrepresent the investment performance that they have accomplished or can reasonably be expected to achieve. SOURCE: Abridged from The Standards of Professional Conduct of the AIMR.

the drop occurs between 2:00 and 2:30, but not at all if the drop occurs after 2:30. If the Dow falls by 20%, trading will be halted for two hours if the drop occurs before 1:00 P.M., for one hour if the drop occurs between 1:00 and 2:00, and for the rest of the day if the drop occurs after 2:00. A 30% drop in the Dow would close the market for the rest of the day, regardless of the time. • Collars. When the Dow moves about two percentage points6 in either direction from the previous day’s close, Rule 80A of the NYSE requires that index arbitrage orders pass a “tick test.” In a falling market, sell orders may be executed only at a plus tick or zero-plus tick, meaning that the trade may be done at a higher price than the last trade (a plus tick) or at the last price if the last recorded change in the stock price is positive (a zero-plus tick). The rule remains in effect for the rest of the day unless the Dow returns to within one percentage point of the previous day’s close. 6

The exact threshold is computed as 2% of the value of the Dow, updated quarterly, rounded to the nearest 10 points.

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The idea behind circuit breakers is that a temporary halt in trading during periods of very high volatility can help mitigate informational problems that might contribute to excessive price swings. For example, even if a trader is unaware of any specific adverse economic news, if he sees the market plummeting, he will suspect that there might be a good reason for the price drop and will become unwilling to buy shares. In fact, he might decide to sell shares to avoid losses. Thus, feedback from price swings to trading behavior can exacerbate market movements. Circuit breakers give participants a chance to assess market fundamentals while prices are temporarily frozen. In this way, they have a chance to decide whether price movements are warranted while the market is closed. Of course, circuit breakers have no bearing on trading in non-U.S. markets. It is quite possible that they simply have induced those who engage in program trading to move their operations into foreign exchanges.

Insider Trading Regulations also prohibit insider trading. It is illegal for anyone to transact in securities to profit from inside information, that is, private information held by officers, directors, or major stockholders that has not yet been divulged to the public. But the definition of insiders can be ambiguous. While it is obvious that the chief financial officer of a firm is an insider, it is less clear whether the firm’s biggest supplier can be considered an insider. Yet a supplier may deduce the firm’s near-term prospects from significant changes in orders. This gives the supplier a unique form of private information, yet the supplier is not technically an insider. These ambiguities plague security analysts, whose job is to uncover as much information as possible concerning the firm’s expected prospects. The distinction between legal private information and illegal inside information can be fuzzy. An important Supreme Court decision in 1997, however, ruled on the side of an expansive view of what constitutes illegal insider trading. The decision upheld the so-called misappropriation theory of insider trading, which holds that traders may not trade on nonpublic information even if they are not company insiders. The SEC requires officers, directors, and major stockholders to report all transactions in their firm’s stock. A compendium of insider trades is published monthly in the SEC’s Official Summary of Securities Transactions and Holdings. The idea is to inform the public of any implicit vote of confidence or no confidence made by insiders. Insiders do exploit their knowledge. Three forms of evidence support this conclusion. First, there have been well-publicized convictions of principals in insider trading schemes. Second, there is considerable evidence of “leakage” of useful information to some traders before any public announcement of that information. For example, share prices of firms announcing dividend increases (which the market interprets as good news concerning the firm’s prospects) commonly increase in value a few days before the public announcement of the increase. Clearly, some investors are acting on the good news before it is released to the public. Similarly, share prices tend to increase a few days before the public announcement of abovetrend earnings growth. Share prices still rise substantially on the day of the public release of good news, however, indicating that insiders, or their associates, have not fully bid up the price of the stock to the level commensurate with the news. A third form of evidence on insider trading has to do with returns earned on trades by insiders. Researchers have examined the SEC’s summary of insider trading to measure the performance of insiders. In one of the best known of these studies, Jaffee (1974) examined the abnormal return of stocks over the months following purchases or sales by insiders. For months in which insider purchasers of a stock exceeded insider sellers of the stock by three or more, the stock had an abnormal return in the following eight months of about 5%. Moreover, when insider sellers exceeded insider buyers, the stock tended to perform poorly.

inside information Nonpublic knowledge about a corporation possessed by corporate officers, major owners, or other individuals with privileged access to information about the firm.

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Restriction of the use of inside information is not universal. Japan has no such prohibition. An argument in favor of free use of inside information is that investors are not misled to believe that the financial market is a level playing field for all. At the same time, free use of inside information means that such information will more quickly be reflected in stock prices. Most Americans believe, however, that it is valuable as well as virtuous to outlaw such advantage, even if less-than-perfect enforcement may leave the door open for some profitable violations of the law.

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SUMMARY

• Firms issue securities to raise the capital necessary to finance their investments. Investment bankers market these securities to the public on the primary market. Investment bankers generally act as underwriters who purchase the securities from the firm and resell them to the public at a markup. Before the securities may be sold to the public, the firm must publish an SEC-approved prospectus that provides information on the firm’s prospects. • Already-issued securities are traded on the secondary market, that is, on organized stock exchanges; the over-the-counter market; and for large trades, through direct negotiation. Only members of exchanges may trade on the exchange. Brokerage firms holding seats on the exchange sell their services to individuals, charging commissions for executing trades on their behalf. The NYSE maintains strict listing requirements. Regional exchanges provide listing opportunities for local firms that do not meet the requirements of the national exchanges. • Trading of common stocks on exchanges occurs through specialists. The specialist acts to maintain an orderly market in the shares of one or more firms. The specialist maintains “books” of limit buy and sell orders and matches trades at mutually acceptable prices. Specialists also accept market orders by selling from or buying for their own inventory of stocks when there is an imbalance of buy and sell orders. • The over-the-counter market is not a formal exchange but a network of brokers and dealers who negotiate sales of securities. The Nasdaq system provides online computer quotes offered by dealers in the stock. When an individual wishes to purchase or sell a share, the broker can search the listing of bid and ask prices, contact the dealer with the best quote, and execute the trade. • Block transactions are a fast-growing segment of the securities market that currently accounts for about half of trading volume. These trades often are too large to be handled readily by specialists and so have given rise to block houses that specialize in identifying potential trading partners for their clients. • Buying on margin means borrowing money from a broker in order to buy more securities than can be purchased with one’s own money alone. By buying securities on a margin, an investor magnifies both the upside potential and the downside risk. If the equity in a margin account falls below the required maintenance level, the investor will get a margin call from the broker. • Short-selling is the practice of selling securities that the seller does not own. The shortseller borrows the securities sold through a broker and may be required to cover the short position at any time on demand. The cash proceeds of a short sale are kept in escrow by the broker, and the broker usually requires that the short-seller deposit additional cash or securities to serve as margin (collateral) for the short sale. • Securities trading is regulated by the Securities and Exchange Commission, other government agencies, and self-regulation of the exchanges. Many of the important

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regulations have to do with full disclosure of relevant information concerning the securities in question. Insider trading rules also prohibit traders from attempting to profit from inside information. • In addition to providing the basic services of executing buy and sell orders, holding securities for safekeeping, making margin loans, and facilitating short sales, full-service brokers offer investors information, advice, and even investment decisions. Discount brokers offer only the basic brokerage services but usually charge less. Total trading costs consist of commissions, the dealer’s bid–ask spread, and price concessions.

inside information, 91 margin, 82 Nasdaq, 67 over-the-counter (OTC) market, 67 primary market, 60 private placement, 61 program trade, 76 prospectus, 60

secondary market, 60 short sale, 86 specialist, 74 stock exchanges, 65 third market, 68 underwriters, 60

1. FBN, Inc., has just sold 100,000 shares in an initial public offering. The underwriter’s explicit fees were $70,000. The offering price for the shares was $50, but immediately upon issue, the share price jumped to $53. a. What is your best guess as to the total cost to FBN of the equity issue? b. Is the entire cost of the underwriting a source of profit to the underwriters? 2. Suppose you short sell 100 shares of IBM, now selling at $120 per share. a. What is your maximum possible loss? b. What happens to the maximum loss if you simultaneously place a stop-buy order at $128? 3. Dée Trader opens a brokerage account, and purchases 300 shares of Internet Dreams at $40 per share. She borrows $4,000 from her broker to help pay for the purchase. The interest rate on the loan is 8%. a. What is the margin in Dée ’s account when she first purchases the stock? b. If the share price falls to $30 per share by the end of the year, what is the remaining margin in her account? If the maintenance margin requirement is 30%, will she receive a margin call? c. What is the rate of return on her investment? 4. Old Economy Traders opened an account to short sell 1,000 shares of Internet Dreams from the previous question. The initial margin requirement was 50%. (The margin account pays no interest.) A year later, the price of Internet Dreams has risen from $40 to $50, and the stock has paid a dividend of $2 per share. a. What is the remaining margin in the account? b. If the maintenance margin requirement is 30%, will Old Economy receive a margin call? c. What is the rate of return on the investment? 5. Do you think it is possible to replace market-making specialists with a fully automated, computerized trade-matching system? 6. Consider the following limit order book of a specialist. The last trade in the stock occurred at a price of $50.

KEY TERMS

PROBLEM SETS

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ask price, 67 bid–ask spread 80 bid price, 67 block transactions, 75 electronic communication networks (ECNs), 68 fourth market, 68 initial public offerings (IPOs), 60

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Limit Buy Orders

7.

8.

9.

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10.

Limit Sell Orders

Price

Shares

Price

Shares

$49.75 49.50 49.25 49.00 48.50

500 800 500 200 600

$50.25 51.50 54.75 58.25

100 100 300 100

a. If a market buy order for 100 shares comes in, at what price will it be filled? b. At what price would the next market buy order be filled? c. If you were the specialist, would you want to increase or decrease your inventory of this stock? You are bullish on Telecom stock. The current market price is $50 per share, and you have $5,000 of your own to invest. You borrow an additional $5,000 from your broker at an interest rate of 8% per year and invest $10,000 in the stock. a. What will be your rate of return if the price of Telecom stock goes up by 10% during the next year? (Ignore the expected dividend.) b. How far does the price of Telecom stock have to fall for you to get a margin call if the maintenance margin is 30%? Assume the price fall happens immediately. You are bearish on Telecom and decide to sell short 100 shares at the current market price of $50 per share. a. How much in cash or securities must you put into your brokerage account if the broker’s initial margin requirement is 50% of the value of the short position? b. How high can the price of the stock go before you get a margin call if the maintenance margin is 30% of the value of the short position? Suppose that Intel currently is selling at $40 per share. You buy 500 shares using $15,000 of your own money and borrowing the remainder of the purchase price from your broker. The rate on the margin loan is 8%. a. What is the percentage increase in the net worth of your brokerage account if the price of Intel immediately changes to: (i) $44; (ii) $40; (iii) $36? What is the relationship between your percentage return and the percentage change in the price of Intel? b. If the maintenance margin is 25%, how low can Intel’s price fall before you get a margin call? c. How would your answer to (b) change if you had financed the initial purchase with only $10,000 of your own money? d. What is the rate of return on your margined position (assuming again that you invest $15,000 of your own money) if Intel is selling after one year at: (i) $44; (ii) $40; (iii) $36? What is the relationship between your percentage return and the percentage change in the price of Intel? Assume that Intel pays no dividends. e. Continue to assume that a year has passed. How low can Intel’s price fall before you get a margin call? Suppose that you sell short 500 shares of Intel, currently selling for $40 per share, and give your broker $15,000 to establish your margin account. a. If you earn no interest on the funds in your margin account, what will be your rate of return after one year if Intel stock is selling at: (i) $44; (ii) $40; (iii) $36? Assume that Intel pays no dividends. b. If the maintenance margin is 25%, how high can Intel’s price rise before you get a margin call?

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c. Redo parts (a) and (b), but now assume that Intel also has paid a year-end dividend of $1 per share. The prices in part (a) should be interpreted as ex-dividend, that is, prices after the dividend has been paid. 11. Call one full-service broker and one discount broker and find out the transaction costs of implementing the following strategies: a. Buying 100 shares of IBM now and selling them six months from now. b. Investing an equivalent amount in six-month at-the-money call options on IBM stock now and selling them six months from now. 12. Here is some price information on Marriott:

Marriott

Bid

Asked

37.25

38.12

You have placed a stop-loss order to sell at $38. What are you telling your broker? Given market prices, will your order be executed? 13. Here is some price information on Fincorp stock. Suppose first that Fincorp trades in a dealer market such as Nasdaq.

15. 16. 17.

Asked

55.25

55.50

a. Suppose you have submitted an order to your broker to buy at market. At what price will your trade be executed? b. Suppose you have submitted an order to sell at market. At what price will your trade be executed? c. Suppose you have submitted a limit order to sell at $55.62. What will happen? d. Suppose you have submitted a limit order to buy at $55.37. What will happen? Now reconsider problem 13 assuming that Fincorp sells in an exchange market like the NYSE. a. Is there any chance for price improvement in the market orders considered in parts (a) and (b)? b. Is there any chance of an immediate trade at $55.37 for the limit buy order in part (d)? What purpose does the SuperDot system serve on the New York Stock Exchange? Who sets the bid and asked price for a stock traded over the counter? Would you expect the spread to be higher on actively or inactively traded stocks? Consider the following data concerning the NYSE: Year

Average Daily Trading Volume (thousands of shares)

Annual High Price of an Exchange Membership

1985 1987 1989 1991 1993 1995 1997

109,169 188,938 165,470 178,917 264,519 346,101 526,925

$ 480,000 1,150,000 675,000 440,000 775,000 1,050,000 1,750,000

a. What do you conclude about the short-run relationship between trading activity and the value of a seat?

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Bid

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b. Based on these data, what do you think has happened to the average commission charged to traders in the last decade? 18. On January 1, you sold short one round lot (that is, 100 shares) of Zenith stock at $14 per share. On March 1, a dividend of $2 per share was paid. On April 1, you covered the short sale by buying the stock at a price of $9 per share. You paid 50 cents per share in commissions for each transaction. What is the value of your account on April 1? The following questions are from past CFA examinations. 19. If you place a stop-loss order to sell 100 shares of stock at $55 when the current price is $62, how much will you receive for each share if the price drops to $50? a. $50. b. $55. c. $54.87. d. Cannot tell from the information given. 20. You wish to sell short 100 shares of XYZ Corporation stock. If the last two transactions were at $34.12 followed by $34.25, you can sell short on the next transaction only at a price of a. 34.12 or higher b. 34.25 or higher c. 34.25 or lower d. 34.12 or lower 21. Specialists on the New York Stock Exchange do all of the following except: a. Act as dealers for their own accounts. b. Execute limit orders. c. Help provide liquidity to the marketplace. d. Act as odd-lot dealers.

WEBMA STER Short Sales Go to the website for Nasdaq at http://www.nasdaq.com. When you enter the site, a dialog box appears that allows you to get quotes for up to 10 stocks. Request quotes for the following companies as identified by their ticker: Noble Drilling (NE), Diamond Offshore (DO), and Haliburton (HAL). Once you have entered the tickers for each company, click the item called info quotes that appears directly below the dialog box for quotes.

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1.

On which market or exchange do these stocks trade? Identify the high and low price based on the current day’s trading.

Below each of the info quotes another dialog box is present. Click the item labeled fundamentals for the first stock. Some basic information on the company will appear along with an additional submenu. One of the items is labeled short interest. When you select that item a 12-month history of short interest will appear. You will need to complete the above process for each of the stocks. 2.

Describe the trend, if any, for short sales over the last year.

3.

What is meant by the term Days to Cover that appears on the history for each company?

4.

Which of the companies has the largest relative number of shares that have been sold short?

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1. Limited time shelf registration was introduced because of its favorable trade-off of saving issue cost against mandated disclosure. Allowing unlimited shelf registration would circumvent “blue sky” laws that ensure proper disclosure as the financial circumstances of the firm change over time.

SOLUTIONS TO

3

2. The advent of negotiated commissions reduced the prices that brokers charged to execute trades on the NYSE. This reduced the profitability of a seat on the exchange, which in turn resulted in the lower seat prices in 1975 that is evident in Table 3.1. Eventually, however, trading volume increased dramatically, which more than made up for lower commissions per trade, and the value of a seat on the exchange rapidly increased after 1975.

> > > >

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AFTER STUDYING THIS CHAPTER YOU SHOULD BE ABLE TO: Cite advantages and disadvantages of investing with an investment company rather than buying securities directly. Contrast open-end mutual funds with closed-end funds and unit investment trusts. Define net asset value and measure the rate of return on a mutual fund. Classify mutual funds according to investment style. Demonstrate the impact of expenses and turnover on mutual fund investment performance.

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Related Websites http://www.brill.com http://www.mfea.com http://www.morningstar.com http://biz.yahoo.com/funds http://moneycentral.msn.com/investor/research/ fundwelcome.asp?Funds=1 http://www.bloomberg.com/money/mutual/index. html The above sites have general and specific information on mutual funds. The Morningstar site has a section dedicated to exchange-traded funds.

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http://www.IndexFunds.com http://www.amex.com http://www.cboe.com/OptiProd/ETFProdSpecs.asp http://www.nyse.com/marketinfo/marketinfo.html These sites give information on exchange-traded funds (ETFs). IndexFunds.com has an excellent screening program that allows you to compare index funds with ETFs in terms of expense ratios.

http://www.vanguard.com http://www100.fidelity.com:80 These sites are examples of specific mutual fund organization websites.

he previous chapter provided an introduction to the mechanics of trading securities and the structure of the markets in which securities trade. Increasingly, however, individual investors are choosing not to trade securities directly for their own accounts. Instead, they direct their funds to investment companies that purchase securities on their behalf. The most important of these financial intermediaries are mutual funds, which are currently owned by about one-half of U.S. households. Other types of investment companies, such as unit investment trusts and closed-end funds, also merit distinctions. We begin the chapter by describing and comparing the various types of investment companies available to investors—unit investment trusts, closed-end investment companies, and open-end investment companies, more commonly known as mutual funds. We devote most of our attention to mutual funds, examining the functions of such funds, their investment styles and policies, and the costs of investing in these funds. Next, we take a first look at the investment performance of these funds. We consider the impact of expenses and turnover on net performance and examine the extent to which performance is consistent from one period to the next. In other words, will the mutual funds that were the best past performers be the best future performers? Finally, we discuss sources of information on mutual funds and consider in detail the information provided in the most comprehensive guide, Morningstar’s Mutual Fund Sourcebook.

T

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4.1

INVESTMENT COMPANIES

Investment companies are financial intermediaries that collect funds from individual investors and invest those funds in a potentially wide range of securities or other assets. Pooling of assets is the key idea behind investment companies. Each investor has a claim to the portfolio established by the investment company in proportion to the amount invested. These companies thus provide a mechanism for small investors to “team up” to obtain the benefits of large-scale investing. Investment companies perform several important functions for their investors:

investment companies Financial intermediaries that invest the funds of individual investors in securities or other assets.

1. Record keeping and administration. Investment companies issue periodic status reports, keeping track of capital gains distributions, dividends, investments, and redemptions, and they may reinvest dividend and interest income for shareholders. 2. Diversification and divisibility. By pooling their money, investment companies enable investors to hold fractional shares of many different securities. They can act as large investors even if any individual shareholder cannot. 3. Professional management. Most, but not all, investment companies have full-time staffs of security analysts and portfolio managers who attempt to achieve superior investment results for their investors. 4. Lower transaction costs. Because they trade large blocks of securities, investment companies can achieve substantial savings on brokerage fees and commissions. While all investment companies pool the assets of individual investors, they also need to divide claims to those assets among those investors. Investors buy shares in investment companies, and ownership is proportional to the number of shares purchased. The value of each share is called the net asset value, or NAV. Net asset value equals assets minus liabilities expressed on a per-share basis:

net asset value (NAV) Assets minus liabilities expressed on a per-share basis.

Net asset value ⫽

Market value of assets minus liabilities Shares outstanding

Consider a mutual fund that manages a portfolio of securities worth $120 million. Suppose the fund owes $4 million to its investment advisers and owes another $1 million for rent, wages due, and miscellaneous expenses. The fund has 5 million shareholders. Then Net asset value ⫽

Concept CHECK

>

$120 million ⫺ $5 million ⫽ $23 per share 5 million shares

1. Consider these data from the December 2000 balance sheet of the Growth Index mutual fund sponsored by the Vanguard Group. (All values are in millions.) What was the net asset value of the portfolio? Assets: Liabilities: Shares:

4.2

$14,754 $ 1,934 419.4

TYPES OF INVESTMENT COMPANIES

In the United States, investment companies are classified by the Investment Company Act of 1940 as either unit investment trusts or managed investment companies. The portfolios of unit investment trusts are essentially fixed and thus are called “unmanaged.” In contrast, managed

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companies are so named because securities in their investment portfolios continually are bought and sold: The portfolios are managed. Managed companies are further classified as either closed-end or open-end. Open-end companies are what we commonly call mutual funds.

Unit Investment Trusts Unit investment trusts are pools of money invested in a portfolio that is fixed for the life of the fund. To form a unit investment trust, a sponsor, typically a brokerage firm, buys a portfolio of securities which are deposited into a trust. It then sells to the public shares, or “units,” in the trust, called redeemable trust certificates. All income and payments of principal from the portfolio are paid out by the fund’s trustees (a bank or trust company) to the shareholders. There is little active management of a unit investment trust because once established, the portfolio composition is fixed; hence these trusts are referred to as unmanaged. Trusts tend to invest in relatively uniform types of assets; for example, one trust may invest in municipal bonds, another in corporate bonds. The uniformity of the portfolio is consistent with the lack of active management. The trusts provide investors a vehicle to purchase a pool of one particular type of asset, which can be included in an overall portfolio as desired. The lack of active management of the portfolio implies that management fees can be lower than those of managed funds. Sponsors of unit investment trusts earn their profit by selling shares in the trust at a premium to the cost of acquiring the underlying assets. For example, a trust that has purchased $5 million of assets may sell 5,000 shares to the public at a price of $1,030 per share, which (assuming the trust has no liabilities) represents a 3% premium over the net asset value of the securities held by the trust. The 3% premium is the trustee’s fee for establishing the trust. Investors who wish to liquidate their holdings of a unit investment trust may sell the shares back to the trustee for net asset value. The trustees can either sell enough securities from the asset portfolio to obtain the cash necessary to pay the investor, or they may instead sell the shares to a new investor (again at a slight premium to net asset value).

unit investment trusts Money pooled from many investors that is invested in a portfolio fixed for the life of the fund.

Managed Investment Companies There are two types of managed companies: closed-end and open-end. In both cases, the fund’s board of directors, which is elected by shareholders, hires a management company to manage the portfolio for an annual fee that typically ranges from .2% to 1.5% of assets. In many cases the management company is the firm that organized the fund. For example, Fidelity Management and Research Corporation sponsors many Fidelity mutual funds and is responsible for managing the portfolios. It assesses a management fee on each Fidelity fund. In other cases, a mutual fund will hire an outside portfolio manager. For example, Vanguard has hired Wellington Management as the investment adviser for its Wellington Fund. Most management companies have contracts to manage several funds. Open-end funds stand ready to redeem or issue shares at their net asset value (although both purchases and redemptions may involve sales charges). When investors in open-end funds wish to “cash out” their shares, they sell them back to the fund at NAV. In contrast, closed-end funds do not redeem or issue shares. Investors in closed-end funds who wish to cash out must sell their shares to other investors. Shares of closed-end funds are traded on organized exchanges and can be purchased through brokers just like other common stock; their prices therefore can differ from NAV. Figure 4.1 is a listing of closed-end funds from The Wall Street Journal. The first column after the name of the fund indicates the exchange on which the shares trade (A: Amex; C: Chicago; N: NYSE; O: Nasdaq; T: Toronto; z: does not trade on an exchange). The next four

open-end funds A fund that issues or redeems its shares at net asset value.

closed-end funds A fund whose shares are traded at prices that can differ from net asset value. Shares may not be redeemed at NAV.

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F I G U R E 4.1 Closed-end mutual funds Source: The Wall Street Journal, November 19, 2001. Reprinted by permission of Dow Jones & Company, Inc., via Copyright Clearance Center, Inc. © 2001 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

columns give the fund’s most recent net asset value, the closing share price, the change in the closing price from the previous day, and trading volume in round lots of 100 shares. The premium or discount is the percentage difference between price and NAV: (Price ⫺ NAV)/NAV. Notice that there are more funds selling at discounts to NAV (indicated by negative differences) than premiums. Finally, the annual dividend and the 52-week return based on the percentage change in share price plus dividend income is presented in the last two columns. The common divergence of price from net asset value, often by wide margins, is a puzzle that has yet to be fully explained. To see why this is a puzzle, consider a closed-end fund that is selling at a discount from net asset value. If the fund were to sell all the assets in the portfolio, it would realize proceeds equal to net asset value. The difference between the market price of the fund and the fund’s NAV would represent the per-share increase in the wealth of the fund’s investors. Despite this apparent profit opportunity, sizable discounts seem to persist for long periods of time. Interestingly, while many closed-end funds sell at a discount from net asset value, the prices of these funds when originally issued are often above NAV. This is a further puzzle, as it is hard to explain why investors would purchase these newly issued funds at a premium to NAV when the shares tend to fall to a discount shortly after issue. Many investors consider closed-end funds selling at a discount to NAV to be a bargain. Even if the market price never rises to the level of NAV, the dividend yield on an investment in the fund at this price would exceed the dividend yield on the same securities held outside the fund. To see this, imagine a fund with an NAV of $10 per share holding a portfolio that pays an annual dividend of $1 per share; that is, the dividend yield to investors that hold this portfolio directly is 10%. Now suppose that the market price of a share of this closed-end fund is $9. If management pays out dividends received from the shares as they come in, then the dividend yield to those that hold the same portfolio through the closed-end fund will be $1/$9, or 11.1%. Variations on closed-end funds are interval closed-end funds and discretionary closed-end funds. Interval closed-end funds may purchase from 5 to 25% of outstanding shares from

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investors at intervals of 3, 6, or 12 months. Discretionary closed-end funds may purchase any or all of outstanding shares from investors, but no more frequently than once every two years. The repurchase of shares for either of these funds takes place at net asset value plus a repurchase fee that may not exceed 2%. In contrast to closed-end funds, the price of open-end funds cannot fall below NAV, because these funds stand ready to redeem shares at NAV. The offering price will exceed NAV, however, if the fund carries a load. A load is, in effect, a sales charge, which is paid to the seller. Load funds are sold by securities brokers and directly by mutual fund groups. Unlike closed-end funds, open-end mutual funds do not trade on organized exchanges. Instead, investors simply buy shares from and liquidate through the investment company at net asset value. Thus, the number of outstanding shares of these funds changes daily.

103

load A sales commission charged on a mutual fund.

Other Investment Organizations There are intermediaries not formally organized or regulated as investment companies that nevertheless serve functions similar to investment companies. Among the more important are commingled funds, real estate investment trusts, and hedge funds.

Commingled funds Commingled funds are partnerships of investors that pool their funds. The management firm that organizes the partnership, for example, a bank or insurance company, manages the funds for a fee. Typical partners in a commingled fund might be trust or retirement accounts which have portfolios that are much larger than those of most individual investors but are still too small to warrant managing on a separate basis. Commingled funds are similar in form to open-end mutual funds. Instead of shares, though, the fund offers units, which are bought and sold at net asset value. A bank or insurance company may offer an array of different commingled funds from which trust or retirement accounts can choose. Examples are a money market fund, a bond fund, and a common stock fund.

Real Estate Investment Trusts (REITs) A REIT is similar to a closed-end fund. REITs invest in real estate or loans secured by real estate. Besides issuing shares, they raise capital by borrowing from banks and issuing bonds or mortgages. Most of them are highly leveraged, with a typical debt ratio of 70%. There are two principal kinds of REITs. Equity trusts invest in real estate directly, whereas mortgage trusts invest primarily in mortgage and construction loans. REITs generally are established by banks, insurance companies, or mortgage companies, which then serve as investment managers to earn a fee. REITs are exempt from taxes as long as at least 95% of their taxable income is distributed to shareholders. For shareholders, however, the dividends are taxable as personal income. Hedge funds Like mutual funds, hedge funds are vehicles that allow private investors to pool assets to be invested by a fund manager. However, hedge funds are not registered as mutual funds and are not subject to SEC regulation. They typically are open only to wealthy or institutional investors. As hedge funds are only lightly regulated, their managers can pursue investment strategies that are not open to mutual fund managers, for example, heavy use of derivatives, short sales, and leverage. Hedge funds typically attempt to exploit temporary misalignments in security valuations. For example, if the yield on mortgage-backed securities seems abnormally high compared to that on Treasury bonds, the hedge fund would buy mortgage-backed and short sell Treasury securities. Notice that the fund is not betting on broad movement in the entire bond market; it

hedge fund A private investment pool, open to wealthy or institutional investors, that is exempt from SEC regulation and can therefore pursue more speculative policies than mutual funds.

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buys one type of bond and sells another. By taking a long mortgage/short Treasury position, the fund “hedges” its interest rate exposure, while making a bet on the relative valuation across the two sectors. The idea is that when yield spreads converge back to their “normal” relationship, the fund will profit from the realignment regardless of the general trend in the level of interest rates. In this respect, it strives to be “market neutral,” which gives rise to the term “hedge fund.” Of course even if the fund’s position is market neutral, this does not mean that it is low risk. The fund still is speculating on valuation differences across the two sectors, often taking a very large position, and this decision can turn out to be right or wrong. Because the funds often operate with considerable leverage, returns can be quite volatile. One of the major financial stories of 1998 was the collapse of Long-Term Capital Management (LTCM), probably the best-known hedge fund at the time. Among its many investments were several “convergence bets,” such as the mortgage-backed/Treasury spread we have described. When Russia defaulted on some of its debts in August 1998, risk and liquidity premiums increased, so that instead of converging, the yield spread between safe Treasuries and almost all other bonds widened. LTCM lost billions of dollars in August and September of 1998; the fear was that given its extreme leverage, continued losses might more than wipe out the firm’s capital and force it to default on its positions. Eventually, several Wall Street firms contributed a total of about $3.5 billion to bail out the fund, in return receiving a 90% ownership stake in the firm.

4.3

MUTUAL FUNDS

Mutual fund is the common name for an open-end investment company. This is the dominant investment company today, accounting for roughly 90% of investment company assets. Assets under management in the mutual fund industry reached $7 trillion by year-end 2001.

Investment Policies Each mutual fund has a specified investment policy, which is described in the fund’s prospectus. For example, money market mutual funds hold the short-term, low-risk instruments of the money market (see Chapter 2 for a review of these securities), while bond funds hold fixed-income securities. Some funds have even more narrowly defined mandates. For example, some bond funds will hold primarily Treasury bonds, others primarily mortgage-backed securities. Management companies manage a family, or “complex,” of mutual funds. They organize an entire collection of funds and then collect a management fee for operating them. By managing a collection of funds under one umbrella, these companies make it easy for investors to allocate assets across market sectors and to switch assets across funds while still benefiting from centralized record keeping. Some of the most well-known management companies are Fidelity, Vanguard, Putnam, and Dreyfus. Each offers an array of open-end mutual funds with different investment policies. There were over 8,000 mutual funds at the end of 2000, which were offered by fewer than 500 fund complexes. Some of the more important fund types, classified by investment policy, are discussed next.

Money market funds These funds invest in money market securities. They usually offer check-writing features, and net asset value is fixed at $1 per share, so that there are no tax implications such as capital gains or losses associated with redemption of shares.

Equity funds Equity funds invest primarily in stock, although they may, at the portfolio manager’s discretion, also hold fixed-income or other types of securities. Funds commonly

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will hold about 5% of total assets in money market securities to provide the liquidity necessary to meet potential redemption of shares. It is traditional to classify stock funds according to their emphasis on capital appreciation versus current income. Thus income funds tend to hold shares of firms with high dividend yields that provide high current income. Growth funds are willing to forgo current income, focusing instead on prospects for capital gains. While the classification of these funds is couched in terms of income versus capital gains, it is worth noting that in practice the more relevant distinction concerns the level of risk these funds assume. Growth stocks—and therefore growth funds—are typically riskier and respond far more dramatically to changes in economic conditions than do income funds.

Bond funds As the name suggests, these funds specialize in the fixed-income sector. Within that sector, however, there is considerable room for specialization. For example, various funds will concentrate on corporate bonds, Treasury bonds, mortgage-backed securities, or municipal (tax-free) bonds. Indeed, some of the municipal bond funds will invest only in bonds of a particular state (or even city!) in order to satisfy the investment desires of residents of that state who wish to avoid local as well as federal taxes on the interest paid on the bonds. Many funds also will specialize by the maturity of the securities, ranging from short-term to intermediate to long-term, or by the credit risk of the issuer, ranging from very safe to highyield or “junk” bonds. Balanced and income funds Some funds are designed to be candidates for an individual’s entire investment portfolio. Therefore, they hold both equities and fixed-income securities in relatively stable proportions. According to Wiesenberger, such funds are classified as income or balanced funds. Income funds strive to maintain safety of principal consistent with “as liberal a current income from investments as possible,” while balanced funds “minimize investment risks so far as this is possible without unduly sacrificing possibilities for long-term growth and current income.”

Asset allocation funds These funds are similar to balanced funds in that they hold both stocks and bonds. However, asset allocation funds may dramatically vary the proportions allocated to each market in accord with the portfolio manager’s forecast of the relative performance of each sector. Hence, these funds are engaged in market timing and are not designed to be low-risk investment vehicles.

Index funds An index fund tries to match the performance of a broad market index. The fund buys shares in securities included in a particular index in proportion to the security’s representation in that index. For example, the Vanguard 500 Index Fund is a mutual fund that replicates the composition of the Standard & Poor’s 500 stock price index. Because the S&P 500 is a value-weighted index, the fund buys shares in each S&P 500 company in proportion to the market value of that company’s outstanding equity. Investment in an index fund is a low-cost way for small investors to pursue a passive investment strategy—that is, to invest without engaging in security analysis. Of course, index funds can be tied to nonequity indexes as well. For example, Vanguard offers a bond index fund and a real estate index fund.

Specialized sector funds Some funds concentrate on a particular industry. For example, Fidelity markets dozens of “select funds,” each of which invests in specific industry such as biotechnology, utilities, precious metals, or telecommunications. Other funds specialize in securities of particular countries. Table 4.1 breaks down the number of mutual funds by investment orientation as of the end of 2001. Figure 4.2 is part of the listings for mutual funds from The Wall Street Journal.

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Assets ($ billion)

% of Total

$ 576.2 1,047.5 1,066.6 125.4 415.1 13.7 173.6

8.3% 15.0 15.3 1.8 6.0 0.2 2.5

Total equity funds Bond Funds Corporate, investment grade Corporate, high yield Government & agency Mortgage-backed Global bond funds Strategic income Municipal single state Municipal general

$3,418.1

49.0%

$ 161.0 94.3 90.9 73.4 19.0 191.6 141.0 154.0

2.3% 1.4 1.3 1.1 0.3 2.7 2.0 2.2

Total bond funds Mixed (hybrid) Asset Classes Balanced Asset allocation & flexible

$ 925.2

13.3%

$ 231.1 115.3

3.3% 1.7

$ 346.3

5.0%

$2,012.9 272.4

28.9% 3.9

$2,285.3

32.8%

$6,974.9

100.0%

TA B L E 4.1 Classification of mutual funds, December 2001

Common Stock Aggressive growth Growth Growth & income Equity income International Emerging markets Sector funds

Total hybrid funds Money Market Taxable Tax-free Total money market funds Total Note: Column sums subject to rounding error. Source: Mutual Fund Fact Book, Investment Company Institute, 2002.

Notice that the funds are organized by the fund family. For example, funds sponsored by the Vanguard Group comprise most of the figure. The first two columns after the name of each fund present the net asset value of the fund and the change in NAV from the previous day. The last column is the year-to-date return on the fund. Often the fund name describes its investment policy. For example, Vanguard’s GNMA fund invests in mortgage-backed securities, the municipal intermediate fund (MuInt) invests in intermediate-term municipal bonds, and the high-yield corporate bond fund (HYCor) invests in large part in speculative grade, or “junk,” bonds with high yields. You can see that Vanguard offers about 20 index funds, including portfolios indexed to the bond market (TotBd), the Wilshire 5000 Index (TotSt), the Russell 2000 Index of small firms (SmCap), as well as European- and Pacific Basin-indexed portfolios (Europe and Pacific). However, names of common stock funds frequently reflect little or nothing about their investment policies. Examples are Vanguard’s Windsor and Wellington funds.

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F I G U R E 4.2 Listing of mutual fund quotations Source: The Wall Street Journal, November 15, 2001. Reprinted by permission of Dow Jones & Company, Inc., via Copyright Clearance Center, Inc. © 2001 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

How Funds Are Sold Most mutual funds have an underwriter that has exclusive rights to distribute shares to investors. Mutual funds are generally marketed to the public either directly by the fund underwriter or indirectly through brokers acting on behalf of the underwriter. Direct-marketed funds are sold through the mail, various offices of the fund, over the phone, and increasingly, over the Internet. Investors contact the fund directly to purchase shares. For example, if you look at the financial pages of your local newspaper, you will see several advertisements for funds, along with toll-free phone numbers that you can call to receive a fund’s prospectus and an application to open an account with the fund. A bit less than half of fund sales today are distributed through a sales force. Brokers or financial advisers receive a commission for selling shares to investors. (Ultimately, the commission is paid by the investor. More on this shortly.) In some cases, funds use a “captive” sales force that sells only shares in funds of the mutual fund group they represent. The trend today, however, is toward “financial supermarkets” that can sell shares in funds of many complexes. This approach was made popular by the OneSource program of Charles Schwab & Co. Schwab allows customers of the OneSource program to buy funds from many different fund groups. Instead of charging customers a sales commission, Schwab splits management fees with the mutual fund company. The supermarket approach has proven to be popular. For example, Fidelity now sells non-Fidelity mutual funds through its FundsNetwork even though many of those funds compete with Fidelity products. Like Schwab, Fidelity shares a portion of the management fee from the non-Fidelity funds it sells.

4.4

COSTS OF INVESTING IN MUTUAL FUNDS

Fee Structure An individual investor choosing a mutual fund should consider not only the fund’s stated investment policy and past performance, but also its management fees and other expenses.

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Comparative data on virtually all important aspects of mutual funds are available in the annual reports prepared by Wiesenberger Investment Companies Services or in Morningstar’s Mutual Fund Sourcebook, which can be found in many academic and public libraries. You should be aware of four general classes of fees.

Front-end load A front-end load is a commission or sales charge paid when you purchase the shares. These charges, which are used primarily to pay the brokers who sell the funds, may not exceed 8.5%, but in practice they are rarely higher than 6%. Low-load funds have loads that range up to 3% of invested funds. No-load funds have no front-end sales charges. Loads effectively reduce the amount of money invested. For example, each $1,000 paid for a fund with an 8.5% load results in a sales charge of $85 and fund investment of only $915. You need cumulative returns of 9.3% of your net investment (85/915 ⫽ .093) just to break even.

Back-end load A back-end load is a redemption, or “exit,” fee incurred when you sell your shares. Typically, funds that impose back-end loads start them at 5% or 6% and reduce them by one percentage point for every year the funds are left invested. Thus, an exit fee that starts at 6% would fall to 4% by the start of your third year. These charges are known more formally as “contingent deferred sales charges.”

Operating expenses

Operating expenses are the costs incurred by the mutual fund in operating the portfolio, including administrative expenses and advisory fees paid to the investment manager. These expenses, usually expressed as a percentage of total assets under management, may range from 0.2% to 2%. Shareholders do not receive an explicit bill for these operating expenses; however, the expenses periodically are deducted from the assets of the fund. Shareholders pay for these expenses through the reduced value of the portfolio.

12b-1 charges The Securities and Exchange Commission allows the managers of so12b-1 fees Annual fees charged by a mutual fund to pay for marketing and distribution costs.

called 12b-1 funds to use fund assets to pay for distribution costs such as advertising, promotional literature including annual reports and prospectuses, and, most important, commissions paid to brokers who sell the fund to investors. These 12b-1 fees are named after the SEC rule that permits use of these plans. Funds may use 12b-1 charges instead of, or in addition to, front-end loads to generate the fees with which to pay brokers. As with operating expenses, investors are not explicitly billed for 12b-1 charges. Instead, the fees are deducted from the assets of the fund. Therefore, 12b-1 fees (if any) must be added to operating expenses to obtain the true annual expense ratio of the fund. The SEC now requires that all funds include in the prospectus a consolidated expense table that summarizes all relevant fees. The 12b-1 fees are limited to 1% of a fund’s average net assets per year.1 A relatively recent innovation in the fee structure of mutual funds is the creation of different “classes”; they represent ownership in the same portfolio of securities but impose different combinations of fees. For example, Class A shares typically are sold with front-end loads of between 4% to 5%. Class B shares impose 12b-1 charges and back-end loads. Because Class B shares pay 12b-1 fees while Class A shares do not, the reported rate of return on the B

1

The maximum 12b-1 charge for the sale of the fund is .75%. However, an additional service fee of .25% of the fund’s assets also is allowed for personal service and/or maintenance of shareholder accounts.

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shares will be less than that of the A shares despite the fact that they represent holdings in the same portfolio. (The reported return on the shares does not reflect the impact of loads paid by the investor.) Class C shares do not impose back-end redemption fees, but they impose 12b-1 fees higher than those in Class B, often as high as 1% annually. Other classes and combinations of fees are also marketed by mutual fund companies. For example, Merrill Lynch has introduced Class D shares of some of its funds, which include front-end loads and 12b-1 charges of .25%. Each investor must choose the best combination of fees. Obviously, pure no-load no-fee funds distributed directly by the mutual fund group are the cheapest alternative, and these will often make the most sense for knowledgeable investors. However, many investors are willing to pay for financial advice, and the commissions paid to advisers who sell these funds are the most common form of payment. Alternatively, investors may choose to hire a fee-only financial manager who charges directly for services and does not accept commissions. These advisers can help investors select portfolios of low- or no-load funds (as well as provide other financial advice). Independent financial planners have become increasingly important distribution channels for funds in recent years. If you do buy a fund through a broker, the choice between paying a load and paying 12b-1 fees will depend primarily on your expected time horizon. Loads are paid only once for each purchase, whereas 12b-1 fees are paid annually. Thus, if you plan to hold your fund for a long time, a one-time load may be preferable to recurring 12b-1 charges. You can identify funds with various charges by the following letters placed after the fund name in the listing of mutual funds in the financial pages: r denotes redemption or exit fees; p denotes 12b-1 fees; and t denotes both redemption and 12b-1 fees. The listings do not allow you to identify funds that involve front-end loads, however; while NAV for each fund is presented, the offering price at which the fund can be purchased, which may include a load, is not.

Fees and Mutual Fund Returns The rate of return on an investment in a mutual fund is measured as the increase or decrease in net asset value plus income distributions such as dividends or distributions of capital gains expressed as a fraction of net asset value at the beginning of the investment period. If we denote the net asset value at the start and end of the period as NAV0 and NAV1, respectively, then Rate of return ⫽

NAV1 ⫺ NAV0 ⫹ Income and capital gain distributions NAV0

For example, if a fund has an initial NAV of $20 at the start of the month, makes income distributions of $.15 and capital gain distributions of $.05, and ends the month with NAV of $20.10, the monthly rate of return is computed as Rate of return ⫽

$20.10 ⫺ $20.00 ⫹ $.15 ⫹ $.05 ⫽ .015, or 1.5% $20.00

Notice that this measure of the rate of return ignores any commissions such as front-end loads paid to purchase the fund. On the other hand, the rate of return is affected by the fund’s expenses and 12b-1 fees. This is because such charges are periodically deducted from the portfolio, which reduces net asset value. Thus the rate of return on the fund equals the gross return on the underlying portfolio minus the total expense ratio.

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Cumulative Proceeds (all dividends reinvested)

TA B L E 4.2 Impact of costs on investment performance

Initial investment* 5 years 10 years 15 years 20 years

Fund A

Fund B

Fund C

$10,000 17,234 29,699 51,183 88,206

$10,000 16,474 27,141 44,713 73,662

$ 9,200 15,502 26,123 44,018 74,173

*

After front-end load, if any.

Notes: 1. Fund A is no-load with .5% expense ratio. 2. Fund B is no-load with 1.5% expense ratio. 3. Fund C has an 8% load on purchases and a 1% expense ratio. 4. Gross return on all funds is 12% per year before expenses.

4.1 EXAMPLE Expenses and Rates of Return

soft dollars The value of research services brokerage houses provide “free of charge” in exchange for the investment manager’s business.

To see how expenses can affect rate of return, consider a fund with $100 million in assets at the start of the year and with 10 million shares outstanding. The fund invests in a portfolio of stocks that provides no income but increases in value by 10%. The expense ratio, including 12b-1 fees, is 1%. What is the rate of return for an investor in the fund? The initial NAV equals $100 million/10 million shares ⫽ $10 per share. In the absence of expenses, fund assets would grow to $110 million and NAV would grow to $11 per share, for a 10% rate of return. However, the expense ratio of the fund is 1%. Therefore, $1 million will be deducted from the fund to pay these fees, leaving the portfolio worth only $109 million, and NAV equal to $10.90. The rate of return on the fund is only 9%, which equals the gross return on the underlying portfolio minus the total expense ratio.

Fees can have a big effect on performance. Table 4.2 considers an investor who starts with $10,000 and can choose between three funds that all earn an annual 12% return on investment before fees but have different fee structures. The table shows the cumulative amount in each fund after several investment horizons. Fund A has total operating expenses of .5%, no load, and no 12b-1 charges. This might represent a low-cost producer like Vanguard. Fund B has no load but has 1% management expenses and .5% in 12b-1 fees. This level of charges is fairly typical of actively managed equity funds. Finally, Fund C has 1% in management expenses, no 12b-1 charges, but assesses an 8% front-end load on purchases. Note the substantial return advantage of low-cost Fund A. Moreover, that differential is greater for longer investment horizons. Although expenses can have a big impact on net investment performance, it is sometimes difficult for the investor in a mutual fund to measure true expenses accurately. This is because of the common practice of paying for some expenses in soft dollars. A portfolio manager earns soft-dollar credits with a stockbroker by directing the fund’s trades to that broker. Based on those credits, the broker will pay for some of the mutual fund’s expenses, such as databases, computer hardware, or stock-quotation systems. The soft-dollar arrangement means that the stockbroker effectively returns part of the trading commission to the fund. The advantage to the mutual fund is that purchases made with soft dollars are not included in the fund’s expenses, so the fund can advertise an unrealistically low expense ratio to the public.

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Although the fund may have paid the broker needlessly high commissions to obtain the softdollar “rebate,” trading costs are not included in the fund’s expenses. The impact of the higher trading commission shows up instead in net investment performance. Soft-dollar arrangements make it difficult for investors to compare fund expenses, and periodically these arrangements come under attack. 2. The Equity Fund sells Class A shares with a front-end load of 4% and Class B shares with 12b-1 fees of .5% annually as well as back-end load fees that start at 5% and fall by 1% for each full year the investor holds the portfolio (until the fifth year). Assume the rate of return on the fund portfolio net of operating expenses is 10% annually. What will be the value of a $10,000 investment in Class A and Class B shares if the shares are sold after (a) 1 year, (b) 4 years, (c) 10 years? Which fee structure provides higher net proceeds at the end of each investment horizon?

4.5

Concept CHECK

TAXATION OF MUTUAL FUND INCOME

Investment returns of mutual funds are granted “pass-through status” under the U.S. tax code, meaning that taxes are paid only by the investor in the mutual fund, not by the fund itself. The income is treated as passed through to the investor as long as the fund meets several requirements, most notably that at least 90% of all income is distributed to shareholders. In addition, the fund must receive less than 30% of its gross income from the sale of securities held for less than three months, and the fund must satisfy some diversification criteria. Actually, the earnings pass-through requirements can be even more stringent than 90%, since to avoid a separate excise tax, a fund must distribute at least 98% of income in the calendar year that it is earned. A fund’s short-term capital gains, long-term capital gains, and dividends are passed through to investors as though the investor earned the income directly. The investor will pay taxes at the appropriate rate depending upon the type of income as well as the investor’s own tax bracket.2 The pass through of investment income has one important disadvantage for individual investors. If you manage your own portfolio, you decide when to realize capital gains and losses on any security; therefore, you can time those realizations to efficiently manage your tax liabilities. When you invest through a mutual fund, however, the timing of the sale of securities from the portfolio is out of your control, which reduces your ability to engage in tax management. Of course, if the mutual fund is held in a tax-deferred retirement account such as an IRA or 401(k) account, these tax management issues are irrelevant. A fund with a high portfolio turnover rate can be particularly “tax inefficient.” Turnover is the ratio of the trading activity of a portfolio to the assets of the portfolio. It measures the fraction of the portfolio that is “replaced” each year. For example, a $100 million portfolio with $50 million in sales of some securities with purchases of other securities would have a turnover rate of 50%. High turnover means that capital gains or losses are being realized constantly, and therefore that the investor cannot time the realizations to manage his or her overall tax obligation.

2

3. An investor’s portfolio currently is worth $1 million. During the year, the investor sells 1,000 shares of Microsoft at a price of $80 per share and 2,000 shares of Ford at a price of $40 per share. The proceeds are used to buy 1,600 shares of IBM at $100 per share. a. What was the portfolio turnover rate? b. If the shares in Microsoft originally were purchased for $70 each and those in Ford were purchased for $35, and if the investor’s tax rate on capital gains income is 20%, how much extra will the investor owe on this year’s taxes as a result of these transactions?

4.6 exchange-traded funds Offshoots of mutual funds that allow investors to trade index portfolios.

EXCHANGE-TRADED FUNDS

Exchange-traded funds (ETFs) are offshoots of mutual funds that allow investors to trade index portfolios just as they do shares of stock. The first ETF was the “Spider,” a nickname for SPDR or Standard & Poor’s Depository Receipt, which is a unit investment trust holding a portfolio matching the S&P 500 index. Unlike mutual funds, which can be bought or sold only at the end of the day when NAV is calculated, investors could trade Spiders throughout the day, just like any other share of stock. Spiders gave rise to many similar products such as “Diamonds” (based on the Dow Jones Industrial Average, ticker DIA), Cubes (based on the Nasdaq 100 Index, ticker QQQ), and WEBS (World Equity Benchmark Shares, which are shares in portfolios of foreign stock market indexes). By 2000, there were dozens of ETFs in three general classes: broad U.S. market indexes, narrow industry or “sector” portfolios, and international indexes, marketed as WEBS. Table 4.3, Panel A, presents some of the sponsors of ETFs; Panel B is a sample of ETFs. ETFs offer several advantages over conventional mutual funds. First, as we just noted, a mutual fund’s net asset value is quoted—and therefore, investors can buy or sell their shares in the fund—only once a day. In contrast, ETFs trade continuously. Moreover, like other shares, but unlike mutual funds, ETFs can be sold short or purchased on margin. ETFs also offer a potential tax advantage over mutual funds. When large numbers of mutual fund investors redeem their shares, the fund must sell securities to meet the redemptions. This can trigger capital gains taxes, which are passed through to and must be paid by the remaining shareholders. In contrast, when small investors wish to redeem their position in an ETF they simply sell their shares to other traders, with no need for the fund to sell any of the underlying portfolio. Moreover, when large traders wish to redeem their position in the ETF, redemptions are satisfied with shares of stock in the underlying portfolio. Again, a redemption does not trigger a stock sale by the fund sponsor. The ability of large investors to redeem ETFs for a portfolio of stocks comprising the index, or to exchange a portfolio of stocks for shares in the corresponding ETF, ensures that the price of an ETF cannot depart significantly from the NAV of that portfolio. Any meaningful discrepancy would offer arbitrage trading opportunities for these large traders, which would quickly eliminate the disparity. ETFs are also cheaper than mutual funds. Investors who buy ETFs do so through brokers, rather than buying directly from the fund. Therefore, the fund saves the cost of marketing

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A. ETF Sponsors

TA B L E 4.3 ETF sponsors and products

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Sponsor

Product Name

Barclays Global Investors Merrill Lynch StateStreet/Merrill Lynch Vanguard

i-Shares HOLDRS (Holding Company Depository Receipts: “Holders”) Select Sector SPDRs (S&P Depository Receipts: “Spiders”) VIPER (Vanguard Index Participation Equity Receipts: “VIPERS”)

B. Sample of ETF Products Name Broad U.S. Indexes Spiders Diamonds Cubes iShares Russell 2000 VIPER Industry Indexes Energy Select Spider iShares Energy Sector Financial Sector Spider iShares Financial Sector International Indexes WEBS United Kingdom WEBS France WEBS Japan

Ticker

Index Tracked

SPY DIA QQQ IWM VTI

S&P 500 Dow Jones Industrials Nasdaq 100 Russell 2000 Wilshire 5000

XLE IYE XLF IYF

S&P 500 energy companies Dow Jones energy companies S&P 500 financial companies Dow Jones financial companies

EWU EWQ EWJ

MCSI U.K. Index MCSI France Index MCSI Japan Index

itself directly to small investors. This reduction in expenses translates into lower management fees. For example, Barclays charges annual expenses of just over 9 basis points (i.e., .09%) of NAV per year on its S&P 500 ETF, whereas Vanguard charges 18 basis points on its S&P 500 index mutual fund. There are some disadvantages to ETFs, however. Because they trade as securities, there is the possibility that their prices can depart by small amounts from NAV. As noted, this discrepancy cannot be too large without giving rise to arbitrage opportunities for large traders, but even small discrepancies can easily swamp the cost advantage of ETFs over mutual funds. Second, while mutual funds can be bought for NAV with no expense from no-load funds, ETFs must be purchased from brokers for a fee. Investors also incur a bid–ask spread when purchasing an ETF. ETFs have to date been a huge success. Most trade on the Amex and currently account for about half of Amex trading volume. So far, ETFs have been limited to index portfolios. A variant on large exchange-traded funds in a “built-to-order” fund, marketed by sponsors to retail investors as folios, e-baskets, or personal funds. The sponsor establishes several model portfolios that investors can purchase as a basket. These baskets may be sector or broader-based portfolios. Alternatively, investors can custom-design their own portfolios. In either case, investors can trade these portfolios with the sponsor just as though it were a personalized mutual fund. The advantage of this arrangement is that, as is true of ETFs, the individual investor is fully in charge of the timing of purchases and sales of securities. In contrast to mutual funds, the investor’s tax liability is unaffected by the redemption activity of other

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investors. (Remember that in the case of mutual funds, redemptions can trigger the realization of capital gains that are passed through to all shareholders.) Of course, investors would similarly control their tax position using a typical brokerage account, but these basket accounts allow one to trade ready-made diversified portfolios. Investors typically pay an annual fee to participate in these plans.

WEBMA STER Exchange Traded Funds Go to William J. Bernstein’s website, http://www.efficientfrontier.com/ef/901/shootout. htm, for a discussion of potential advantages and disadvantages of ETFs versus index mutual funds. After reading the discussion, address the following questions: 1.

What did Mr. Bernstein conclude about tracking error on ETFs compared to index funds?

2.

What four reasons did he give for possibly favoring ETFs over index funds?

3.

What did the author mean by the statement that the ETF is only as good as its underlying index?

4.7

MUTUAL FUND INVESTMENT PERFORMANCE: A FIRST LOOK

We noted earlier that one of the benefits of mutual funds for the individual investor is the ability to delegate management of the portfolio to investment professionals. The investor retains control over the broad features of the overall portfolio through the asset allocation decision: Each individual chooses the percentages of the portfolio to invest in bond funds versus equity funds versus money market funds, and so forth, but can leave the specific security selection decisions within each investment class to the managers of each fund. Shareholders hope that these portfolio managers can achieve better investment performance than they could obtain on their own. What is the investment record of the mutual fund industry? This seemingly straightforward question is deceptively difficult to answer because we need a standard against which to evaluate performance. For example, we clearly would not want to compare the investment performance of an equity fund to the rate of return available in the money market. The vast differences in the risk of these two markets dictate that year-by-year as well as average performance will differ considerably. We would expect to find that equity funds outperform money market funds (on average) as compensation to investors for the extra risk incurred in equity markets. How can we determine whether mutual fund portfolio managers are performing up to par given the level of risk they incur? In other words, what is the proper benchmark against which investment performance ought to be evaluated? Measuring portfolio risk properly and using such measures to choose an appropriate benchmark is an extremely difficult task. We devote all of Parts II and III of the text to issues surrounding the proper measurement of portfolio risk and the trade-off between risk and return. In this chapter, therefore, we will satisfy ourselves with a first look at the question of fund performance by using only very simple performance benchmarks and ignoring the more subtle issues of risk differences across funds. However, we will return to this topic in Chapter 11,

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where we take a closer look at mutual fund performance after adjusting for differences in the exposure of portfolios to various sources of risk. Here, we will use as a benchmark for the performance of equity fund managers the rate of return on the Wilshire 5000 Index. Recall from Chapter 2 that this is a value-weighted index of about 7,000 stocks that trade on the NYSE, Nasdaq, and Amex stock markets. It is the most inclusive index of the performance of U.S. equities. The performance of the Wilshire 5000 is a useful benchmark with which to evaluate professional managers because it corresponds to a simple passive investment strategy: Buy all the shares in the index in proportion to their outstanding market value. Moreover, this is a feasible strategy for even small investors, because the Vanguard Group offers an index fund (its Total Stock Market Portfolio) designed to replicate the performance of the Wilshire 5000 Index. The expense ratio of the fund is extremely small by the standards of other equity funds, only .20% per year. Using the Wilshire 5000 Index as a benchmark, we may pose the problem of evaluating the performance of mutual fund portfolio managers this way: How does the typical performance of actively managed equity mutual funds compare to the performance of a passively managed portfolio that simply replicates the composition of a broad index of the stock market? By using the Wilshire 5000 as a benchmark, we use a well-diversified equity index to evaluate the performance of managers of diversified equity funds. Nevertheless, as noted earlier, this is only an imperfect comparison, as the risk of the Wilshire 5000 portfolio may not be comparable to that of any particular fund. Casual comparisons of the performance of the Wilshire 5000 Index versus that of professionally managed mutual fund portfolios show disappointing results for most fund managers. Figure 4.3 shows the percent of mutual fund managers whose performance was inferior in each year to the Wilshire 5000. In more years than not, the Index has outperformed the median manager. Figure 4.4 shows the cumulative return since 1970 of the Wilshire 5000 compared to the Lipper General Equity Fund Average. The annualized compound return of the Wilshire 5000 was 12.20% versus 11.11% for the average fund. The 1.09% margin is substantial. To some extent, however, this comparison is unfair. Real funds incur expenses that reduce the rate of return of the portfolio, as well as trading costs such as commissions and bid–ask

F I G U R E 4.3

90%

Percent of equity mutual funds outperformed by Wilshire 5000 Index, 1972–2001

80% 70% 60%

Source: The Vanguard Group.

50% 40% 30% 20%

2000

1998

1996

1994

1992

1990

1988

1986

1984

1982

1980

1978

1976

1974

0

1972

10%

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F I G U R E 4.4

50

Growth of $1 invested in Wilshire 5000 Index versus average general equity fund

Compound growth rate (% / year) Wilshire 5000 12.20 Average Fund 11.11

40 Portfolio Value

Source: The Vanguard Group.

30

20

2000

1998

1996

1994

1992

1990

1988

1986

1984

1982

1980

1978

1976

1974

0

1972

10

1970

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spreads that also reduce returns. John Bogle, former chairman of the Vanguard Group, has estimated that operating expenses reduce the return of typical managed portfolios by about 1% and that transaction fees associated with trading reduce returns by an additional .7%. In contrast, the return to the Wilshire index is calculated as though investors can buy or sell the index with reinvested dividends without incurring any expenses. These considerations suggest that a better benchmark for the performance of actively managed funds is the performance of index funds, rather than the performance of the indexes themselves. Vanguard’s Wilshire 5000 fund was established in 1992, and so has a relatively short track record. However, because it is passively managed, its expense ratio is only about 0.20%; moreover because index funds need to engage in very little trading, its turnover rate is about 3% per year, also extremely low. If we reduce the rate of return on the index by about 0.30%, we ought to obtain a good estimate of the rate of return achievable by a low-cost indexed portfolio. This procedure reduces the average margin of superiority of the index strategy over the average mutual fund from 1.09% to 0.79%, still suggesting that over the past two decades, passively managed (indexed) equity funds would have outperformed the typical actively managed fund. This result may seem surprising to you. After all, it would not seem unreasonable to expect that professional money managers should be able to outperform a very simple rule such as “hold an indexed portfolio.” As it turns out, however, there may be good reasons to expect such a result. We will explore them in detail in Chapter 8, where we discuss the efficient market hypothesis. Of course, one might argue that there are good managers and bad managers, and that the good managers can, in fact, consistently outperform the index. To test this notion, we examine whether managers with good performance in one year are likely to repeat that performance in a following year. In other words, is superior performance in any particular year due to luck, and therefore random, or due to skill, and therefore consistent from year to year? To answer this question, Goetzmann and Ibbotson3 examined the performance of a large sample of equity mutual fund portfolios over the 1976–1985 period. Dividing the funds into 3

William N. Goetzmann and Roger G. Ibbotson, “Do Winners Repeat?” Journal of Portfolio Management (Winter 1994), pp. 9–18.

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TA B L E 4.4 Consistency of investment results

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Initial Period Performance A. Goetzmann and Ibbotson study Top half Bottom half B. Malkiel study, 1970s Top half Bottom half C. Malkiel study, 1980s Top half Bottom half

Top Half

Bottom Half

62.0% 36.6%

38.0% 63.4%

65.1% 35.5%

34.9% 64.5%

51.7% 47.5%

48.3% 52.5%

Sources: Panel A: From “Do Winners Repeat?” by William N. Goetzmann and Roger G. Ibbotson, Journal of Portfolio Management, Winter 1994, pp. 9–18. Reprinted by permission of Institutional Investor. Panels B and C: From “Returns from Investing in Equity Mutual Funds 1971–1991,” by Burton G. Malkiel, Journal of Finance 50 (June 1995), pp. 549–572. Reprinted by permission of Blackwell Science, UK.

two groups based on total investment return for different subperiods, they posed the question: “Do funds with investment returns in the top half of the sample in one two-year period continue to perform well in the subsequent two-year period?” Panel A of Table 4.4 presents a summary of their results. The table shows the fraction of “winners” (i.e., top-half performers) in the initial period that turn out to be winners or losers in the following two-year period. If performance were purely random from one period to the next, there would be entries of 50% in each cell of the table, as top- or bottom-half performers would be equally likely to perform in either the top or bottom half of the sample in the following period. On the other hand, if performance were due entirely to skill, with no randomness, we would expect to see entries of 100% on the diagonals and entries of 0% on the off-diagonals: Top-half performers would all remain in the top half while all bottom-half performers similarly would all remain in the bottom half. In fact, the table shows that 62.0% of initial top-half performers fall in the top half of the sample in the following period, while 63.4% of initial bottom-half performers fall in the bottom half in the following period. This evidence is consistent with the notion that at least part of a fund’s performance is a function of skill as opposed to luck, so that relative performance tends to persist from one period to the next.4 On the other hand, this relationship does not seem stable across different sample periods. Malkiel5 uses a larger sample, but a similar methodology (except that he uses one-year instead of two-year investment returns) to examine performance consistency. He finds that while initial-year performance predicts subsequent-year performance in the 1970s (see Table 4.4, Panel B), the pattern of persistence in performance virtually disappears in the 1980s (Panel C). To summarize, the evidence that performance is consistent from one period to the next is suggestive, but it is inconclusive. In the 1970s, top-half funds in one year were twice as likely in the following year to be in the top half rather as the bottom half of funds. In the 1980s, the odds that a top-half fund would fall in the top half in the following year were essentially equivalent to those of a coin flip. Other studies suggest that bad performance is more likely to persist than good performance. This makes some sense: It is easy to identify fund characteristics that will predictably lead to consistently poor investment performance, notably high expense ratios, and high turnover 4

Another possibility is that performance consistency is due to variation in fee structure across funds. We return to this possibility in Chapter 11. 5 Burton G. Malkiel, “Returns from Investing in Equity Mutual Funds 1971–1991,” Journal of Finance 50 (June 1995), pp. 549–72.

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ratios with associated trading costs. It is far harder to identify the secrets of successful stock picking. (If it were easy, we would all be rich!) Thus the consistency we do observe in fund performance may be due in large part to the poor performers. This suggests that the real value of past performance data is to avoid truly poor funds, even if identifying the future top performers is still a daunting task.

Concept CHECK

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4. Suppose you observe the investment performance of 400 portfolio managers and rank them by investment returns during the year. Twenty percent of all managers are truly skilled, and therefore always fall in the top half, but the others fall in the top half purely because of good luck. What fraction of these top-half managers would you expect to be top-half performers next year? Assume skilled managers always are top-half performers.

4.8

INFORMATION ON MUTUAL FUNDS

The first place to find information on a mutual fund is in its prospectus. The Securities and Exchange Commission requires that the prospectus describe the fund’s investment objectives and policies in a concise “Statement of Investment Objectives” as well as in lengthy discussions of investment policies and risks. The fund’s investment adviser and its portfolio manager also are described. The prospectus also presents the costs associated with purchasing shares in the fund in a fee table. Sales charges such as front-end and back-end loads as well as annual operating expenses such as management fees and 12b-1 fees are detailed in the fee table. Despite this useful information, there is widespread agreement that until recently most prospectuses were difficult to read and laden with legalese. In 1999, however, the SEC required firms to prepare more easily understood prospectuses using less jargon, simpler sentences, and more charts. The nearby box contains some illustrative changes from two prospectuses that illustrate the scope of the problem the SEC was attempting to address. Still, even with these improvements, there remains a question as to whether these plain-English prospectuses contain the information an investor should know when selecting a fund. The answer, unfortunately, is that they still do not. The box also contains a discussion of the information one should look for, as well as what tends to be missing, from the usual prospectus. Funds provide information about themselves in two other sources. The Statement of Additional Information, also known as Part B of the prospectus, includes a list of the securities in the portfolio at the end of the fiscal year, audited financial statements, and a list of the directors and officers of the fund. The fund’s annual report, which generally is issued semiannually, also includes portfolio composition and financial statements, as well as a discussion of the factors that influenced fund performance over the last reporting period. With more than 8,000 mutual funds to choose from, it can be difficult to find and select the fund that is best suited for a particular need. Several publications now offer “encyclopedias” of mutual fund information to help in the search process. Two prominent sources are Wiesenberger’s Investment Companies and Morningstar’s Mutual Fund Sourcebook. The Investment Company Institute—the national association of mutual funds, closed-end funds, and unit investment trusts—publishes an annual Directory of Mutual Funds that includes information on fees as well as phone numbers to contact funds. To illustrate the range of information available about funds, we consider Morningstar’s report on Fidelity’s Magellan fund, reproduced in Figure 4.5. Some of Morningstar’s analysis is qualitative. The top box on the left-hand side of the page provides a short description of fund strategy, in particular the types of securities in which the fund manager tends to invest. The bottom box on the left (“Analysis”) is a more detailed discussion of the fund’s income strategy. The short statement of the fund’s investment policy is in the top right-hand corner: Magellan is a “large blend” fund, meaning that it tends to

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F I G U R E 4.5 Morningstar report Source: Morningstar Mutual Funds. © 2002 Morningstar, Inc. All rights reserved. 225 W. Wacker Dr., Chicago, IL . Although data are gathered from reliable sources, Morningstar cannot guarantee completeness and accuracy.

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Shorter, Clearer Mutual-Fund Disclosure May Omit Vital Investment Information Mutual-fund investors will receive shorter and clearer disclosure documents, under new rules adopted by the Securities and Exchange Commission. But despite all the hoopla surrounding the improvements—including a new “profile” prospectus and an easier-to-read full prospectus—there’s still a slew of vital information fund investors don’t get from any disclosure documents, long or short. Of course, more information isn’t necessarily better. As it is, investors rarely read fund disclosure documents, such as the prospectus (which funds must provide to prospective investors), the semiannual reports (provided to all fund investors) or the statement of additional information (made available upon request). Buried in each are a few nuggets of useful data; but for the most part, they’re full of legalese and technical terms. So what should funds be required to disclose that they currently don’t—and won’t have to even under the SEC’s new rules? Here’s a partial list: Tax-adjusted returns: Under the new rules, both the full prospectus and the fund profile must contain a bar chart of annual returns over the past 10 years, and the fund’s best and worst quarterly returns during that period. That’s a huge improvement over not long ago when a fund’s raw returns were sometimes nowhere to be found in the prospectus. But that doesn’t go far enough, according to some investment advisers. Many would like to see funds report returns after taxes—using assumptions about an investor’s tax bracket that would be disclosed in footnotes. The reason: Many funds make big payouts of dividends and capital gains, forcing investors to fork over a big chunk of their gains to the Internal Revenue Service.

What’s in the fund: If you’re about to put your retirement nest egg in a fund, shouldn’t you get to see what’s in it first? The zippy new profile prospectus describes a fund’s investment strategy, as did the old-style prospectus. But neither gives investors a look at what the fund actually owns. To get the fund’s holdings, you have to have its latest semiannual or annual report. Most people don’t get those documents until after they invest, and even then it can be as much as six months old. Many investment advisers think funds should begin reporting their holdings monthly, but so far funds have resisted doing so. A manager’s stake in a fund: Funds should be required to tell investors whether the fund manager owns any of its shares so investors can see just how confident a manager is in his or her own ability to pick stocks, some investment advisers say. As it stands now, many fund groups don’t even disclose the names and backgrounds of the men and women calling the shots, and instead report that their funds are managed by a “team” of individuals whose identities they don’t disclose. A breakdown of fees: Investors will see in the profile prospectus a clearer outline of the expenses incurred by the fund company that manages the portfolio. But there’s no way to tell whether you are picking up the tab for another guy’s lunch. The problem is, some no-load funds impose a socalled 12b-1 marketing fee on all shareholders. But they use the money gathered from the fee to cover the cost of participating in mutual-fund supermarket distribution programs. Only some fund shareholders buy the fund shares through these programs, but all shareholders bear the expense—including those who purchased shares directly from the fund.

invest in large firms, and not to specialize in either value versus growth stocks—it holds a blend of these. The table on the left labeled “Performance” reports on the fund’s returns over the last few years and over longer periods up to 15 years. Comparisons of returns to relevant indexes, in this case, the S&P 500 and the Wilshire top 750 indexes, are provided to serve as benchmarks in evaluating the performance of the fund. The values under these columns give the performance of the fund relative to the index. For example, Magellan’s return was 1.87% below the S&P 500 over the last three months, but 0.55% per year above the S&P over the past 5 years. The returns reported for the fund are calculated net of expenses, 12b-1 fees, and any other fees automatically deducted from fund assets, but they do not account for any sales charges such as front-end loads or back-end charges. Next appear the percentile ranks of the fund compared to all other funds (see column headed by All) and to all funds with the same investment objective (see column headed by Cat). A rank of 1 means the fund is a top performer. A rank of 80 would mean that it was beaten by 80% of funds in the comparison group. You can see 120

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Nice, Light Read: the Prospectus Old Language Dreyfus The Transfer Agent has adopted example standards and procedures pursuant to which signature-guarantees in proper form generally will be accepted from domestic banks, brokers, dealers, credit unions, national securities exchanges, registered securities associations, clearing agencies and savings associations, as well as from participants in the New York Stock Exchange Medallion Signature Program, the Securities Transfer Agents Medallion Program (“STAMP”) and the Stock Exchange Medallion Program. T. Rowe Price example

Total Return. The Fund may advertise total return figures on both a cumulative and compound average annual basis. Cumulative total return compares the amount invested at the beginning of a period with the amount redeemed at the end of the period, assuming the reinvestment of all dividends and capital gain distributions. The compound average annual total return, derived from the cumulative total return figure, indicates a yearly average of the Fund’s performance. The annual compound rate of return for the Fund may vary from any average.

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Plain English A signature guarantee helps protect against fraud. You can obtain one from most banks or securities dealers, but not from a notary public.

Total Return. This tells you how much an investment in a fund has changed in value over a given time period. It reflects any net increase or decrease in the share price and assumes that all dividends and capital gains (if any) paid during the period were reinvested in additional shares. Therefore, total return numbers include the effect of compounding. Advertisements for a fund may include cumulative or average annual total return figures, which may be compared with various indices, other performance measures, or other mutual funds.

Sources: Adapted from Vanessa O’Connell, “Shorter, Clearer, Mutual-Fund Disclosure May Omit Vital Investment Information,” The Wall Street Journal, March 12, 1999. Reprinted by permission of Dow Jones & Company, Inc., via Copyright Clearance Center, Inc. © 1999 Dow Jones & Company, Inc. All Rights Reserved Worldwide. “A Little Light Reading? Try a Fund Prospectus,” The Wall Street Journal, May 3, 1999. p. R1. Reprinted by permission of Dow Jones & Company, Inc., via Copyright Clearance Center, Inc. © 1999 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

from the table that Magellan has had below-par recent (three month to three year) performance compared to other growth and income funds, but excellent longer-term performance. For example, over the past 15 years, its average return was higher than all but 13% of the funds in its category. Finally, growth of $10,000 invested in the fund over various periods ranging from the past three months to the past 15 years is given in the last column. More data on the performance of the fund are provided in the graph at the top right of the figure. The bar charts give the fund’s rate of return for each quarter of the last 10 years. Below the graph is a box for each year that depicts the relative performance of the fund for that year. The shaded area on the box shows the quartile in which the fund’s performance falls relative to other funds with the same objective. If the shaded band is at the top of the box, the firm was a top quartile performer in that period, and so on. 121

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The table below the bar charts presents historical data on characteristics of the fund. These data include return, return relative to appropriate benchmark indexes such as the S&P 500, the component of returns due to income (dividends) or capital gains, the percentile rank of the fund compared to all funds and funds in its objective class (where, again, 1% is the best performer and 99% would mean that the fund was outperformed by 99% of its comparison group), the expense ratio, and the turnover rate of the portfolio. The table on the right entitled Portfolio Analysis presents the 25 largest holdings of the portfolio, showing the price–earnings ratio and year-to-date return of each of those securities. Investors can thus get a quick look at the manager’s biggest bets. Below the portfolio analysis table is a box labeled Current Investment Style. In this box, Morningstar evaluates style along two dimensions: One dimension is the size of the firms held in the portfolio as measured by the market value of outstanding equity; the other dimension is a value/growth continuum. Morningstar defines value stocks as those with low ratios of market price per share to various measures of value. It puts stocks on a growth-value continuum based on the ratios of stock price to the firm’s earnings, book value, sales, cash flow, and dividends. Value stocks are those with a low price relative to these measures of value. In contrast, growth stocks have high ratios, suggesting that investors in these firms must believe that the firm will experience rapid growth to justify the prices at which the stocks sell. The shaded box for Magellan shows that the portfolio tends to hold larger firms (top row) and blend stocks (middle column). A year-by-year history of Magellan’s investment style is presented in the sequence of such boxes at the top of the figure. The center of the figure, labeled Risk Analysis, is one of the more complicated but interesting facets of Morningstar’s analysis. The column labeled Load-Adj Return rates a fund’s return compared to other funds with the same investment policy. Returns for periods ranging from 1 to 10 years are calculated with all loads and back-end fees applicable to that investment period subtracted from total income. The return is then divided by the average return for the comparison group of funds to obtain the Morningstar Return; therefore, a value of 1.0 in the Return column would indicate average performance while a value of 1.10 would indicate returns 10% above the average for the comparison group (e.g., 11% return for the fund versus 10% for the comparison group). The risk measure indicates the portfolio’s exposure to poor performance, that is, the “downside risk” of the fund. Morningstar bases its risk measure in part on the overall volatility of returns. However, it focuses more intently on episodes of underperformance relative to Treasury bills. The total underperformance compared to T-bills in those months with poor portfolio performance divided by total months sampled is part of the measure of downside risk. The risk measure also is scaled by dividing by the average risk measure for all firms with the same investment objective. Therefore, the average value in the Risk column is 1.0. The two columns to the left of the Morningstar Risk and Return columns are the percentile scores of risk and return for each fund. The risk-adjusted rating, ranging from one to five stars, is based on the Morningstar return score minus the risk score. The stars each fund earns are based on risk-adjusted performance relative to other funds in the same style group. To allow funds to be compared to other funds with similar investment styles, Morningstar recently increased the number of categories; there are now 18 separate stock fund groups and 20 fixed income categories. The tax analysis box on the left provides some evidence on the tax efficiency of the fund by comparing pretax and after-tax returns. The after-tax return, given in the first column, is computed based on the dividends paid to the portfolio as well as realized capital gains, assuming the investor is in the maximum tax bracket at the time of the distribution. State and local taxes are ignored. The “tax efficiency” of the fund is defined as the ratio of after-tax to pretax returns; it is presented in the second column, labeled % Pretax Return. Tax efficiency will be lower when turnover is higher because capital gains are taxed as they are realized.

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The bottom of the page provides information on the expenses and loads associated with investments in the fund, as well as information on the fund’s investment adviser. Thus, Morningstar provides a considerable amount of the information you would need to decide among several competing funds.

closed-end fund, 101 exchange-traded funds, 112 hedge fund, 103

investment company, 100 load, 103 net asset value (NAV), 100 open-end fund, 101

soft dollars, 110 12b-1 fees, 108 turnover, 111 unit investment trust, 101

SUMMARY

KEY TERMS

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• Unit investment trusts, closed-end management companies, and open-end management companies are all classified and regulated as investment companies. Unit investment trusts are essentially unmanaged in the sense that the portfolio, once established, is fixed. Managed investment companies, in contrast, may change the composition of the portfolio as deemed fit by the portfolio manager. Closed-end funds are traded like other securities; they do not redeem shares for their investors. Open-end funds will redeem shares for net asset value at the request of the investor. • Net asset value equals the market value of assets held by a fund minus the liabilities of the fund divided by the shares outstanding. • Mutual funds free the individual from many of the administrative burdens of owning individual securities and offer professional management of the portfolio. They also offer advantages that are available only to large-scale investors, such as lower trading costs. On the other hand, funds are assessed management fees and incur other expenses, which reduce the investor’s rate of return. Funds also eliminate some of the individual’s control over the timing of capital gains realizations. • Mutual funds often are categorized by investment policy. Major policy groups include money market funds; equity funds, which are further grouped according to emphasis on income versus growth; fixed-income funds; balanced and income funds; asset allocation funds; index funds; and specialized sector funds. • Costs of investing in mutual funds include front-end loads, which are sales charges; backend loads, which are redemption fees or, more formally, contingent-deferred sales charges; fund operating expenses; and 12b-1 charges, which are recurring fees used to pay for the expenses of marketing the fund to the public. • Income earned on mutual fund portfolios is not taxed at the level of the fund. Instead, as long as the fund meets certain requirements for pass-through status, the income is treated as being earned by the investors in the fund. • The average rate of return of the average equity mutual fund in the last 25 years has been below that of a passive index fund holding a portfolio to replicate a broad-based index like the S&P 500 or Wilshire 5000. Some of the reasons for this disappointing record are the costs incurred by actively managed funds, such as the expense of conducting the research to guide stock-picking activities, and trading costs due to higher portfolio turnover. The record on the consistency of fund performance is mixed. In some sample periods, the better-performing funds continue to perform well in the following periods; in other sample periods they do not.

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1. Would you expect a typical open-end fixed-income mutual fund to have higher or lower operating expenses than a fixed-income unit investment trust? Why? 2. An open-end fund has a net asset value of $10.70 per share. It is sold with a front-end load of 6%. What is the offering price? 3. If the offering price of an open-end fund is $12.30 per share and the fund is sold with a front-end load of 5%, what is its net asset value? 4. The composition of the Fingroup Fund portfolio is as follows: Stock

Shares

Price

A B C D

200,000 300,000 400,000 600,000

$35 40 20 25

The fund has not borrowed any funds, but its accrued management fee with the portfolio manager currently totals $30,000. There are 4 million shares outstanding. What is the net asset value of the fund? 5. Reconsider the Fingroup Fund in the previous problem. If during the year the portfolio manager sells all of the holdings of stock D and replaces it with 200,000 shares of stock E at $50 per share and 200,000 shares of stock F at $25 per share, what is the portfolio turnover rate? 6. The Closed Fund is a closed-end investment company with a portfolio currently worth $200 million. It has liabilities of $3 million and 5 million shares outstanding. a. What is the NAV of the fund? b. If the fund sells for $36 per share, what is its premium or discount as a percent of NAV? 7. Corporate Fund started the year with a net asset value of $12.50. By year-end, its NAV equaled $12.10. The fund paid year-end distributions of income and capital gains of $1.50. What was the rate of return to an investor in the fund? 8. A closed-end fund starts the year with a net asset value of $12.00. By year-end, NAV equals $12.10. At the beginning of the year, the fund is selling at a 2% premium to NAV. By the end of the year, the fund is selling at a 7% discount to NAV. The fund paid year-end distributions of income and capital gains of $1.50. a. What is the rate of return to an investor in the fund during the year? b. What would have been the rate of return to an investor who held the same securities as the fund manager during the year? 9. What are some comparative advantages of investing your assets in the following: a. Unit investment trusts. b. Open-end mutual funds. c. Individual stocks and bonds that you choose for yourself. 10. Open-end equity mutual funds find it necessary to keep a significant percentage of total investments, typically around 5% of the portfolio, in very liquid money market assets. Closed-end funds do not have to maintain such a position in “cash-equivalent” securities. What difference between open-end and closed-end funds might account for their differing policies? 11. Balanced funds and asset allocation funds invest in both the stock and bond markets. What is the difference between these types of funds?

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12. a. Impressive Fund had excellent investment performance last year, with portfolio returns that placed it in the top 10% of all funds with the same investment policy. Do you expect it to be a top performer next year? Why or why not? b. Suppose instead that the fund was among the poorest performers in its comparison group. Would you be more or less likely to believe its relative performance will persist into the following year? Why? 13. Consider a mutual fund with $200 million in assets at the start of the year and with 10 million shares outstanding. The fund invests in a portfolio of stocks that provides dividend income at the end of the year of $2 million. The stocks included in the fund’s portfolio increase in price by 8%, but no securities are sold, and there are no capital gains distributions. The fund charges 12b-1 fees of 1%, which are deducted from portfolio assets at year-end. What is net asset value at the start and end of the year? What is the rate of return for an investor in the fund? 14. The New Fund had average daily assets of $2.2 billion in the past year. The fund sold $400 million and purchased $500 million worth of stock during the year. What was its turnover ratio? 15. If New Fund’s expense ratio was 1.1% and the management fee was .7%, what were the total fees paid to the fund’s investment managers during the year? What were the other administrative expenses? 16. You purchased 1,000 shares of the New Fund at a price of $20 per share at the beginning of the year. You paid a front-end load of 4%. The securities in which the fund invests increase in value by 12% during the year. The fund’s expense ratio is 1.2%. What is your rate of return on the fund if you sell your shares at the end of the year? 17. The Investments Fund sells Class A shares with a front-end load of 6% and Class B shares with 12b-1 fees of .5% annually as well as back-end load fees that start at 5% and fall by 1% for each full year the investor holds the portfolio (until the fifth year). Assume the portfolio rate of return net of operating expenses is 10% annually. If you plan to sell the fund after four years, are Class A or Class B shares the better choice for you? What if you plan to sell after 15 years? 18. Suppose you observe the investment performance of 350 portfolio managers for five years, and rank them by investment returns during each year. After five years, you find that 11 of the funds have investment returns that place the fund in the top half of the sample in each and every year of your sample. Such consistency of performance indicates to you that these must be the funds whose managers are in fact skilled, and you invest your money in these funds. Is your conclusion warranted? 19. You are considering an investment in a mutual fund with a 4% load and an expense ratio of .5%. You can invest instead in a bank CD paying 6% interest. a. If you plan to invest for two years, what annual rate of return must the fund portfolio earn for you to be better off in the fund than in the CD? Assume annual compounding of returns. b. How does your answer change if you plan to invest for six years? Why does your answer change? c. Now suppose that instead of a front-end load the fund assesses a 12b-1 fee of .75% per year. What annual rate of return must the fund portfolio earn for you to be better off in the fund than in the CD? Does your answer in this case depend on your time horizon? 20. Suppose that every time a fund manager trades stock, transaction costs such as commissions and bid–ask spreads amount to .4% of the value of the trade. If the portfolio turnover rate is 50%, by how much is the total return of the portfolio reduced by trading costs?

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21. You expect a tax-free municipal bond portfolio to provide a rate of return of 4%. Management fees of the fund are .6%. What fraction of portfolio income is given up to fees? If the management fees for an equity fund also are .6%, but you expect a portfolio return of 12%, what fraction of portfolio income is given up to fees? Why might management fees be a bigger factor in your investment decision for bond funds than for stock funds? Can your conclusion help explain why unmanaged unit investment trusts tend to focus on the fixed-income market?

WEBMA STER Mutual Fund Report Go to http://morningstar.com. From the home page select the Funds tab. From this location you can request information on an individual fund. In the dialog box enter the ticker JANSX, for the Janus Fund, and enter Go. This contains the report information on the fund. On the left-hand side of the screen are tabs that allow you to view the various components of the report. Using the components specified, answer the following questions on the Janus Fund:

SOLUTIONS TO

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1.

Morningstar analysis: What is the Morningstar rating? What has been the fund’s year-to-date return?

2.

Total returns: What are the 5- and 10-year returns and how do they compare with the return of the S&P?

3.

Ratings and risk: What is the beta of the fund? What are the mean and standard deviation of returns? What is the 10-year rating on the fund?

4.

Portfolio: What two sectors’ weightings are the largest? What percent of the portfolio assets are in cash?

5.

Nuts and bolts: What is the fund’s total expense ratio? Who is the current manager of the fund and what was his/her start date? How long has the fund been in operation?

1. NAV ⫽ ($14,754 ⫺ $1,934)/419.4 ⫽ $30.57 2. The net investment in the Class A shares after the 4% commission is $9,600. If the fund earns a 10% return, the investment will grow after n years to $9,600 ⫻ (1.10)n. The Class B shares have no front-end load. However, the net return to the investor after 12b-1 fees will be only 9.5%. In addition, there is a back-end load that reduces the sales proceeds by a percentage equal to (5 ⫺ years until sale) until the fifth year, when the back-end load expires. Class A Shares

Class B Shares

Horizon

$9,600 ⴛ (1.10)

1 year 4 years 10 years

$10,560.00 14,055.36 $24,899.93

n

$10,000 ⴛ (1.095)n ⴛ (1 ⴚ percentage exit fee) $10,000 ⫻ (1.095) ⫻ (1 ⫺ .04) $10,000 ⫻ (1.095)4 ⫻ (1 ⫺ .01) $10,000 ⫻ (1.095)10

⫽ $10,512.00 ⫽ $14,232.89 ⫽ $24,782.28

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For a very short horizon such as one year, the Class A shares are the better choice. The front-end and back-end loads are equal, but the Class A shares don’t have to pay the 12b-1 fees. For moderate horizons such as four years, the Class B shares dominate because the front-end load of the Class A shares is more costly than the 12b-1 fees and the now smaller exit fee. For long horizons of 10 years or more, Class A again dominates. In this case, the one-time front-end load is less expensive than the continuing 12b-1 fees. 3. a. Turnover ⫽ $160,000 in trades per $1 million of portfolio value ⫽ 16%. b. Realized capital gains are $10 ⫻ 1,000 ⫽ $10,000 on Microsoft and $5 ⫻ 2,000 ⫽ $10,000 on Ford. The tax owed on the capital gains is therefore .20 ⫻ $20,000 ⫽ $4,000.

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4. Twenty percent of the managers are skilled, which accounts for .2 ⫻ 400 ⫽ 80 of those managers who appear in the top half. There are 120 slots left in the top half, and 320 other managers, so the probability of an unskilled manager “lucking into” the top half in any year is 120/320, or .375. Therefore, of the 120 lucky managers in the first year, we would expect .375 ⫻ 120 ⫽ 45 to repeat as top-half performers next year. Thus, we should expect a total of 80 ⫹ 45 ⫽ 125, or 62.5%, of the better initial performers to repeat their top-half performance.

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Introduction

PA RT

TWO

PORTFOLIO THEORY

uppose you believe that investments in stocks offer an expected rate of return of 10% while the expected rate of return on bonds is only 6%. Would you invest all of your money in stocks? Probably not: putting all of your eggs in one basket in such a manner would violate even the most basic notion of diversification. But what is the optimal combination of these two asset classes? And how will the opportunity to invest in other asset classes—for example, real estate, foreign stocks, precious metals, and so on—affect your decision? In short, is there a “best” solution to your asset allocation problem? These questions are the focus of the first chapters of Part II, which address what has come to be known as Modern Portfolio Theory, or MPT. In large part, MPT addresses the question of “efficient diversification,” how to achieve the best trade-off between portfolio risk and reward.

S

>

This analysis quickly leads to other questions. For example, how should one measure the risk of an individual asset held as part of a diversified portfolio? You will probably be surprised at the answer. Once we have an acceptable measure of risk, what precisely should be the relation between risk and return? And what is the minimally acceptable rate of return for an investment to be considered attractive? These questions also are addressed in this Part of the text. Finally, we come to one of the most controversial topics in investment management, the question of whether portfolio managers— amateur or professional—can outperform simple investment strategies such as “buy a market index fund.” The evidence will at least make you pause before pursuing active strategies. You will come to appreciate how good active managers must be to outperform their passive counterparts.

5

Risk and Return: Past and Prologue

6

Efficient Diversification

7

Capital Asset Pricing and Arbitrage Pricing Theory

8

The Efficient Market Hypothesis

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5 RISK AND RETURN: PAST AND PROLOGUE

AFTER STUDYING THIS CHAPTER YOU SHOULD BE ABLE TO:

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Use data on the past performance of stocks and bonds to characterize the risk and return features of these investments.

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Determine the expected return and risk of portfolios that are constructed by combining risky assets with risk-free investments in Treasury bills.

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Evaluate the performance of a passive strategy.

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Related Websites http://www.bloomberg.com/markets/wei.html http://app.marketwatch.com/intl/default.asp http://www.quote.com/quotecom/markets/ snapshot.asp These websites list returns on various equity indexes.

http://www.standardandpoors.com This site gives detailed analysis on index returns. Analysis of historical returns and comparisons to other indexes are available. The site also reports on changes to the index.

http://www.indexfunds.com/data/ IndexScreener.php This site contains information on virtually all available indexes. It also has a screening program that allows you to rank indexes by various return measures.

http://online.wsj.com/home/us http://www.smartmoney.com/bonds http://www.bloomberg.com/markets/rates.html These sites report current rates on U.S. and international government bonds.

http://www.bondmarkets.com http://www.investinginbonds.com These two sites are pages from the bond market association. General information on a variety of bonds and strategies can be accessed online at no charge. Current information on rates is also available at investinginbonds.com.

http://www.stls.frb.org This site contains current and historical information on a variety of interest rates. Historical data can be downloaded in spreadsheet format, which is available through the Federal Reserve Economic Database (FRED).

hat constitutes a satisfactory investment portfolio? Until the early 1970s, a reasonable answer would have been a bank savings account (a risk-free asset) plus a risky portfolio of U.S. stocks. Nowadays, investors have access to a vastly wider array of assets and may contemplate complex portfolio strategies that may include foreign stocks and bonds, real estate, precious metals, and collectibles. Even more complex strategies may include futures and options to insure portfolios against unacceptable losses. How might such portfolios be constructed? Clearly every individual security must be judged on its contributions to both the expected return and the risk of the entire portfolio. These contributions must be evaluated in the context of the expected performance of the overall portfolio. To guide us in forming reasonable expectations for portfolio performance, we will start this chapter with an examination of various conventions for measuring and reporting rates of return. Given these measures, we turn to the historical performance of several broadly diversified investment portfolios. In doing so, we use a risk-free portfolio of Treasury bills as a benchmark to evaluate the historical performance of diversified stock and bond portfolios. We then proceed to consider the trade-offs investors face when they practice the simplest form of risk control: choosing the fraction of the portfolio invested in virtually risk-free money market securities versus risky securities such as stocks. We show how to calculate the performance one may reasonably expect from various allocations between a risk-free asset and a risky portfolio and discuss the considerations that determine the mix that would best suit different investors. With this background, we can evaluate a passive strategy that will serve as a benchmark for the active strategies considered in the next chapter.

W

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5.1 holding-period return Rate of return over a given investment period.

RATES OF RETURN

A key measure of investors’ success is the rate at which their funds have grown during the investment period. The total holding-period return (HPR) of a share of stock depends on the increase (or decrease) in the price of the share over the investment period as well as on any dividend income the share has provided. The rate of return is defined as dollars earned over the investment period (price appreciation as well as dividends) per dollar invested HPR

Ending price Beginning price Cash dividend Beginning price

This definition of the HPR assumes that the dividend is paid at the end of the holding period. To the extent that dividends are received earlier, the definition ignores reinvestment income between the receipt of the dividend and the end of the holding period. Recall also that the percentage return from dividends is called the dividend yield, and so the dividend yield plus the capital gains yield equals the HPR. This definition of holding return is easy to modify for other types of investments. For example, the HPR on a bond would be calculated using the same formula, except that the bond’s interest or coupon payments would take the place of the stock’s dividend payments.

5.1 EXAMPLE Holding-Period Return

Suppose you are considering investing some of your money, now all invested in a bank account, in a stock market index fund. The price of a share in the fund is currently $100, and your time horizon is one year. You expect the cash dividend during the year to be $4, so your expected dividend yield is 4%. Your HPR will depend on the price one year from now. Suppose your best guess is that it will be $110 per share. Then your capital gain will be $10, so your capital gains yield is $10/$100 .10, or 10%. The total holding period rate of return is the sum of the dividend yield plus the capital gain yield, 4% 10% 14%. HPR

$110 $100 $4 $100

.14, or 14%

Measuring Investment Returns over Multiple Periods The holding period return is a simple and unambiguous measure of investment return over a single period. But often you will be interested in average returns over longer periods of time. For example, you might want to measure how well a mutual fund has performed over the preceding five-year period. In this case, return measurement is more ambiguous. Consider, for example, a fund that starts with $1 million under management at the beginning of the year. The fund receives additional funds to invest from new and existing shareholders, and also receives requests for redemptions from existing shareholders. Its net cash inflow can be positive or negative. Suppose its quarterly results are as given in Table 5.1 with negative numbers reported in parentheses. The story behind these numbers is that when the firm does well (i.e., reports a good HPR), it attracts new funds; otherwise it may suffer a net outflow. For example, the 10% return in the first quarter by itself increased assets under management by 0.10 $1 million $100,000; it also elicited new investments of $100,000, thus bringing assets under management to $1.2 million by the end of the quarter. An even better HPR in the second quarter elicited a larger net inflow, and the second quarter ended with $2 million under management. However, HPR in the third quarter was negative, and net inflows were negative.

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TA B L E 5.1 Quarterly cash flows and rates of return of a mutual fund

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Assets under management at start of quarter ($ million) Holding-period return (%) Total assets before net inflows Net inflow ($ million)* Assets under management at end of quarter ($ million)

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1st Quarter

2nd Quarter

3rd Quarter

4th Quarter

1.0

1.2

2.0

0.8

10.0 1.1 0.1 1.2

25.0 1.5 0.5 2.0

(20.0) 1.6 (0.8) 0.8

25.0 1.0 0.0 1.0

*

New investment less redemptions and distributions, all assumed to occur at the end of each quarter.

How would we characterize fund performance over the year, given that the fund experienced both cash inflows and outflows? There are several candidate measures of performance, each with its own advantages and shortcomings. These are the arithmetic average, the geometric average, and the dollar-weighted return. These measures may vary considerably, so it is important to understand their differences.

Arithmetic average The arithmetic average of the quarterly returns is just the sum of

the quarterly returns divided by the number of quarters; in the above example: (10 25 20 25)/4 10%. Since this statistic ignores compounding, it does not represent an equivalent, single quarterly rate for the year. The arithmetic average is useful, though, because it is the best forecast of performance in future quarters, using this particular sample of historic returns. (Whether the sample is large enough or representative enough to make accurate forecasts is, of course, another question.)

Geometric average The geometric average of the quarterly returns is equal to the single per-period return that would give the same cumulative performance as the sequence of actual returns. We calculate the geometric average by compounding the actual period-by-period returns and then finding the equivalent single per-period return. In this case, the geometric average quarterly return, rG, is defined by: (1 0.10) (1 0.25) (1 0.20) (1 0.25) (1 rG)4 so that rG [(1 0.10) (1 0.25) (1 0.20) (1 0.25)]1/4 1 .0829, or 8.29% The geometric return also is called a time-weighted average return because it ignores the quarter-to-quarter variation in funds under management. In fact, an investor will obtain a larger cumulative return if high returns are earned in those periods when additional sums have been invested, while the lower returns are realized when less money is at risk. Here, the highest returns (25%) were achieved in quarters 2 and 4, when the fund managed $1,200,000 and $800,000, respectively. The worst returns (20% and 10%) occurred when the fund managed $2,000,000 and $1,000,000, respectively. In this case, better returns were earned when less money was under management—an unfavorable combination. The appeal of the time-weighted return is that in some cases we wish to ignore variation in money under management. For example, published data on past returns earned by mutual funds actually are required to be time-weighted returns. The rationale for this practice is that since the fund manager does not have full control over the amount of assets under management, we should not weight returns in one period more heavily than those in other periods when assessing “typical” past performance.

arithmetic average The sum of returns in each period divided by the number of periods.

geometric average The single per-period return that gives the same cumulative performance as the sequence of actual returns.

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Dollar-weighted return When we wish to account for the varying amounts under management, we treat the fund cash flows to investors as we would a capital budgeting problem in corporate finance. The initial value of $1 million and the net cash inflows are treated as the cash flows associated with an investment “project.” The final “liquidation value” of the project is the ending value of the portfolio. In this case, therefore, investor net cash flows are as follows: Time

Net cash flow ($ million)

dollar-weighted average return The internal rate of return on an investment.

0

1

2

3

4

1.0

0.1

0.5

0.8

1.0

The entry for time 0 reflects the starting contribution of $1 million, while the entries for times 1, 2, and 3 represent net inflows at the end of the first three quarters. Finally, the entry for time 4 represents the value of the portfolio at the end of the fourth quarter. This is the value for which the portfolio could have been liquidated by year-end based on the initial investment and net additional investments earlier in the year. The dollar-weighted average return is the internal rate of return (IRR) of the project, which is 4.17%. The IRR is the interest rate that sets the present value of the cash flows realized on the portfolio (including the $1 million for which the portfolio can be liquidated at the end of the year) equal to the initial cost of establishing the portfolio. It therefore is the interest rate that satisfies the following equation: 0.8 1.0 0.1 0.5 1.0 3 (1 IRR) (1 IRR)4 1 IRR (1 IRR)2 The dollar-weighted return in this example is less than the time-weighted return of 8.29% because, as we noted, the portfolio returns were higher when less money was under management. The difference between the dollar- and time-weighted average return in this case is quite large.

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1. A fund begins with $10 million and reports the following three-month results (with negative figures in parentheses): Month

Net inflows (end of month, $ million) HPR (%)

1

2

3

3 2

5 8

0 (4)

Compute the arithmetic, time-weighted, and dollar-weighted average returns.

Conventions for Quoting Rates of Return We’ve seen that there are several ways to compute average rates of return. There also is some variation in how the mutual fund in our example might annualize its quarterly returns. Returns on assets with regular cash flows, such as mortgages (with monthly payments) and bonds (with semiannual coupons), usually are quoted as annual percentage rates, or APRs, which annualize per-period rates using a simple interest approach, ignoring compound interest. The APR can be translated to an effective annual rate (EAR) by remembering that APR Per-period rate Periods per year

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Therefore, to obtain the EAR if there are n compounding periods in the year, we first recover the rate per period as APR/n and then compound that rate for the number of periods in a year. (For example, n 12 for mortgages and n 2 for bonds making payments semiannually).

(

1 EAR (1 Rate per period)n 1

APR n

n

)

Rearranging, APR [(1 EAR)1/n 1] n

(5.1)

The formula assumes that you can earn the APR each period. Therefore, after one year (when n periods have passed), your cumulative return would be (1 APR/n)n. Note that one needs to know the holding period when given an APR in order to convert it to an effective rate. The EAR diverges from the APR as n becomes larger (that is, as we compound cash flows more frequently). In the limit, we can envision continuous compounding when n becomes extremely large in Equation 5.1. With continuous compounding, the relationship between the APR and EAR becomes EAR eAPR 1 or equivalently, APR ln(1 EAR)

(5.2)

Suppose you buy a Treasury bill maturing in one month for $9,900. On the bill’s maturity date, you collect the face value of $10,000. Since there are no other interest payments, the holding period return for this one-month investment is: HPR

Cash income Price change Initial price

$100 $9,900

0.0101 1.01%

The APR on this investment is therefore 1.01% 12 12.12%. The effective annual rate is higher: 1 EAR (1.0101)12 1.1282 which implies that EAR .1282 12.82%

The difficulties in interpreting rates of return over time do not end here. Two thorny issues remain: the uncertainty surrounding the investment in question and the effect of inflation.

5.2

RISK AND RISK PREMIUMS

Any investment involves some degree of uncertainty about future holding period returns, and in most cases that uncertainty is considerable. Sources of investment risk range from macroeconomic fluctuations, to the changing fortunes of various industries, to asset-specific unexpected developments. Analysis of these multiple sources of risk is presented in Part Four on Security Analysis.

Scenario Analysis and Probability Distributions When we attempt to quantify risk, we begin with the question: What HPRs are possible, and how likely are they? A good way to approach this question is to devise a list of possible economic

EXAMPLE 5.2 Annualizing Treasury-Bill Returns

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TA B L E 5.2

State of the Economy

Probability distribution of HPR on the stock market

Boom Normal growth Recession

scenario analysis Process of devising a list of possible economic scenarios and specifying the likelihood of each one, as well as the HPR that will be realized in each case.

probability distribution List of possible outcomes with associated probabilities.

expected return The mean value of the distribution of holding period returns.

variance The expected value of the squared deviation from the mean.

Scenario, s

Probability, p(s)

1 2 3

0.25 0.50 0.25

The square root of the variance.

HPR 44% 14 16

outcomes, or scenarios, and specify both the likelihood (i.e., the probability) of each scenario and the HPR the asset will realize in that scenario. Therefore, this approach is called scenario analysis. The list of possible HPRs with associated probabilities is called the probability distribution of HPRs. Consider an investment in a broad portfolio of stocks, say an index fund, which we will refer to as the “stock market.” A very simple scenario analysis for the stock market (assuming only three possible scenarios) is illustrated in Table 5.2. The probability distribution lets us derive measurements for both the reward and the risk of the investment. The reward from the investment is its expected return, which you can think of as the average HPR you would earn if you were to repeat an investment in the asset many times. The expected return also is called the mean of the distribution of HPRs and often is referred to as the mean return. To compute the expected return from the data provided, we label scenarios by s and denote the HPR in each scenario as r(s), with probability p(s). The expected return, denoted E(r), is then the weighted average of returns in all possible scenarios, s 1, . . . , S, with weights equal to the probability of that particular scenario. E(r)

S

兺 s1

p(s)r(s)

(5.3)

We show in Example 5.3, which follows shortly, that the data in Table 5.2 imply E(r) 14%. Of course, there is risk to the investment, and the actual return may be more or less than 14%. If a “boom” materializes, the return will be better, 44%, but in a recession, the return will be only 16%. How can we quantify the uncertainty of the investment? The “surprise” return on the investment in any scenario is the difference between the actual return and the expected return. For example, in a boom (scenario 1) the surprise is 30%: r(1) E(r) 44% 14% 30%. In a recession (scenario 3), the surprise is 30%: r(3) E(r) 16% 14% 30%. Uncertainty surrounding the investment is a function of the magnitudes of the possible surprises. To summarize risk with a single number we first define the variance as the expected value of the squared deviation from the mean (i.e., the expected value of the squared “surprise” across scenarios). Var(r) ⬅ 2

standard deviation

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S

兺 s1

p(s)[r(s) E(r)]2

(5.4)

We square the deviations because if we did not, negative deviations would offset positive deviations, with the result that the expected deviation from the mean return would necessarily be zero. Squared deviations are necessarily positive. Of course, squaring (a nonlinear transformation) exaggerates large (positive or negative) deviations and relatively deemphasizes small deviations. Another result of squaring deviations is that the variance has a dimension of percent squared. To give the measure of risk the same dimension as expected return (%), we use the standard deviation, defined as the square root of the variance: SD(r) ⬅ 兹苵苵苵苵苵 Var(r)

(5.5)

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A potential drawback to the use of variance and standard deviation as measures of risk is that they treat positive deviations and negative deviations from the expected return symmetrically. In practice, of course, investors welcome positive surprises, and a natural measure of risk would focus only on bad outcomes. However, if the distribution of returns is symmetric (meaning that the likelihood of negative surprises is roughly equal to the probability of positive surprises of the same magnitude), then standard deviation will approximate risk measures that concentrate solely on negative deviations. In the special case that the distribution of returns is approximately normal—represented by the well-known bell-shaped curve—the standard deviation will be perfectly adequate to measure risk. The evidence shows that for fairly short holding periods, the returns of most diversified portfolios are well described by a normal distribution. Applying Equation 5.3 to the data in Table 5.2, we find that the expected rate of return on the stock index fund is E(r) 0.25 44% 0.50 14% 0.25 (16%) 14% We use Equation 5.4 to find the variance. First we take the difference between the holding period return in each scenario and the mean return, then we square that difference, and finally we multiply by the probability of each scenario to find the average of the squared deviations. The result is

EXAMPLE 5.3 Expected Return and Standard Deviation

2 0.25(44 14)2 0.50(14 14)2 0.25(16 14)2 450 and so the standard deviation is 兹苵苵苵 450 21.21%

2. A share of stock of A-Star Inc. is now selling for $23.50. A financial analyst summarizes the uncertainty about the rate of return on the stock by specifying three possible scenarios: Business Conditions

Scenario, s

Probability, p

End-of-Year Price

Annual Dividend

High growth Normal growth No growth

1 2 3

0.35 0.30 0.35

$35 27 15

$4.40 4.00 4.00

5. a. Suppose the real interest rate is 3% per year, and the expected inflation rate is 8%. What is the nominal interest rate? b. Suppose the expected inflation rate rises to 10%, but the real rate is unchanged. What happens to the nominal interest rate?

5.5

asset allocation Portfolio choice among broad investment classes.

ASSET ALLOCATION ACROSS RISKY AND RISK-FREE PORTFOLIOS

History shows us that long-term bonds have been riskier investments than investments in Treasury bills and that stock investments have been riskier still. On the other hand, the riskier investments have offered higher average returns. Investors, of course, do not make all-ornothing choices from these investment classes. They can and do construct their portfolios using securities from all asset classes. Some of the portfolio may be in risk-free Treasury bills and some in high-risk stocks. The most straightforward way to control the risk of the portfolio is through the fraction of the portfolio invested in Treasury bills and other safe money market securities versus risky assets. This is an example of an asset allocation choice—a choice among broad investment classes, rather than among the specific securities within each asset class. Most investment professionals consider asset allocation the most important part of portfolio construction. Consider this statement by John Bogle, made when he was the chairman of the Vanguard Group of Investment Companies: The most fundamental decision of investing is the allocation of your assets: How much should you own in stock? How much should you own in bonds? How much should you own in cash reserves? . . . That decision [has been shown to account] for an astonishing 94% of the differences

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in total returns achieved by institutionally managed pension funds. . . . There is no reason to believe that the same relationship does not also hold true for individual investors.4

Therefore, we start our discussion of the risk-return trade-off available to investors by examining the most basic asset allocation choice: the choice of how much of the portfolio to place in risk-free money market securities versus other risky asset classes. We will denote the investor’s portfolio of risky assets as P, and the risk-free asset as F. We will assume for the sake of illustration that the risky component of the investor’s overall portfolio comprises two mutual funds: one invested in stocks and the other invested in long-term bonds. For now, we take the composition of the risky portfolio as given and focus only on the allocation between it and risk-free securities. In the next chapter, we turn to asset allocation and security selection across risky assets.

The Risky Asset When we shift wealth from the risky portfolio (P) to the risk-free asset, we do not change the relative proportions of the various risky assets within the risky portfolio. Rather, we reduce the relative weight of the risky portfolio as a whole in favor of risk-free assets. A simple example demonstrates the procedure. Assume the total market value of an investor’s portfolio is $300,000. Of that, $90,000 is invested in the Ready Assets money market fund, a risk-free asset. The remaining $210,000 is in risky securities, say $113,400 in the Vanguard S&P 500 index fund (called the Vanguard 500 Index Fund) and $96,600 in Fidelity’s Investment Grade Bond Fund. The Vanguard fund (V) is a passive equity fund that replicates the S&P 500 portfolio. The Fidelity Investment Grade Bond Fund (IG) invests primarily in corporate bonds with high safety ratings and also in Treasury bonds. We choose these two funds for the risky portfolio in the spirit of a low-cost, well-diversified portfolio. While in the next chapter we discuss portfolio optimization, here we simply assume the investor considers the given weighting of V and IG to be optimal. The holdings in Vanguard and Fidelity make up the risky portfolio, with 54% in V and 46% in IG. wV 113,400/210,000 0.54 (Vanguard) wIG 96,600/210,000 0.46 (Fidelity) The weight of the risky portfolio, P, in the complete portfolio, including risk-free as well as risky investments, is denoted by y, and so the weight of the money market fund is 1 y. y 210,000/300,000 0.7 (risky assets, portfolio P) 1 y 90,000/300,000 0.3 (risk-free assets) The weights of the individual assets in the complete portfolio (C) are: Vanguard Fidelity

113,400/300,000 0.378 96,600/300,000 0.322

Portfolio P 210,000/300,000 0.700 Ready Assets F 90,000/300,000 0.300 Portfolio C

300,000/300,000 1.000

Suppose the investor decides to decrease risk by reducing the exposure to the risky portfolio from y 0.7 to y 0.56. The risky portfolio would total only 0.56 300,000 $168,000, requiring the sale of $42,000 of the original $210,000 risky holdings, with the proceeds used to 4

John C. Bogle, Bogle on Mutual Funds (Burr Ridge, IL: Irwin Professional Publishing, 1994), p. 235.

complete portfolio The entire portfolio including risky and risk-free assets.

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purchase more shares in Ready Assets. Total holdings in the risk-free asset will increase to 300,000 (1 0.56) $132,000 (the original holdings plus the new contribution to the money market fund: 90,000 42,000 $132,000). The key point is that we leave the proportion of each asset in the risky portfolio unchanged. Because the weights of Vanguard and Fidelity in the risky portfolio are 0.54 and 0.46 respectively, we sell 0.54 42,000 $22,680 of Vanguard and 0.46 42,000 $19,320 of Fidelity. After the sale, the proportions of each fund in the risky portfolio are unchanged. wV

113,400 22,680 0.54 (Vanguard) 210,000 42,000

wIG

96,600 19,320 0.46 (Fidelity) 210,000 42,000

This procedure shows that rather than thinking of our risky holdings as Vanguard and Fidelity separately, we may view our holdings as if they are in a single fund holding Vanguard and Fidelity in fixed proportions. In this sense, we may treat the risky fund as a single risky asset, that asset being a particular bundle of securities. As we shift in and out of safe assets, we simply alter our holdings of that bundle of securities commensurately. Given this simplification, we now can turn to the desirability of reducing risk by changing the risky/risk-free asset mix, that is, reducing risk by decreasing the proportion y. Because we do not alter the weights of each asset within the risky portfolio, the probability distribution of the rate of return on the risky portfolio remains unchanged by the asset reallocation. What will change is the probability distribution of the rate of return on the complete portfolio that is made up of the risky and risk-free assets.

Concept CHECK

>

6. What will be the dollar value of your position in Vanguard and its proportion in your complete portfolio if you decide to hold 50% of your investment budget in Ready Assets?

The Risk-Free Asset The power to tax and to control the money supply lets the government, and only government, issue default-free bonds. The default-free guarantee by itself is not sufficient to make the bonds risk-free in real terms, since inflation affects the purchasing power of the proceeds from an investment in T-bills. The only risk-free asset in real terms would be a price-indexed government bond. Even then, a default-free, perfectly indexed bond offers a guaranteed real rate to an investor only if the maturity of the bond is identical to the investor’s desired holding period. These qualifications notwithstanding, it is common to view Treasury bills as the risk-free asset. Because they are short-term investments, their prices are relatively insensitive to interest rate fluctuations. An investor can lock in a short-term nominal return by buying a bill and holding it to maturity. Any inflation uncertainty over the course of a few weeks, or even months, is negligible compared to the uncertainty of stock market returns. In practice, most investors treat a broader range of money market instruments as effectively risk-free assets. All the money market instruments are virtually immune to interest rate risk (unexpected fluctuations in the price of a bond due to changes in market interest rates) because of their short maturities, and all are fairly safe in terms of default or credit risk. Money market mutual funds hold, for the most part, three types of securities: Treasury bills, bank certificates of deposit (CDs), and commercial paper. The instruments differ slightly in their default risk. The yields to maturity on CDs and commercial paper, for identical maturities, are always slightly higher than those of T-bills. A history of this yield spread for 90-day CDs is shown in Figure 2.3 in Chapter 2.

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Money market funds have changed their relative holdings of these securities over time, but by and large, T-bills make up only about 15% of their portfolios. Nevertheless, the risk of such blue-chip, short-term investments as CDs and commercial paper is minuscule compared to that of most other assets, such as long-term corporate bonds, common stocks, or real estate. Hence, we treat money market funds as representing the most easily accessible risk-free asset for most investors.

Portfolio Expected Return and Risk Now that we have specified the risky portfolio and the risk-free asset, we can examine the risk-return combinations that result from various investment allocations between these two assets. Finding the available combinations of risk and return is the “technical” part of asset allocation; it deals only with the opportunities available to investors given the features of the asset markets in which they can invest. In the next section, we address the “personal” part of the problem, the specific individual’s choice of the best risk-return combination from the set of feasible combinations, given his or her level of risk aversion. Since we assume the composition of the optimal risky portfolio (P) already has been determined, the concern here is with the proportion of the investment budget (y) to be allocated to the risky portfolio. The remaining proportion (1 y) is to be invested in the risk-free asset (F). We denote the actual risky rate of return by rP, the expected rate of return on P by E(rP), and its standard deviation by P. The rate of return on the risk-free asset is denoted as rf. In the numerical example, we assume E(rP) 15%, P 22%, and rf 7%. Thus, the risk premium on the risky asset is E(rP) rf 8%. Let’s start with two extreme cases. If you invest all of your funds in the risky asset, that is, if you choose y 1.0, the expected return on your complete portfolio will be 15% and the standard deviation will be 22%. This combination of risk and return is plotted as point P in Figure 5.5. At the other extreme, you might put all of your funds into the risk-free asset, that

E(r)

CAL = Capital allocation line P

E(rP) = 15% y = .50 rƒ = 7% F

y = 1.25 E(rP) – rƒ = 8%

S = 8/22

σP = 22%

F I G U R E 5.5 The investment opportunity set with a risky asset and a risk-free asset

σ

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is, you choose y 0. In this case, your portfolio would behave just as the risk-free asset, and you would earn a riskless return of 7%. (This choice is plotted as point F in Figure 5.5.) Now consider more moderate choices. For example, if you allocate equal amounts of your overall or complete portfolio, C, to the risky and risk-free assets, that is, if you choose y 0.5, the expected return on the complete portfolio will be an average of the expected return on portfolios F and P. Therefore, E(rC) 0.5 7% 0.5 15% 11%. The risk premium of the complete portfolio is therefore 11% 7% 4%, which is half of the risk premium of P. The standard deviation of the portfolio also is one-half of P’s, that is, 11%. When you reduce the fraction of the complete portfolio allocated to the risky asset by half, you reduce both the risk and risk premium by half. To generalize, the risk premium of the complete portfolio, C, will equal the risk premium of the risky asset times the fraction of the portfolio invested in the risky asset. E(rC) rf y[E(rP) rf]

(5.9)

The standard deviation of the complete portfolio will equal the standard deviation of the risky asset times the fraction of the portfolio invested in the risky asset. C yP

(5.10)

In sum, both the risk premium and the standard deviation of the complete portfolio increase in proportion to the investment in the risky portfolio. Therefore, the points that describe the risk and return of the complete portfolio for various asset allocations, that is, for various choices of y, all plot on the straight line connecting F and P, as shown in Figure 5.5, with an intercept of rf and slope (rise/run) of S

Concept CHECK

>

E(rP) rf 15 7 0.36 P 22

(5.11)

7. What are the expected return, risk premium, standard deviation, and ratio of risk premium to standard deviation for a complete portfolio with y 0.75?

The Capital Allocation Line capital allocation line Plot of risk-return combinations available by varying portfolio allocation between a risk-free asset and a risky portfolio.

The line plotted in Figure 5.5 depicts the risk-return combinations available by varying asset allocation, that is, by choosing different values of y. For this reason, it is called the capital allocation line, or CAL. The slope, S, of the CAL equals the increase in expected return that an investor can obtain per unit of additional standard deviation. In other words, it shows extra return per extra risk. For this reason, the slope also is called the reward-to-variability ratio. Notice that the reward-to-variability ratio is the same for risky portfolio P and the complete portfolio that was formed by mixing P and the risk-free asset in equal proportions. Expected Return

Risk Premium

Standard Deviation

reward-tovariability ratio

Portfolio P:

15%

8%

22%

Ratio of risk premium to standard deviation.

Portfolio C:

11%

4%

11%

Reward-toVariability Ratio 8 0.36 22 4 0.36 11

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In fact, the reward-to-variability ratio is the same for all complete portfolios that plot on the capital allocation line. While the risk-return combinations differ, the ratio of reward to risk is constant. What about points on the line to the right of portfolio P in the investment opportunity set? If investors can borrow at the (risk-free) rate of rf 7%, they can construct complete portfolios that plot on the CAL to the right of P. They simply choose values of y greater than 1.0. Suppose the investment budget is $300,000, and our investor borrows an additional $120,000, investing the $420,000 in the risky asset. This is a levered position in the risky asset, which is financed in part by borrowing. In that case y 420,000 1.4 300,000 and 1 y 1 1.4 0.4, reflecting a short position in the risk-free asset, or a borrowing position. Rather than lending at a 7% interest rate, the investor borrows at 7%. The portfolio rate of return is

EXAMPLE 5.6 Levered Complete Portfolios

E(rC) 7 (1.4 8) 18.2 Another way to find this portfolio rate of return is as follows. Your income statement will show that you expect to earn $63,000 (15% of $420,000) and pay $8,400 (7% of $120,000) in interest on the loan. Simple subtraction yields an expected profit of $54,000, which is 18.2% of your investment budget of $300,000. Your portfolio still exhibits the same reward-to-variability ratio: C 1.4 22 30.8 11.2 E(rC) rf S C 30.8

0.36

As you might have expected, the levered portfolio has both a higher expected return and a higher standard deviation than an unlevered position in the risky asset.

Of course, nongovernment investors cannot borrow at the risk-free rate. The risk of a borrower’s default leads lenders to demand higher interest rates on loans. Therefore, the nongovernment investor’s borrowing cost will exceed the lending rate of rf 7%. Suppose the borrowing rate is rB 9%. Then, for y greater than 1.0 (the borrowing range), the reward-to-variability ratio (the slope of the CAL) will be: [E(rP) rB]/P 6/22 0.27. Here, the borrowing rate (rB) replaces the lending rate (rf), reducing the “reward” (numerator) in the reward-to-variability ratio. The CAL will be “kinked” at point P as in Figure 5.6. To the left of P, where y 1, the investor is lending at 7% and the slope of the CAL is 0.36. To the right of P, where y 1, the investor is borrowing (at a higher than risk-free rate) to finance extra investments in the risky asset, and the slope is 0.27. In practice, borrowing to invest in the risky portfolio is easy and straightforward if you have a margin account with a broker. All you have to do is tell your broker you want to buy “on margin.” Margin purchases may not exceed 50% of the purchase value. For example, if your net worth in the account is $300,000, the broker is allowed to lend you up to $300,000 to purchase additional stock. You would then have $600,000 on the asset side of your account and $300,000 on the liability side, resulting in y 2.0. 8. Suppose there is a shift upward in the expected rate of return on the risky asset, from 15% to 17%. If all other parameters remain unchanged, what will be the slope of the CAL for y 1 and y 1?

1) = .27

S(y ≤ 1) = .36

σP = 22%

σ

F I G U R E 5.6 The opportunity set with differential borrowing and lending rates

Risk Tolerance and Asset Allocation We have developed the CAL, the graph of all feasible risk-return combinations available from allocating the complete portfolio between a risky portfolio and a risk-free asset. The investor confronting the CAL now must choose one optimal combination from the set of feasible choices. This choice entails a trade-off between risk and return. Individual investors with different levels of risk aversion, given an identical capital allocation line, will choose different positions in the risky asset. Specifically, the more risk-averse investors will choose to hold less of the risky asset and more of the risk-free asset. Graphically, more risk-averse investors will choose portfolios near point F on the capital allocation line plotted in Figure 5.5. More risk-tolerant investors will choose points closer to P, with higher expected return and higher risk. The most risk-tolerant investors will choose portfolios to the right of point P. These levered portfolios provide even higher expected returns, but even greater risk. The nearby box contains a further discussion of this risk-return trade-off, which sometimes is characterized as a decision to “eat well,” versus “sleep well.” You will eat well if you earn a high expected rate of return on your portfolio. However, this requires that you accept a large risk premium and, therefore, a large amount of risk. Unfortunately, this risk may make it difficult to sleep well. The investor’s asset allocation choice also will depend on the trade-off between risk and return. If the reward-to-variability ratio increases, then investors might well decide to take on riskier positions. For example, suppose an investor reevaluates the probability distribution of the risky portfolio and now perceives a greater expected return without an accompanying increase in the standard deviation. This amounts to an increase in the reward-to-variability ratio

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The Right Mix: Make Money vs. Sleep Soundly Plunged into doubt? Amid the recent market turmoil, maybe you are wondering whether you really have the right mix of investments. Here are a few thoughts to keep in mind:

TAKING STOCK If you are a bond investor who is petrified of stocks, the wild price swings of the past few weeks have probably confirmed all of your worst suspicions. But the truth is, adding stocks to your bond portfolio could bolster your returns, without boosting your portfolio’s overall gyrations. How can that be? While stocks and bonds often move up and down in tandem, this isn’t always the case, and sometimes stocks rise when bonds are tumbling. Indeed, Chicago researchers Ibbotson Associates figure a portfolio that’s 100% in longer-term government bonds has the same risk profile as a mix that includes 83% in longer-term government bonds and 17% in the blue-chip stocks that constitute Standard & Poor’s 500 stock index. The bottom line? Everybody should own some stocks. Even cowards.

PADDING THE MATTRESS On the other hand, maybe you’re a committed stock market investor, but you would like to add a calming influence to your portfolio. What’s your best bet? When investors look to mellow their stock portfolios, they usually turn to bonds. Indeed, the traditional balanced portfolio, which typically includes 60% stocks

and 40% bonds, remains a firm favorite with many investment experts. A balanced portfolio isn’t a bad bet. But if you want to calm your stock portfolio, I would skip bonds and instead add cash investments such as Treasury bills and money market funds. Ibbotson calculates that, over the past 25 years, a mix of 75% stocks and 25% Treasury bills would have performed about as well as a mix of 60% stocks and 40% longer-term government bonds, and with a similar level of portfolio price gyrations. Moreover, the stock–cash mix offers more certainty, because you know that even if your stocks fall in value, your cash never will. By contrast, both the stocks and bonds in a balanced portfolio can get hammered at the same time.

PATIENCE HAS ITS REWARDS, SOMETIMES Stocks are capable of generating miserable short-run results. During the past 50 years, the worst five-calendaryear stretch for stocks left investors with an annualized loss of 2.4%. But while any investment can disappoint in the short run, stocks do at least sparkle over the long haul. As a long-term investor, your goal is to fend off the dual threats of inflation and taxes and make your money grow. And on that score, stocks have been supreme. SOURCE: Abridged from Jonathan Clements, “The Right Mix: FineTuning a Portfolio to Make Money and Still Sleep Soundly,” The Wall Street Journal, July 23, 1996. Reprinted by permission of Dow Jones & Company, Inc. via Copyright Clearance Center, Inc. © 1996 Dow Jones & Company, Inc. All rights reserved Worldwide.

or, equivalently, an increase in the slope of the CAL. As a result, this investor will choose a higher y, that is, a greater position in the risky portfolio. One role of a professional financial adviser is to present investment opportunity alternatives to clients, obtain an assessment of the client’s risk tolerance, and help determine the appropriate complete portfolio.5

5.6

PASSIVE STRATEGIES AND THE CAPITAL MARKET LINE

The capital allocation line shows the risk-return trade-offs available by mixing risk-free assets with the investor’s risky portfolio. Investors can choose the assets included in the risky 5

“Risk tolerance” is simply the flip side of “risk aversion.” Either term is a reasonable way to describe attitudes toward risk. We generally find it easier to talk about risk aversion, but practitioners often use the term risk tolerance.

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Risk Premium (%)

TA B L E 5.5 Average rates of return, standard deviations, and the reward-to-variability ratio of the risk premiums of large common stocks over one-month bills over 1926–2001 and various subperiods.

1926–1944 1945–1963 1964–1982 1983–2001 1926–2001

Mean

Standard Deviation

Reward-toVariability Ratio

8.03 14.41 2.22 9.91 8.64

28.69 18.83 17.56 14.77 20.70

0.2798 0.7655 0.1265 0.6709 0.4176

Source: Prepared from data in Table 5.3.

passive strategy Investment policy that avoids security analysis.

capital market line The capital allocation line using the market index portfolio as the risky asset.

portfolio using either passive or active strategies. A passive strategy is based on the premise that securities are fairly priced and it avoids the costs involved in undertaking security analysis. Such a strategy might at first blush appear to be naive. However, we will see in Chapter 8 that intense competition among professional money managers might indeed force security prices to levels at which further security analysis is unlikely to turn up significant profit opportunities. Passive investment strategies may make sense for many investors. To avoid the costs of acquiring information on any individual stock or group of stocks, we may follow a “neutral” diversification approach. A natural strategy is to select a diversified portfolio of common stocks that mirrors the corporate sector of the broad economy. This results in a value-weighted portfolio, which, for example, invests a proportion in GM stock that equals the ratio of GM’s market value to the market value of all listed stocks. Such strategies are called indexing. The investor chooses a portfolio with all the stocks in a broad market index such as the Standard & Poor’s 500 index. The rate of return on the portfolio then replicates the return on the index. Indexing has become an extremely popular strategy for passive investors. We call the capital allocation line provided by one-month T-bills and a broad index of common stocks the capital market line (CML). That is, a passive strategy based on stocks and bills generates an investment opportunity set that is represented by the CML.

Historical Evidence on the Capital Market Line Can we use past data to help forecast the risk-return trade-off offered by the CML? The notion that one can use historical returns to forecast the future seems straightforward but actually is somewhat problematic. On one hand, you wish to use all available data to obtain a large sample. But when using long time series, old data may no longer be representative of future circumstances. Another reason for weeding out subperiods is that some past events simply may be too improbable to be given equal weight with results from other periods. Do the data we have pose this problem? Table 5.5 breaks the 76-year period, 1926–2001 into four subperiods and shows the risk premium, standard deviation, and reward-to-variability ratio for each subperiod. That ratio is

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Triumph of the Optimists As a whole, the last 7 decades have been very kind to U.S. equity investors. Stock investments have outperformed investments in safe Treasury bills by more than 8% per year. The real rate of return averaged more than 9%, implying an expected doubling of the real value of the investment portfolio about every 8 years! Is this experience representative? A new book by three professors at the London Business School, Elroy Dimson, Paul Marsh, and Mike Staunton, extends the U.S. evidence to other countries and to longer time periods. Their conclusion is given in the book’s title, Triumph of the Optimists*: in every country in their study (which included markets in North America, Europe, Asia, and Africa), the investment optimists—those who bet on the economy by investing in stocks rather than bonds or bills—were vindicated. Over the long haul, stocks beat bonds everywhere. On the other hand, the equity risk premium is probably not as large as the post-1926 evidence from

Table 5.1 would seem to indicate. First, results from the first 25 years of the last century (which included the first World War) were less favorable to stocks. Second, U.S. returns have been better than that of most other countries, and so a more representative value for the historical risk premium may be lower than the U.S. experience. Finally, the sample that is amenable to historical analysis suffers from a self-selection problem. Only those markets that have survived to be studied can be included in the analysis. This leaves out countries such as Russia or China, whose markets were shut down during communist rule, and whose results if included would surely bring down the average performance of equity investments. Nevertheless, there is powerful evidence of a risk premium that shows its force everywhere the authors looked. *Elroy Dimson, Paul Marsh, Mike Staunton, Triumph of the Optimists: 101 Years of Global Investment Returns. Princeton University Press, Princeton, N.J.: 2002.

the slope of the CML based on the subperiod data. Indeed, the differences across subperiods are quite striking. The most plausible explanation for the variation in subperiod returns is based on the observation that the standard deviation of returns is quite large in all subperiods. If we take the 76-year standard deviation of 20.3% as representative and assume that returns in one year are nearly uncorrelated with those in other years (the evidence suggests that any correlation across years is small), then the standard deviation of our estimate of the mean return in any of our 19-year subperiods will be 20.3/ 兹苵苵 19 4.7% , which is fairly large. This means that in approximately one out of three cases, a 19-year average will deviate by 4.7% or more from the true mean. Applying this insight to the data in Table 5.5 tells us that we cannot reject with any confidence the possibility that the true mean is similar in all subperiods! In other words, the “noise” in the data is so large that we simply cannot make reliable inferences from average returns in any subperiod. The variation in returns across subperiods may simply reflect statistical variation, and we have to reconcile ourselves to the fact that the market return and the reward-to-variability ratio for passive (as well as active!) strategies is simply very hard to predict. The instability of average excess return on stocks over the 19-year subperiods in Table 5.5 also calls into question the precision of the 76-year average excess return (8.64%) as an estimate of the risk premium on stocks looking into the future. In fact, there has been considerable recent debate among financial economists about the “true” equity risk premium, with an emerging consensus that the historical average is an unrealistically high estimate of the future risk premium. This argument is based on several factors: the use of longer time periods in

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which equity returns are examined; a broad range of countries rather than just the U.S. in which excess returns are computed (Dimson, Marsh, and Staunton, 2001); direct surveys of financial executives about their expectations for stock market returns (Graham and Harvey, 2001); and inferences from stock market data about investor expectations (Jagannathan, McGrattan, and Scherbina, 2000; Fama and French, 2002). The nearby box discusses some of this evidence.

Costs and Benefits of Passive Investing How reasonable is it for an investor to pursue a passive strategy? We cannot answer such a question definitively without comparing passive strategy results to the costs and benefits accruing to an active portfolio strategy. Some issues are worth considering, however. First, the alternative active strategy entails costs. Whether you choose to invest your own valuable time to acquire the information needed to generate an optimal active portfolio of risky assets or whether you delegate the task to a professional who will charge a fee, constructing an active portfolio is more expensive than constructing a passive one. The passive portfolio requires only small commissions on purchases of U.S. T-bills (or zero commissions if you purchase bills directly from the government) and management fees to a mutual fund company that offers a market index fund to the public. An index fund has the lowest operating expenses of all mutual stock funds because it requires minimal effort. A second argument supporting a passive strategy is the free-rider benefit. If you assume there are many active, knowledgeable investors who quickly bid up prices of undervalued assets and offer down overvalued assets (by selling), you have to conclude that most of the time most assets will be fairly priced. Therefore, a well-diversified portfolio of common stock will be a reasonably fair buy, and the passive strategy may not be inferior to that of the average active investor. We will expand on this insight and provide a more comprehensive analysis of the relative success of passive strategies in Chapter 8. To summarize, a passive strategy involves investment in two passive portfolios: virtually risk-free short-term T-bills (or a money market fund) and a fund of common stocks that mimics a broad market index. Recall that the capital allocation line representing such a strategy is called the capital market line. Using Table 5.5, we see that using 1926 to 2001 data, the passive risky portfolio has offered an average excess return of 8.6% with a standard deviation of 20.7%, resulting in a reward-to-variability ratio of 0.42.

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SUMMARY

• Investors face a trade-off between risk and expected return. Historical data confirm our intuition that assets with low degrees of risk provide lower returns on average than do those of higher risk. • Shifting funds from the risky portfolio to the risk-free asset is the simplest way to reduce risk. Another method involves diversification of the risky portfolio. We take up diversification in later chapters. • U.S. T-bills provide a perfectly risk-free asset in nominal terms only. Nevertheless, the standard deviation of real rates on short-term T-bills is small compared to that of assets such as long-term bonds and common stocks, so for the purpose of our analysis, we consider T-bills the risk-free asset. Besides T-bills, money market funds hold short-term, safe obligations such as commercial paper and CDs. These entail some default risk but relatively little compared to most other risky assets. For convenience, we often refer to money market funds as risk-free assets. • A risky investment portfolio (referred to here as the risky asset) can be characterized by its reward-to-variability ratio. This ratio is the slope of the capital allocation line (CAL), the

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line connecting the risk-free asset to the risky asset. All combinations of the risky and riskfree asset lie on this line. Investors would prefer a steeper sloping CAL, because that means higher expected returns for any level of risk. If the borrowing rate is greater than the lending rate, the CAL will be “kinked” at the point corresponding to an investment of 100% of the complete portfolio in the risky asset. • An investor’s preferred choice among the portfolios on the capital allocation line will depend on risk aversion. Risk-averse investors will weight their complete portfolios more heavily toward Treasury bills. Risk-tolerant investors will hold higher proportions of their complete portfolios in the risky asset. • The capital market line is the capital allocation line that results from using a passive investment strategy that treats a market index portfolio, such as the Standard & Poor’s 500, as the risky asset. Passive strategies are low-cost ways of obtaining well-diversified portfolios with performance that will reflect that of the broad stock market. expected return, 136 geometric average, 133 holding-period return, 132 inflation rate, 147 nominal interest rate, 147 passive strategy, 156 probability distribution, 136 real interest rate, 147

reward-to-variability ratio, 152 risk aversion, 138 risk-free rate, 137 risk premium, 137 scenario analysis, 136 standard deviation, 136 variance, 136

1. A portfolio of nondividend-paying stocks earned a geometric mean return of 5.0% between January 1, 1996, and December 31, 2002. The arithmetic mean return for the same period was 6.0 %. If the market value of the portfolio at the beginning of 1996 was $100,000, what was the market value of the portfolio at the end of 2002? 2. Which of the following statements about the standard deviation is/are true? A standard deviation: i. Is the square root of the variance. ii. Is denominated in the same units as the original data. iii. Can be a positive or a negative number. 3. Which of the following statements reflects the importance of the asset allocation decision to the investment process? The asset allocation decision: a. Helps the investor decide on realistic investment goals. b. Identifies the specific securities to include in a portfolio. c. Determines most of the portfolio’s returns and volatility over time. d. Creates a standard by which to establish an appropriate investment time horizon. 4. Look at Table 5.2 in the text. Suppose you now revise your expectations regarding the stock market as follows: State of the Economy

Probability

HPR

Boom Normal growth Recession

0.3 0.4 0.3

44% 14 16

KEY TERMS

PROBLEM SETS

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arithmetic average, 133 asset allocation, 148 capital allocation line, 152 capital market line, 156 complete portfolio, 149 dollar-weighted average return, 134 excess return, 138

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Use Equations 5.3–5.5 to compute the mean and standard deviation of the HPR on stocks. Compare your revised parameters with the ones in the text. 5. The stock of Business Adventures sells for $40 a share. Its likely dividend payout and end-of-year price depend on the state of the economy by the end of the year as follows: Dividend

Stock Price

$2.00 1.00 .50

$50 43 34

Boom Normal economy Recession

a. Calculate the expected holding-period return and standard deviation of the holdingperiod return. All three scenarios are equally likely. b. Calculate the expected return and standard deviation of a portfolio invested half in Business Adventures and half in Treasury bills. The return on bills is 4%. Use the following data in answering questions 6, 7, and 8. Utility Formula Data Investment

Expected Return E(r)

Standard Deviation

1 2 3 4

.12 .15 .21 .24

.30 .50 .16 .21

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U E(r) 1⁄2A2

where A 4

6. Based on the utility formula above, which investment would you select if you were risk averse with A 4? a. 1 b. 2 c. 3 d. 4 7. Based on the utility formula above, which investment would you select if you were risk neutral? a. 1 b. 2 c. 3 d. 4 8. The variable (A) in the utility formula represents the: a. investor’s return requirement. b. investor’s aversion to risk. c. certainty equivalent rate of the portfolio. d. preference for one unit of return per four units of risk. Use the following expectations on Stocks X and Y to answer questions 9 through 12 (round to the nearest percent).

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Bear Market

Normal Market

Bull Market

0.2 20% 15%

0.5 18% 20%

0.3 50% 10%

Probability Stock X Stock Y

161

9. What are the expected returns for Stocks X and Y? Stock X

Stock Y

18% 18% 20% 20%

5% 12% 11% 10%

a. b. c. d.

10. What are the standard deviations of returns on Stocks X and Y? Stock X

Stock Y

15% 20% 24% 28%

26% 4% 13% 8%

a. b. c. d.

Probability of Economic State

Stock Performance

Probability of Stock Performance in Given Economic State

Good

.3

Neutral

.5

Poor

.2

Good Neutral Poor Good Neutral Poor Good Neutral Poor

.6 .3 .1 .4 .3 .3 .2 .3 .5

State of Economy

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11. Assume that of your $10,000 portfolio, you invest $9,000 in Stock X and $1,000 in Stock Y. What is the expected return on your portfolio? a. 18% b. 19% c. 20% d. 23% 12. Probabilities for three states of the economy, and probabilities for the returns on a particular stock in each state are shown in the table below.

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The probability that the economy will be neutral and the stock will experience poor performance is a. .06 c. .50 b. .15 d. .80 13. An analyst estimates that a stock has the following probabilities of return depending on the state of the economy: State of Economy

Probability

Return

.1 .6 .3

15% 13 7

Good Normal Poor

The expected return of the stock is: a. 7.8% b. 11.4% c. 11.7% d. 13.0% 14. XYZ stock price and dividend history are as follows:

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15.

16. 17. 18.

Year

Beginning-of-Year Price

Dividend Paid at Year-End

1999 2000 2001 2002

$100 $110 $ 90 $ 95

$4 $4 $4 $4

An investor buys three shares of XYZ at the beginning of 1999 buys another two shares at the beginning of 2000, sells one share at the beginning of 2001, and sells all four remaining shares at the beginning of 2002. a. What are the arithmetic and geometric average time-weighted rates of return for the investor? b. What is the dollar-weighted rate of return. Hint: Carefully prepare a chart of cash flows for the four dates corresponding to the turns of the year for January 1, 1999, to January 1, 2002. If your calculator cannot calculate internal rate of return, you will have to use trial and error. a. Suppose you forecast that the standard deviation of the market return will be 20% in the coming year. If the measure of risk aversion in equation 5.6 is A 4, what would be a reasonable guess for the expected market risk premium? b. What value of A is consistent with a risk premium of 9%? c. What will happen to the risk premium if investors become more risk tolerant? Using the historical risk premiums as your guide, what is your estimate of the expected annual HPR on the S&P 500 stock portfolio if the current risk-free interest rate is 5%? What has been the historical average real rate of return on stocks, Treasury bonds, and Treasury notes? Consider a risky portfolio. The end-of-year cash flow derived from the portfolio will be either $50,000 or $150,000, with equal probabilities of 0.5. The alternative riskless investment in T-bills pays 5%.

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a. If you require a risk premium of 10%, how much will you be willing to pay for the portfolio? b. Suppose the portfolio can be purchased for the amount you found in (a). What will the expected rate of return on the portfolio be? c. Now suppose you require a risk premium of 15%. What is the price you will be willing to pay now? d. Comparing your answers to (a) and (c), what do you conclude about the relationship between the required risk premium on a portfolio and the price at which the portfolio will sell? For problems 19–23, assume that you manage a risky portfolio with an expected rate of return of 17% and a standard deviation of 27%. The T-bill rate is 7%. 19. a. Your client chooses to invest 70% of a portfolio in your fund and 30% in a T-bill money market fund. What is the expected return and standard deviation of your client’s portfolio? b. Suppose your risky portfolio includes the following investments in the given proportions:

20.

21.

22.

23.

27% 33% 40%

What are the investment proportions of your client’s overall portfolio, including the position in T-bills? c. What is the reward-to-variability ratio (S) of your risky portfolio and your client’s overall portfolio? d. Draw the CAL of your portfolio on an expected return/standard deviation diagram. What is the slope of the CAL? Show the position of your client on your fund’s CAL. Suppose the same client in problem 19 decides to invest in your risky portfolio a proportion (y) of his total investment budget so that his overall portfolio will have an expected rate of return of 15%. a. What is the proportion y? b. What are your client’s investment proportions in your three stocks and the T-bill fund? c. What is the standard deviation of the rate of return on your client’s portfolio? Suppose the same client in problem 19 prefers to invest in your portfolio a proportion (y) that maximizes the expected return on the overall portfolio subject to the constraint that the overall portfolio’s standard deviation will not exceed 20%. a. What is the investment proportion, y? b. What is the expected rate of return on the overall portfolio? You estimate that a passive portfolio invested to mimic the S&P 500 stock index yields an expected rate of return of 13% with a standard deviation of 25%. Draw the CML and your fund’s CAL on an expected return/standard deviation diagram. a. What is the slope of the CML? b. Characterize in one short paragraph the advantage of your fund over the passive fund. Your client (see problem 19) wonders whether to switch the 70% that is invested in your fund to the passive portfolio. a. Explain to your client the disadvantage of the switch.

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Stock A Stock B Stock C

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b. Show your client the maximum fee you could charge (as a percent of the investment in your fund deducted at the end of the year) that would still leave him at least as well off investing in your fund as in the passive one. (Hint: The fee will lower the slope of your client’s CAL by reducing the expected return net of the fee.) 24. What do you think would happen to the expected return on stocks if investors perceived an increase in the volatility of stocks? 25. The change from a straight to a kinked capital allocation line is a result of the: a. Reward-to-variability ratio increasing. b. Borrowing rate exceeding the lending rate. c. Investor’s risk tolerance decreasing. d. Increase in the portfolio proportion of the risk-free asset. 26. You manage an equity fund with an expected risk premium of 10% and an expected standard deviation of 14%. The rate on Treasury bills is 6%. Your client chooses to invest $60,000 of her portfolio in your equity fund and $40,000 in a T-bill money market fund. What is the expected return and standard deviation of return on your client’s portfolio? Expected Return

a. b. c. d.

8.4% 8.4 12.0 12.0

Standard Deviation of Return 8.4% 14.0 8.4 14.0

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27. What is the reward-to-variability ratio for the equity fund in problem 26? a. .71 b. 1.00 c. 1.19 d. 1.91 For problems 28–30, download Table 5.3: Rates of return, 1926–2001, from www.mhhe.com/ blkm. 28. Calculate the same subperiod means and standard deviations for small stocks as Table 5.5 of the text provides for large stocks. a. Do small stocks provide better reward-to-variability ratios than large stocks? b. Do small stocks show a similar declining trend in standard deviation as Table 5.5 documents for large stocks? 29. Convert the nominal returns on both large and small stocks to real rates. Reproduce Table 5.5 using real rates instead of excess returns. Compare the results to those of Table 5.5. 30. Repeat problem 29 for small stocks and compare with the results for nominal rates.

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WEBMA STER Inflation and Interest Rates The Federal Reserve Bank of St. Louis has several sources of information available on interest rates and economic conditions. One publication called Monetary Trends contains graphs and tabular information relevant to assess conditions in the capital markets. Go to the most recent edition of Monetary Trends at http://www.stls.frb.org/ docs/publications/mt/mt.pdf and answer the following questions: 1.

What is the current level of three-month and long-term Treasury yields?

2.

Have nominal interest rates increased, decreased, or remained the same over the last three months?

3.

Have real interest rates increased, decreased, or remained the same over the last two years?

4.

Examine the information comparing recent U.S. inflation and long-term interest rates with the inflation and long-term interest rate experience of Japan. Are the results consistent with theory?

1. a. The arithmetic average is (2 8 4)/3 2% per month. b. The time-weighted (geometric) average is [(1 .02) (1 .08) (1 .04)]1/3 .0188 1.88% per month c. We compute the dollar-weighted average (IRR) from the cash flow sequence (in $ millions):

SOLUTIONS TO

> > >

168

Show how covariance and correlation affect the power of diversification to reduce portfolio risk. Construct efficient portfolios. Calculate the composition of the optimal risky portfolio. Use factor models to analyze the risk characteristics of securities and portfolios.

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Related Websites http://finance.yahoo.com http://moneycentral.msn.com/investor These sites can be used to find historical price information for estimating returns, standard deviation of returns, and covariance of returns for individual securities.

http://www.financialengines.com This site provides risk measures that can be used to compare individual stocks to an average hypothetical portfolio.

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The risk measure is based on the concept of value at risk and includes some capabilities of stress testing.

http://aida.econ.yale.edu/~shiller/data.htm Professor Shiller provides historical data used in his applications in Irrational Exuberance. The site also has links to other data sites.

http://www.mhhe.com/edumarketinsight The Education Version of Market Insight contains information on monthly, weekly, and daily returns. You can use these data in estimating correlation coefficients and covariance to find optimal portfolios.

http://www.portfolioscience.com Here you’ll find historical information to calculate potential losses on individual securities or portfolios.

n this chapter we describe how investors can construct the best possible risky portfolio. The key concept is efficient diversification. The notion of diversification is age-old. The adage “don’t put all your eggs in one basket” obviously predates economic theory. However, a formal model showing how to make the most of the power of diversification was not devised until 1952, a feat for which Harry Markowitz eventually won the Nobel Prize in economics. This chapter is largely developed from his work, as well as from later insights that built on his work. We start with a bird’s-eye view of how diversification reduces the variability of portfolio returns. We then turn to the construction of optimal risky portfolios. We follow a top-down approach, starting with asset allocation across a small set of broad asset classes, such as stocks, bonds, and money market securities. Then we show how the principles of optimal asset allocation can easily be generalized to solve the problem of security selection among many risky assets. We discuss the efficient set of risky portfolios and show how it leads us to the best attainable capital allocation. Finally, we show how factor models of security returns can simplify the search for efficient portfolios and the interpretation of the risk characteristics of individual securities. An appendix examines the common fallacy that long-term investment horizons mitigate the impact of asset risk. We argue that the common belief in “time diversification” is in fact an illusion and is not real diversification.

I

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6.1

market risk, systematic risk, nondiversifiable risk Risk factors common to the whole economy.

F I G U R E 6.1

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DIVERSIFICATION AND PORTFOLIO RISK

Suppose you have in your risky portfolio only one stock, say, Dell Computer Corporation. What are the sources of risk affecting this “portfolio”? We can identify two broad sources of uncertainty. The first is the risk that has to do with general economic conditions, such as the business cycle, the inflation rate, interest rates, exchange rates, and so forth. None of these macroeconomic factors can be predicted with certainty, and all affect the rate of return Dell stock eventually will provide. Then you must add to these macro factors firm-specific influences, such as Dell’s success in research and development, its management style and philosophy, and so on. Firm-specific factors are those that affect Dell without noticeably affecting other firms. Now consider a naive diversification strategy, adding another security to the risky portfolio. If you invest half of your risky portfolio in ExxonMobil, leaving the other half in Dell, what happens to portfolio risk? Because the firm-specific influences on the two stocks differ (statistically speaking, the influences are independent), this strategy should reduce portfolio risk. For example, when oil prices fall, hurting ExxonMobil, computer prices might rise, helping Dell. The two effects are offsetting, which stabilizes portfolio return. But why stop at only two stocks? Diversifying into many more securities continues to reduce exposure to firm-specific factors, so portfolio volatility should continue to fall. Ultimately, however, even with a large number of risky securities in a portfolio, there is no way to avoid all risk. To the extent that virtually all securities are affected by common (risky) macroeconomic factors, we cannot eliminate our exposure to general economic risk, no matter how many stocks we hold. Figure 6.1 illustrates these concepts. When all risk is firm-specific, as in Figure 6.1A, diversification can reduce risk to low levels. With all risk sources independent, and with investment spread across many securities, exposure to any particular source of risk is negligible. This is just an application of the law of averages. The reduction of risk to very low levels because of independent risk sources is sometimes called the insurance principle. When common sources of risk affect all firms, however, even extensive diversification cannot eliminate risk. In Figure 6.1B, portfolio standard deviation falls as the number of securities increases, but it is not reduced to zero. The risk that remains even after diversification is called market risk, risk that is attributable to marketwide risk sources. Other names are systematic

σ

σ

Portfolio risk as a function of the number of stocks in the portfolio Unique risk

Market risk n A: Firm-specific risk only

n B: Market and unique risk

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risk or nondiversifiable risk. The risk that can be eliminated by diversification is called unique risk, firm-specific risk, nonsystematic risk, or diversifiable risk. This analysis is borne out by empirical studies. Figure 6.2 shows the effect of portfolio diversification, using data on NYSE stocks. The figure shows the average standard deviations of equally weighted portfolios constructed by selecting stocks at random as a function of the number of stocks in the portfolio. On average, portfolio risk does fall with diversification, but the power of diversification to reduce risk is limited by common sources of risk. The box on the following page highlights the dangers of neglecting diversification and points out that such neglect is widespread.

unique risk, firm-specific risk, nonsystematic risk, diversifiable risk

6

6.2

Risk that can be eliminated by diversification.

ASSET ALLOCATION WITH TWO RISKY ASSETS

In the last chapter we examined the simplest asset allocation decision, that involving the choice of how much of the portfolio to place in risk-free money market securities versus in a risky portfolio. We simply assumed that the risky portfolio comprised a stock and a bond fund in given proportions. Of course, investors need to decide on the proportion of their portfolios to allocate to the stock versus the bond market. This, too, is an asset allocation decision. As the box on page 173 emphasizes, most investment professionals recognize that the asset allocation decision must take precedence over the choice of particular stocks or mutual funds. We examined capital allocation between risky and risk-free assets in the last chapter. We turn now to asset allocation between two risky assets, which we will continue to assume are two mutual funds, one a bond fund and the other a stock fund. After we understand the properties of portfolios formed by mixing two risky assets, we will reintroduce the choice of the third, risk-free portfolio. This will allow us to complete the basic problem of asset allocation across the three key asset classes: stocks, bonds, and risk-free money market securities. Once you understand this case, it will be easy to see how portfolios of many risky securities might best be constructed.

Covariance and Correlation

100%

50 40

75%

30 50% 40%

20 10 0

Risk compared to a one-stock portfolio

Average portfolio standard deviation (%)

Because we now envision forming a risky portfolio from two risky assets, we need to understand how the uncertainties of asset returns interact. It turns out that the key determinant of portfolio risk is the extent to which the returns on the two assets tend to vary either in tandem

0

2 4 6 8 10 12 14 16 18 20 Number of stocks in portfolio

0 100 200 300 400 500 600 700 800 9001,000

F I G U R E 6.2 Portfolio risk decreases as diversification increases Source: Meir Statman, “How Many Stocks Make a Diversified Portfolio?” Journal of Financial and Quantitative Analysis 22, September 1987.

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Dangers of Not Diversifying Hit Investors Enron, Tech Bubble Are Wake-Up Calls Mutual-fund firms and financial planners have droned on about the topic for years. But suddenly, it’s at the epicenter of lawsuits, congressional hearings and presidential reform proposals. Diversification—that most basic of investing principles—has returned with a vengeance. During the late 1990s, many people scoffed at being diversified, because the idea of investing in a mix of stocks, bonds and other financial assets meant missing out on some of the soaring gains of tech stocks. But with the collapse of the tech bubble and now the fall of Enron Corp. wiping out the 401(k) holdings of many current and retired Enron employees, the dangers of overloading a portfolio with one stock—or even with a group of similar stocks—has hit home for many investors. The pitfalls of holding too much of one company’s stock aren’t limited to Enron. Since the beginning of 2000, nearly one of every five U.S. stocks has fallen by two-thirds or more, while only 1% of diversified stock mutual funds have swooned as much, according to research firm Morningstar Inc. While not immune from losses, mutual funds tend to weather storms better, because they spread their bets over dozens or hundreds of companies. “Most

people think their company is safer than a stock mutual fund, when the data show that the opposite is true,” says John Rekenthaler, president of Morningstar’s online-advice unit. While some companies will match employees’ 401(k) contributions exclusively in company stock, investors can almost always diversify a large portion of their 401(k)—namely, the part they contribute themselves. Half or more of the assets in a typical 401(k) portfolio are contributed by employees themselves, so diversifying this portion of their portfolio can make a significant difference in reducing overall investing risk. But in picking an investing alternative to buying your employer’s stock, some choices are more useful than others. For example, investors should take into account the type of company they work for when diversifying. Workers at small technology companies—the type of stock often held by growth funds—might find better diversification with a fund focusing on large undervalued companies. Conversely, an auto-company worker might want to put more money in funds that specialize in smaller companies that are less tied to economic cycles.

SOURCE: Abridged from Aaron Luccheth and Theo Francis, “Dangers of Not Diversifying Hit Investors,” The Wall Street Journal, February 15, 2002.

or in opposition. Portfolio risk depends on the correlation between the returns of the assets in the portfolio. We can see why using a simple scenario analysis. Suppose there are three possible scenarios for the economy: a recession, normal growth, and a boom. The performance of stock funds tends to follow the performance of the broad economy. So suppose that in a recession, the stock fund will have a rate of return of 11%, in a normal period it will have a rate of return of 13%, and in a boom period it will have a rate of return of 27%. In contrast, bond funds often do better when the economy is weak. This is because interest rates fall in a recession, which means that bond prices rise. Suppose that a bond fund will provide a rate of return of 16% in a recession, 6% in a normal period, and 4% in a boom. These assumptions and the probabilities of each scenario are summarized in Spreadsheet 6.1. The expected return on each fund equals the probability-weighted average of the outcomes in the three scenarios. The last row of Spreadsheet 6.1 shows that the expected return of the stock fund is 10%, and that of the bond fund is 6%. As we discussed in the last chapter, the variance is the probability-weighted average across all scenarios of the squared deviation between the actual return of the fund and its expected return; the standard deviation is the square root of the variance. These values are computed in Spreadsheet 6.2. What about the risk and return characteristics of a portfolio made up from the stock and bond funds? The portfolio return is the weighted average of the returns on each fund with weights equal to the proportion of the portfolio invested in each fund. Suppose we form a 172

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First Take Care of Asset-Allocation Needs If you want to build a top-performing mutual-fund portfolio, you should start by hunting for top-performing funds, right? Wrong. Too many investors gamely set out to find top-notch funds without first settling on an overall portfolio strategy. Result? These investors wind up with a mishmash of funds that don’t add up to a decent portfolio. . . . . . . So what should you do? With more than 11,000 stock, bond, and money-market funds to choose from, you couldn’t possibly analyze all the funds available. Instead, to make sense of the bewildering array of funds available, you should start by deciding what basic mix of stock, bond, and money-market funds you want to hold. This is what experts call your “asset allocation.” This asset allocation has a major influence on your portfolio’s performance. The more you have in stocks, the higher your likely long-run return. But with the higher potential return from stocks come sharper short-term swings in a portfolio’s value. As a result, you may want to include a healthy dose of bond and money-market funds, especially if you are a conservative investor or you will need to tap your portfolio for cash in the near future.

Once you have settled on your asset-allocation mix, decide what sort of stock, bond, and money-market funds you want to own. This is particularly critical for the stock portion of your portfolio. One way to damp the price swings in your stock portfolio is to spread your money among large, small, and foreign stocks. You could diversify even further by making sure that, when investing in U.S. large- and small-company stocks, you own both growth stocks with rapidly increasing sales or earnings and also beaten-down value stocks that are inexpensive compared with corporate assets or earnings. Similarly, among foreign stocks, you could get additional diversification by investing in both developed foreign markets such as France, Germany, and Japan, and also emerging markets like Argentina, Brazil, and Malaysia.

Source: Abridged from Jonathan Clements, “It Pays for You to Take Care of Asset-Allocation Needs before Latching onto Fads,” The Wall Street Journal, April 6, 1998. Reprinted by permission of Dow Jones & Company, Inc. via Copyright Clearance Center, Inc. © 1998 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

portfolio with 60% invested in the stock fund and 40% in the bond fund. Then the portfolio return in each scenario is the weighted average of the returns on the two funds. For example Portfolio return in recession 0.60 (11%) 0.40 16% 0.20% which appears in cell C5 of Spreadsheet 6.3. Spreadsheet 6.3 shows the rate of return of the portfolio in each scenario, as well as the portfolio’s expected return, variance, and standard deviation. Notice that while the portfolio’s expected return is just the average of the expected return of the two assets, the standard deviation is actually less than that of either asset.

S P R E A D S H E E T 6.1 Capital market expectations for the stock and bond funds

A

B

1 2 3 4 5 6

Scenario Probability Recession 0.3 Normal 0.4 Boom 0.3 Expected or Mean Return:

C

D

Stock Fund Rate of Return Col. B Col. C 11 3.3 13 5.2 27 8.1 SUM: 10.0

E

F

Bond Fund Rate of Return Col. B Col. E 16 4.8 6 2.4 4 1.2 SUM: 6.0

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S P R E A D S H E E T 6.2 Variance of returns

A 1 2 3 4 5 6 7 8 9 10

B

C

D

E

F

Stock Fund Deviation Rate from Column B of Expected Squared x Prob. Return Return Deviation Column E 0.3 -11 -21 441 132.3 0.4 13 3 9 3.6 0.3 27 17 289 86.7 Variance = SUM 222.6 Standard deviation = SQRT(Variance) 14.92

Scenario Recession Normal Boom

G

Rate of Return 16 6 -4

H

I

J

Bond Fund Deviation from Column B Expected Squared x Return Deviation Column I 10 100 30 0 0 0 -10 100 30 Sum: 60 Sum: 7.75

S P R E A D S H E E T 6.3 Performance of the portfolio of stock and bond funds

A 1 2 3 4 5 6 7 8 9

Scenario Recession Normal Boom

B

C

D

E

F

G

Portfolio of 60% in stocks and 40% in bonds Rate Column B Deviation from Column B of x Expected Squared x Probability Return Column C Return Deviation Column F 0.3 -0.2 -0.06 -8.60 73.96 22.188 0.4 10.2 4.08 1.80 3.24 1.296 0.3 14.6 4.38 6.20 38.44 11.532 Expected return: 8.40 Variance: 35.016 Standard deviation: 5.92

The low risk of the portfolio is due to the inverse relationship between the performance of the two funds. In a recession, stocks fare poorly, but this is offset by the good performance of the bond fund. Conversely, in a boom scenario, bonds fall, but stocks do well. Therefore, the portfolio of the two risky assets is less risky than either asset individually. Portfolio risk is reduced most when the returns of the two assets most reliably offset each other. The natural question investors should ask, therefore, is how one can measure the tendency of the returns on two assets to vary either in tandem or in opposition to each other. The statistics that provide this measure are the covariance and the correlation coefficient. The covariance is calculated in a manner similar to the variance. Instead of measuring the typical difference of an asset return from its expected value, however, we wish to measure the extent to which the variation in the returns on the two assets tend to reinforce or offset each other. We start in Spreadsheet 6.4 with the deviation of the return on each fund from its expected or mean value. For each scenario, we multiply the deviation of the stock fund return from its mean by the deviation of the bond fund return from its mean. The product will be positive if both asset returns exceed their respective means in that scenario or if both fall short of their respective means. The product will be negative if one asset exceeds its mean return, while the other falls short of its mean return. For example, Spreadsheet 6.4 shows that the stock fund return in the recession falls short of its expected value by 21%, while the bond fund return exceeds its mean by 10%. Therefore, the product of the two deviations in the recession is 21 10 210, as reported in column E. The product of deviations is negative if one asset performs well when the other is performing poorly. It is positive if both assets perform well or poorly in the same scenarios.

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S P R E A D S H E E T 6.4 Covariance between the returns of the stock and bond funds

A 1 2 3 4 5 6 7

B

C

D

E

F

Deviation from Mean Return Covariance Scenario Probability Stock Fund Bond Fund Product of Dev Col. B Col. E Recession 0.3 21 10 210 63 Normal 0.4 3 0 0 0 Boom 0.3 17 10 170 51 Covariance: SUM: 114 Correlation coefficient = Covariance/(StdDev(stocks)*StdDev(bonds)): 0.99

If we compute the probability-weighted average of the products across all scenarios, we obtain a measure of the average tendency of the asset returns to vary in tandem. Since this is a measure of the extent to which the returns tend to vary with each other, that is, to co-vary, it is called the covariance. The covariance of the stock and bond funds is computed in the next-tolast line of Spreadsheet 6.4. The negative value for the covariance indicates that the two assets vary inversely, that is, when one asset performs well, the other tends to perform poorly. Unfortunately, it is difficult to interpret the magnitude of the covariance. For instance, does the covariance of 114 indicate that the inverse relationship between the returns on stock and bond funds is strong or weak? It’s hard to say. An easier statistic to interpret is the correlation coefficient, which is simply the covariance divided by the product of the standard deviations of the returns on each fund. We denote the correlation coefficient by the Greek letter rho, . Correlation coefficient

Covariance 114 .99 stock bond 14.92 7.75

Correlations can range from values of 1 to 1. Values of 1 indicate perfect negative correlation, that is, the strongest possible tendency for two returns to vary inversely. Values of 1 indicate perfect positive correlation. Correlations of zero indicate that the returns on the two assets are unrelated to each other. The correlation coefficient of 0.99 confirms the overwhelming tendency of the returns on the stock and bond funds to vary inversely in this scenario analysis. We are now in a position to derive the risk and return features of portfolios of risky assets. 1. Suppose the rates of return of the bond portfolio in the three scenarios of Spreadsheet 6.4 are 10% in a recession, 7% in a normal period, and 2% in a boom. The stock returns in the three scenarios are 12% (recession), 10% (normal), and 28% (boom). What are the covariance and correlation coefficient between the rates of return on the two portfolios?

Using Historical Data We’ve seen that portfolio risk and return depend on the means and variances of the component securities, as well as on the covariance between their returns. One way to obtain these inputs is a scenario analysis as in Spreadsheets 6.1–6.4. As we noted in Chapter 5, however, a common alternative approach to produce these inputs is to make use of historical data. In this approach, we use realized returns to estimate mean returns and volatility as well as the tendency for security returns to co-vary. The estimate of the mean return for each security is its average value in the sample period; the estimate of variance is the average value of the squared deviations around the sample average; the estimate of the covariance is the average

2. Suppose that for some reason you are required to invest 50% of your portfolio in bonds and 50% in stocks. a. If the standard deviation of your portfolio is 15%, what must be the correlation coefficient between stock and bond returns? b. What is the expected rate of return on your portfolio? c. Now suppose that the correlation between stock and bond returns is 0.22 but that you are free to choose whatever portfolio proportions you desire. Are you likely to be better or worse off than you were in part (a)?

Let’s return to the data for ABC and XYZ in Example 6.1. Using the spreadsheet estimates of the means and standard deviations obtained from the AVERAGE and STDEV functions, and the estimate of the correlation coefficient we obtained in that example, we can compute the risk-return trade-off for various portfolios formed from ABC and XYZ. Columns E and F in the lower half of the spreadsheet on the following page are calculated from Equations 6.2 and 6.3 respectively, and show the risk-return opportunities. These calculations use the estimates of the stocks’ means in cells B16 and C16, the standard deviations in cells B17 and C17, and the correlation coefficient in cell F10. Examination of column E shows that the portfolio mean starts at XYZ’s mean of 11.97% and moves toward ABC’s mean as we increase the weight of ABC and correspondingly reduce that of XYZ. Examination of the standard deviation in column F shows that diversification reduces the standard deviation until the proportion in ABC increases above 30%; thereafter, standard deviation increases. Hence, the minimum-variance portfolio uses weights of approximately 30% in ABC and 70% in XYZ. The exact proportion in ABC in the minimum-variance portfolio can be computed from the formula shown in Spreadsheet 6.6. Note, however, that achieving a minimum-variance portfolio is not a compelling goal. Investors may well be willing to take on more risk in order to increase expected return. The investment opportunity set offered by stocks ABC and XYZ may be found by graphing the expected return–standard deviation pairs in columns E and F.

6.3 EXAMPLE Using Historical Data to Estimate the Investment Opportunity Set

Concept CHECK

>

3. The following tables present returns on various pairs of stocks in several periods. In part A, we show you a scatter diagram of the returns on the first pair of stocks. Draw (or prepare in Excel) similar scatter diagrams for cases B through E. Match up the diagrams (A–E) to the following list of correlation coefficients by choosing the correlation that best describes the relationship between the returns on the two stocks: ⴝ ⴚ1, 0, 0.2, 0.5, 1.0. (continued) The proportion in bonds that will drive the standard deviation to zero when 1 is:

2

wB

S B S

Compare this formula to the formula in footnote 1 for the variance-minimizing proportions when 0.

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Spreadsheet for Example 6.3

(concluded) B.

% Return

C.

Stock 1 Stock 2 1 2 3 4 5

6.3

% Return Stock 1 Stock 2

1 2 3 4 5

1 2 3 4 5

5 4 3 2 1

D.

% Return

E.

Stock 1 Stock 2 5 1 4 2 3

% Return Stock 1 Stock 2

5 3 3 0 5

5 1 4 2 3

4 3 1 0 5

THE OPTIMAL RISKY PORTFOLIO WITH A RISK-FREE ASSET

Now we can expand the asset allocation problem to include a risk-free asset. Let us continue to use the input data from the bottom of Spreadsheet 6.5, but now assume a realistic correlation coefficient between stocks and bonds of 0.20. Suppose then that we are still confined to the risky bond and stock funds, but now can also invest in risk-free T-bills yielding 5%. Figure 6.5 shows the opportunity set generated from the bond and stock funds. This is the same opportunity set as graphed in Figure 6.4 with BS 0.20. Two possible capital allocation lines (CALs) are drawn from the risk-free rate (rf 5%) to two feasible portfolios. The first possible CAL is drawn through the variance-minimizing portfolio (A), which invests 87.06% in bonds and 12.94% in stocks. Portfolio A’s expected return is 6.52% and its standard deviation is 11.54%. With a T-bill rate (rf) of 5%, the reward-tovariability ratio of portfolio A (which is also the slope of the CAL that combines T-bills with portfolio A) is SA

F I G U R E 6.5

12 11 Expected return (%)

The opportunity set using bonds and stocks and two capital allocation lines

E(rA) rf 6.52 5 0.13 A 11.54

10 Stocks 9 8 7

B

CALB CALA

A Bonds

6 5 4 0

5

10

15 20 25 Standard deviation (%)

30

35

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Now consider the CAL that uses portfolio B instead of A. Portfolio B invests 80% in bonds and 20% in stocks, providing an expected return of 6.80% with a standard deviation of 11.68%. Thus, the reward-to-variability ratio of any portfolio on the CAL of B is 6.80 5 .15 11.68

SB

This is higher than the reward-to-variability ratio of the CAL of the variance-minimizing portfolio A. The difference in the reward-to-variability ratios is SB SA 0.02. This implies that portfolio B provides 2 extra basis points (0.02%) of expected return for every percentage point increase in standard deviation. The higher reward-to-variability ratio of portfolio B means that its capital allocation line is steeper than that of A. Therefore, CALB plots above CALA in Figure 6.5. In other words, combinations of portfolio B and the risk-free asset provide a higher expected return for any level of risk (standard deviation) than combinations of portfolio A and the risk-free asset. Therefore, all risk-averse investors would prefer to form their complete portfolio using the risk-free asset with portfolio B rather than with portfolio A. In this sense, portfolio B dominates A. But why stop at portfolio B? We can continue to ratchet the CAL upward until it reaches the ultimate point of tangency with the investment opportunity set. This must yield the CAL with the highest feasible reward-to-variability ratio. Therefore, the tangency portfolio (O) in Figure 6.6 is the optimal risky portfolio to mix with T-bills, which may be defined as the risky portfolio resulting in the highest possible CAL. We can read the expected return and standard deviation of portfolio O (for “optimal”) off the graph in Figure 6.6 as E(rO) 8.68% O 17.97% which can be identified as the portfolio that invests 32.99% in bonds and 67.01% in stocks.3 We can obtain a numerical solution to this problem using a computer program.

The optimal capital allocation line with bonds, stocks, and T-bills

11 Expected return (%)

The best combination of risky assets to be mixed with safe assets to form the complete portfolio.

F I G U R E 6.6

12 Stocks

10 E(ro) 8.68%

9

O

8 7 6

Bonds

5

σo 17.97%

4 0

5

10

15

20

25

30

Standard deviation (%)

3

The proportion of portfolio O invested in bonds is: wB

optimal risky portfolio

[E(rB) rf]S2 [E(rS) rf]B S BS [E(rB) rf]S2 [E(rS) rf]B2 [E(rB) rf E(rS) rf]B S BS

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F I G U R E 6.7

E(rP)

The complete portfolio CALo 8.68%

O, optimal risky portfolio

7.02% 5%

C, complete portfolio

9.88%

σP

17.97%

The CAL with our optimal portfolio has a slope of SO

8.68 5 .20 17.97

which is the reward-to-variability ratio of portfolio O. This slope exceeds the slope of any other feasible portfolio, as it must if it is to be the slope of the best feasible CAL. In the last chapter we saw that the preferred complete portfolio formed from a risky portfolio and a risk-free asset depends on the investor’s risk aversion. More risk-averse investors will prefer low-risk portfolios despite the lower expected return, while more risk-tolerant investors will choose higher-risk, higher-return portfolios. Both investors, however, will choose portfolio O as their risky portfolio since that portfolio results in the highest return per unit of risk, that is, the steepest capital allocation line. Investors will differ only in their allocation of investment funds between portfolio O and the risk-free asset. Figure 6.7 shows one possible choice for the preferred complete portfolio, C. The investor places 55% of wealth in portfolio O and 45% in Treasury bills. The rate of return and volatility of the portfolio are E(rC) 5 0.55 (8.68 5) 7.02% C 0.55 17.97 9.88% In turn, we found above that portfolio O is formed by mixing the bond fund and stock fund with weights of 32.99% and 67.01%. Therefore, the overall asset allocation of the complete portfolio is as follows: Weight in risk-free asset Weight in bond fund Weight in stock fund Total

45.00% 0.3299 55% 18.14 0.6701 55% 36.86 100.00%

Figure 6.8 depicts the overall asset allocation. The allocation reflects considerations of both efficient diversification (the construction of the optimal risky portfolio, O) and risk aversion (the allocation of funds between the risk-free asset and the risky portfolio O to form the complete portfolio, C).

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F I G U R E 6.8 The composition of the complete portfolio: The solution to the asset allocation problem

Bonds 18.14% T-bills 45% Stocks 36.86%

Portfolio O 55%

4. A universe of securities includes a risky stock (X), a stock index fund (M), and T-bills. The data for the universe are:

X M T-bills

Expected Return

Standard Deviation

15% 10 5

50% 20 0

The correlation coefficient between X and M is ⴚ0.2. a. Draw the opportunity set of securities X and M. b. Find the optimal risky portfolio (O) and its expected return and standard deviation. c. Find the slope of the CAL generated by T-bills and portfolio O. d. Suppose an investor places 2/9 (i.e., 22.22%) of the complete portfolio in the risky portfolio O and the remainder in T-bills. Calculate the composition of the complete portfolio.

6.4

EFFICIENT DIVERSIFICATION WITH MANY RISKY ASSETS

We can extend the two-risky-assets portfolio construction methodology to cover the case of many risky assets and a risk-free asset. First, we offer an overview. As in the two-risky-assets example, the problem has three separate steps. To begin, we identify the best possible or most efficient risk-return combinations available from the universe of risky assets. Next we determine the optimal portfolio of risky assets by finding the portfolio that supports the steepest CAL. Finally, we choose an appropriate complete portfolio based on the investor’s risk aversion by mixing the risk-free asset with the optimal risky portfolio.

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Two-Security Portfolio

The Excel model “Two-Security Portfolio” is based on the asset allocation problem between stocks and bonds that appears in this chapter. You can change correlations, mean returns, and standard deviation of return for any two securities or, as it is used in the text example, any two portfolios. All of the concepts that are covered in this section can be explored using the model. You can learn more about this spreadsheet model by using the interactive version available on our website at www.mhhe.com/bkm.

A 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

B

C

Asset Allocation Analysis: Risk and Return Expected Standard Return Deviation Bonds 6.00% 12.00% Stocks 10.00% 25.00% T-Bill 5.00% 0.00%

Weight Bonds 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

Weight Stocks 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Minimum Variance Portfolio Weight Bonds Weight Stocks Return Risk CAL(MV)

D

Corr. Coeff s,b 0

E

F

Covariance 0

Expected Standard Reward to Return Deviation Variability 6.0000% 12.0000% 0.08333 6.4000% 11.0856% 0.12629 6.8000% 10.8240% 0.16630 7.2000% 11.2610% 0.19536 7.6000% 12.3223% 0.21100 8.0000% 13.8654% 0.21637 8.4000% 15.7493% 0.21588 8.8000% 17.8664% 0.21269 9.2000% 20.1435% 0.20850 9.6000% 22.5320% 0.20415 10.0000% 25.0000% 0.20000 Short Sales No Short Allowed Sales 0.81274 0.81274 0.18726 0.18726 6.7490% 6.7490% 10.8183% 10.8183%

The Efficient Frontier of Risky Assets To get a sense of how additional risky assets can improve the investor’s investment opportunities, look at Figure 6.9. Points A, B, and C represent the expected returns and standard deviations of three stocks. The curve passing through A and B shows the risk-return combinations of all the portfolios that can be formed by combining those two stocks. Similarly, the curve passing through B and C shows all the portfolios that can be formed from those two stocks. Now observe point E on the AB curve and point F on the BC curve. These points represent two

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35 30 Expected return (%)

C F

25 20 B 15 E 10

A

5 0 0

10

20

30

40

Standard deviation (%)

F I G U R E 6.9 Portfolios constructed with three stocks (A, B, and C)

portfolios chosen from the set of AB combinations and BC combinations. The curve that passes through E and F in turn represents all the portfolios that can be constructed from portfolios E and F. Since E and F are themselves constructed from A, B, and C, this curve also may be viewed as depicting some of the portfolios that can be constructed from these three securities. Notice that curve EF extends the investment opportunity set to the northwest, which is the desired direction. Now we can continue to take other points (each representing portfolios) from these three curves and further combine them into new portfolios, thus shifting the opportunity set even farther to the northwest. You can see that this process would work even better with more stocks. Moreover, the efficient frontier, the boundary or “envelope” of all the curves thus developed, will lie quite away from the individual stocks in the northwesterly direction, as shown in Figure 6.10. The analytical technique to derive the efficient frontier of risky assets was developed by Harry Markowitz at the University of Chicago in 1951 and ultimately earned him the Nobel Prize in economics. We will sketch his approach here. First, we determine the risk-return opportunity set. The aim is to construct the northwestern-most portfolios in terms of expected return and standard deviation from the universe of securities. The inputs are the expected returns and standard deviations of each asset in the universe, along with the correlation coefficients between each pair of assets. These data come from security analysis, to be discussed in Part Four. The graph that connects all the northwestern-most portfolios is called the efficient frontier of risky assets. It represents

efficient frontier Graph representing a set of portfolios that maximizes expected return at each level of portfolio risk.

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F I G U R E 6.10 The efficient frontier of risky assets and individual assets

Portfolio expected return E(rP)

Minimum variance portfolio

Efficient frontier of risky assets

Individual assets

σP Portfolio standard deviation

the set of portfolios that offers the highest possible expected rate of return for each level of portfolio standard deviation. These portfolios may be viewed as efficiently diversified. One such frontier is shown in Figure 6.10. Expected return-standard deviation combinations for any individual asset end up inside the efficient frontier, because single-asset portfolios are inefficient—they are not efficiently diversified. When we choose among portfolios on the efficient frontier, we can immediately discard portfolios below the minimum-variance portfolio. These are dominated by portfolios on the upper half of the frontier with equal risk but higher expected returns. Therefore, the real choice is among portfolios on the efficient frontier above the minimum-variance portfolio. Various constraints may preclude a particular investor from choosing portfolios on the efficient frontier, however. If an institution is prohibited by law from taking short positions in any asset, for example, the portfolio manager must add constraints to the computeroptimization program that rule out negative (short) positions. Short sale restrictions are only one possible constraint. Some clients may want to assure a minimum level of expected dividend yield. In this case, data input must include a set of expected dividend yields. The optimization program is made to include a constraint to ensure that the expected portfolio dividend yield will equal or exceed the desired level. Another common constraint forbids investments in companies engaged in “undesirable social activity.” In principle, portfolio managers can tailor an efficient frontier to meet any particular objective. Of course, satisfying constraints carries a price tag. An efficient frontier subject to a number of constraints will offer a lower reward-to-variability ratio than a less constrained one. Clients should be aware of this cost and may want to think twice about constraints that are not mandated by law. Deriving the efficient frontier may be quite difficult conceptually, but computing and graphing it with any number of assets and any set of constraints is quite straightforward. For a small number of assets, and in the absence of constraints beyond the obvious one that

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Efficient Frontier for Many Stocks

Excel spreadsheets can be used to construct an efficient frontier for a group of individual securities or a group of portfolios of securities. The Excel model “Efficient Portfolio” is built using a sample of actual returns on stocks that make up a part of the Dow Jones Industrial Average Index. The efficient frontier is graphed, similar to Figure 6.10, using various possible target returns. The model is built for eight securities and can be easily modified for any group of eight assets. You can learn more about this spreadsheet model by using the interactive version available on our website at www.mhhe.com/bkm.

A 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34

TKR SYM C GE HD INTC JNJ MRK SBC WMT

B

C

Return

D

E

F

G

H

I

S.D. 46.6 37.3 41.8 46.0 24.6 32.6 19.0 41.2

34.8 25.0 31.4 45.9 26.2 31.0 28.1 31.4 Correlation Matrix

C

GE

HD

C GE HD INTC JNJ MRK SBC WMT

1.00 0.54 0.26 0.26 0.35 0.29 0.25 0.40

0.54 1.00 0.58 0.26 0.29 0.20 0.34 0.52

C GE HD INTC JNJ MRK SBC WMT

C 1211.55 468.81 282.30 419.81 320.52 308.52 239.86 440.95

GE 468.81 627.47 451.99 299.86 189.64 158.28 240.96 409.29

INTC

0.35 0.29 -0.02 0.09 1.00 0.58 0.28 0.28

MRK 0.29 0.20 -0.12 0.11 0.58 1.00 0.37 0.12

SBC

0.26 0.26 -0.09 1.00 0.09 0.11 -0.05 -0.02

0.25 0.34 0.15 -0.05 0.28 0.37 1.00 0.16

0.40 0.52 0.58 -0.02 0.28 0.12 0.16 1.00

Covariance Matrix HD INTC 282.30 419.81 451.99 299.86 983.39 -133.54 -133.54 2106.34 -17.19 113.73 -117.25 151.78 133.28 -63.77 566.72 -34.46

JNJ 320.52 189.64 -17.19 113.73 686.88 473.15 203.37 229.77

MRK 308.52 158.28 -117.25 151.78 473.15 961.63 324.53 119.16

SBC 239.86 240.96 133.28 -63.77 203.37 324.53 790.22 140.90

WMT 440.95 409.29 566.72 -34.46 229.77 119.16 140.90 987.13

0.26 0.58 1.00 -0.09 -0.02 -0.12 0.15 0.58

JNJ

WMT

portfolio proportions must sum to 1.0, the efficient frontier can be computed and graphed with a spreadsheet program.

Choosing the Optimal Risky Portfolio The second step of the optimization plan involves the risk-free asset. Using the current riskfree rate, we search for the capital allocation line with the highest reward-to-variability ratio (the steepest slope), as shown in Figures 6.5 and 6.6.

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The CAL formed from the optimal risky portfolio (O) will be tangent to the efficient frontier of risky assets discussed above. This CAL dominates all alternative feasible lines (the dashed lines that are drawn through the frontier). Portfolio O, therefore, is the optimal risky portfolio.

The Preferred Complete Portfolio and the Separation Property

separation property The property that implies portfolio choice can be separated into two independent tasks: (1) determination of the optimal risky portfolio, which is a purely technical problem, and (2) the personal choice of the best mix of the risky portfolio and the risk-free asset.

Concept CHECK

>

factor model Statistical model to measure the firmspecific versus systematic risk of a stock’s rate of return.

Finally, in the third step, the investor chooses the appropriate mix between the optimal risky portfolio (O) and T-bills, exactly as in Figure 6.7. A portfolio manager will offer the same risky portfolio (O) to all clients, no matter what their degrees of risk aversion. Risk aversion comes into play only when clients select their desired point on the CAL. More risk-averse clients will invest more in the risk-free asset and less in the optimal risky portfolio O than less risk-averse clients, but both will use portfolio O as the optimal risky investment vehicle. This result is called a separation property, introduced by James Tobin (1958), the 1983 Nobel Laureate for economics: It implies that portfolio choice can be separated into two independent tasks. The first task, which includes steps one and two, determination of the optimal risky portfolio (O), is purely technical. Given the particular input data, the best risky portfolio is the same for all clients regardless of risk aversion. The second task, construction of the complete portfolio from bills and portfolio O, however, depends on personal preference. Here the client is the decision maker. Of course, the optimal risky portfolio for different clients may vary because of portfolio constraints such as dividend yield requirements, tax considerations, or other client preferences. Our analysis, though, suggests that a few portfolios may be sufficient to serve the demands of a wide range of investors. We see here the theoretical basis of the mutual fund industry. If the optimal portfolio is the same for all clients, professional management is more efficient and less costly. One management firm can serve a number of clients with relatively small incremental administrative costs. The (computerized) optimization technique is the easiest part of portfolio construction. If different managers use different input data to develop different efficient frontiers, they will offer different “optimal” portfolios. Therefore, the real arena of the competition among portfolio managers is in the sophisticated security analysis that underlies their choices. The rule of GIGO (garbage in–garbage out) applies fully to portfolio selection. If the quality of the security analysis is poor, a passive portfolio such as a market index fund can yield better results than an active portfolio tilted toward seemingly favorable securities. 5. Two portfolio managers work for competing investment management houses. Each employs security analysts to prepare input data for the construction of the optimal portfolio. When all is completed, the efficient frontier obtained by manager A dominates that of manager B in that A’s optimal risky portfolio lies northwest of B’s. Is the more attractive efficient frontier asserted by manager A evidence that she really employs better security analysts?

6.5

A SINGLE-FACTOR ASSET MARKET

We started this chapter with the distinction between systematic and firm-specific risk. Systematic risk is largely macroeconomic, affecting all securities, while firm-specific risk factors affect only one particular firm or, perhaps, its industry. Factor models are statistical models designed to estimate these two components of risk for a particular security or portfolio. The

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first to use a factor model to explain the benefits of diversification was another Nobel Prize winner, William S. Sharpe (1963). We will introduce his major work (the capital asset pricing model) in the next chapter. The popularity of factor models is due to their practicality. To construct the efficient frontier from a universe of 100 securities, we would need to estimate 100 expected returns, 100 variances, and 100 99/2 4,950 covariances. And a universe of 100 securities is actually quite small. A universe of 1,000 securities would require estimates of 1,000 999/2 499,500 covariances, as well as 1,000 expected returns and variances. We will see shortly that the assumption that one common factor is responsible for all the covariability of stock returns, with all other variability due to firm-specific factors, dramatically simplifies the analysis. Let us use Ri to denote the excess return on a security, that is, the rate of return in excess of the risk-free rate: Ri ri rf. Then we can express the distinction between macroeconomic and firm-specific factors by decomposing this excess return in some holding period into three components Ri E(Ri ) iM ei

(6.5)

In Equation 6.5, E(Ri) is the expected excess holding-period return (HPR) at the start of the holding period. The next two terms reflect the impact of two sources of uncertainty. M quantifies the market or macroeconomic surprises (with zero meaning that there is “no surprise”) during the holding period. i is the sensitivity of the security to the macroeconomic factor. Finally, ei is the impact of unanticipated firm-specific events. Both M and ei have zero expected values because each represents the impact of unanticipated events, which by definition must average out to zero. The beta ( i) denotes the responsiveness of security i to macroeconomic events; this sensitivity will be different for different securities. As an example of a factor model, suppose that the excess return on Dell stock is expected to be 9% in the coming holding period. However, on average, for every unanticipated increase of 1% in the vitality of the general economy, which we take as the macroeconomic factor M, Dell’s stock return will be enhanced by 1.2%. Dell’s is therefore 1.2. Finally, Dell is affected by firm-specific surprises as well. Therefore, we can write the realized excess return on Dell stock as follows RD 9% 1.2M ei If the economy outperforms expectations by 2%, then we would revise upward our expectations of Dell’s excess return by 1.2 2%, or 2.4%, resulting in a new expected excess return of 11.4%. Finally, the effects of Dell’s firm-specific news during the holding period must be added to arrive at the actual holding-period return on Dell stock. Equation 6.5 describes a factor model for stock returns. This is a simplification of reality; a more realistic decomposition of security returns would require more than one factor in Equation 6.5. We treat this issue in the next chapter, but for now, let us examine the singlefactor case.

Specification of a Single-Index Model of Security Returns A factor model description of security returns is of little use if we cannot specify a way to measure the factor that we say affects security returns. One reasonable approach is to use the rate of return on a broad index of securities, such as the S&P 500, as a proxy for the common macro factor. With this assumption, we can use the excess return on the market index, RM , to measure the direction of macro shocks in any period.

193

excess return Rate of return in excess of the risk-free rate.

beta The sensitivity of a security’s returns to the systematic or market factor.

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Part TWO Portfolio Theory

index model

The index model separates the realized rate of return on a security into macro (systematic) and micro (firm-specific) components much like Equation 6.5. The excess rate of return on each security is the sum of three components:

A model of stock returns using a market index such as the S&P 500 to represent common or systematic risk factors.

Symbol 1. The stock’s excess return if the market factor is neutral, that is, if the market’s excess return is zero. 2. The component of return due to movements in the overall market (as represented by the index RM); i is the security’s responsiveness to the market. 3. The component attributable to unexpected events that are relevant only to this security (firm-specific).

i

iRM ei

The excess return on the stock now can be stated as Ri i i RM ei

(6.6)

Equation 6.6 specifies two sources of security risk: market or systematic risk ( i RM), attributable to the security’s sensitivity (as measured by beta) to movements in the overall market, and firm-specific risk (ei ), which is the part of uncertainty independent of the market factor. Because the firm-specific component of the firm’s return is uncorrelated with the market return, we can write the variance of the excess return of the stock as4 Variance (Ri ) Variance (i i RM ei ) Variance ( i RM) Variance (ei ) 2i M2

2(ei )

Systematic risk Firm-specific risk

(6.7)

Therefore, the total variability of the rate of return of each security depends on two components: 1. The variance attributable to the uncertainty common to the entire market. This systematic risk is attributable to the uncertainty in RM . Notice that the systematic risk of each stock depends on both the volatility in RM (that is, M2 ) and the sensitivity of the stock to fluctuations in RM . That sensitivity is measured by i . 2. The variance attributable to firm-specific risk factors, the effects of which are measured by ei . This is the variance in the part of the stock’s return that is independent of market performance. This single-index model is convenient. It relates security returns to a market index that investors follow. Moreover, as we soon shall see, its usefulness goes beyond mere convenience.

Statistical and Graphical Representation of the Single-Index Model Equation 6.6, Ri i i RM ei , may be interpreted as a single-variable regression equation of Ri on the market excess return RM . The excess return on the security (Ri ) is the dependent variable that is to be explained by the regression. On the right-hand side of the equation are the intercept i; the regression (or slope) coefficient beta, i , multiplying the independent (or explanatory) variable RM; and the security residual (unexplained) return, ei . Notice that because i is a constant, it has no bearing on the variance of Ri .

4

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We can plot this regression relationship as in Figure 6.11, which shows a possible scatter diagram for Dell Computer Corporation’s excess return against the excess return of the market index. The horizontal axis of the scatter diagram measures the explanatory variable, here the market excess return, RM. The vertical axis measures the dependent variable, here Dell’s excess return, RD. Each point on the scatter diagram represents a sample pair of returns (RM, RD) that might be observed for a particular holding period. Point T, for instance, describes a holding period when the excess return was 17% on the market index and 27% on Dell. Regression analysis lets us use the sample of historical returns to estimate a relationship between the dependent variable and the explanatory variable. The regression line in Figure 6.11 is drawn so as to minimize the sum of all the squared deviations around it. Hence, we say the regression line “best fits” the data in the scatter diagram. The line is called the security characteristic line, or SCL. The regression intercept (D) is measured from the origin to the intersection of the regression line with the vertical axis. Any point on the vertical axis represents zero market excess return, so the intercept gives us the expected excess return on Dell during the sample period when market performance was neutral. The intercept in Figure 6.11 is about 4.5%. The slope of the regression line can be measured by dividing the rise of the line by its run. It also is expressed by the number multiplying the explanatory variable, which is called the regression coefficient or the slope coefficient or simply the beta. The regression beta is a natural measure of systematic risk since it measures the typical response of the security return to market fluctuations. The regression line does not represent the actual returns: that is, the points on the scatter diagram almost never lie on the regression line, although the actual returns are used to calculate the regression coefficients. Rather, the line represents average tendencies; it shows the effect of the index return on our expectation of RD. The algebraic representation of the regression line is E(RD RM) D D RM

195

security characteristic line Plot of a security’s excess return as a function of the excess return of the market.

(6.8)

which reads: The expectation of RD given a value of RM equals the intercept plus the slope coefficient times the given value of RM .

Dell’s excess return (%) RD 30

F I G U R E 6.11 Scatter diagram for Dell

T

20 10 αD

RM 10

20

30

40

Market excess return (%)

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Because the regression line represents expectations, and because these expectations may not be realized in any or all of the actual returns (as the scatter diagram shows), the actual security returns also include a residual, the firm-specific surprise, ei. This surprise (at point T, for example) is measured by the vertical distance between the point of the scatter diagram and the regression line. For example, the expected return on Dell, given a market return of 17%, would have been 4.5% 1.4 17% 28.3%. The actual return was only 27%, so point T falls below the regression line by 1.3%. Equation 6.7 shows that the greater the beta of the security, that is, the greater the slope of the regression, the greater the security’s systematic risk ( 2D M2 ), as well as its total variance (D2 ). The average security has a slope coefficient (beta) of 1.0: Because the market is composed of all securities, the typical response to a market movement must be one for one. An “aggressive” investment will have a beta higher than 1.0; that is, the security has aboveaverage market risk.5 In Figure 6.11, Dell’s beta is 1.4. Conversely, securities with betas lower than 1.0 are called defensive. A security may have a negative beta. Its regression line will then slope downward, meaning that, for more favorable macro events (higher RM), we would expect a lower return, and vice versa. The latter means that when the macro economy goes bad (negative RM) and securities with positive beta are expected to have negative excess returns, the negative-beta security will shine. The result is that a negative-beta security has negative systematic risk, that is, it provides a hedge against systematic risk. The dispersion of the scatter of actual returns about the regression line is determined by the residual variance 2(eD), which measures the effects of firm-specific events. The magnitude of firm-specific risk varies across securities. One way to measure the relative importance of systematic risk is to measure the ratio of systematic variance to total variance. 2

Systematic (or explained) variance Total variance

2D 2M

2D 2M 2D

2D 2M 2(eD)

(6.9)

where is the correlation coefficient between RD and RM . Its square measures the ratio of explained variance to total variance, that is, the proportion of total variance that can be attributed to market fluctuations. But if beta is negative, so is the correlation coefficient, an indication that the explanatory and dependent variables are expected to move in opposite directions. At the extreme, when the correlation coefficient is either 1.0 or 1.0, the security return is fully explained by the market return, that is, there are no firm-specific effects. All the points of the scatter diagram will lie exactly on the line. This is called perfect correlation (either positive or negative); the return on the security is perfectly predictable from the market return. A large correlation coefficient (in absolute value terms) means systematic variance dominates the total variance; that is, firm-specific variance is relatively unimportant. When the correlation coefficient is small (in absolute value terms), the market factor plays a relatively unimportant part in explaining the variance of the asset, and firm-specific factors predominate. 5

Note that the average beta of all securities will be 1.0 only when we compute a weighted average of betas (using market values as weights), since the stock market index is value weighted. We know from Chapter 5 that the distribution of securities by market value is not symmetric: There are relatively few large corporations and many more smaller ones. Thus, if you were to take a randomly selected sample of stocks, you should expect smaller companies to dominate. As a result, the simple average of the betas of individual securities, when computed against a value-weighted index such as the S&P 500, will be greater than 1.0, pushed up by the tendency for stocks of low-capitalization companies to have betas greater than 1.0.

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Use the implications of capital market theory to compute security risk premiums. Construct and use the security market line. Take advantage of an arbitrage opportunity with a portfolio that includes mispriced securities. Use arbitrage pricing theory with more than one factor to identify mispriced securities.

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Related Websites

http://www.mhhe.com/edumarketinsight

http://finance.yahoo.com http://moneycentral.msn.com/investor/home.asp http://bloomberg.com http://www.411stocks.com/ http://www.morningstar.com

This site contains information on monthly, weekly, and daily returns that can be used in estimating beta coefficients.

http://www.efficientfrontier.com Here you’ll find information on modern portfolio theory and portfolio allocation.

You can use these sites to assess beta coefficients for individual securities and mutual funds.

he capital asset pricing model, almost always referred to as the CAPM, is a centerpiece of modern financial economics. It was first proposed by William F. Sharpe, who was awarded the 1990 Nobel Prize for economics. The CAPM provides a precise prediction of the relationship we should observe between the risk of an asset and its expected return. This relationship serves two vital functions. First, it provides a benchmark rate of return for evaluating possible investments. For example, a security analyst might want to know whether the expected return she forecasts for a stock is more or less than its “fair” return given its risk. Second, the model helps us make an educated guess as to the expected return on assets that have not yet been traded in the marketplace. For example, how do we price an initial public offering of stock? How will a major new investment project affect the return investors require on a company’s stock? Although the CAPM does not fully withstand empirical tests, it is widely used because of the insight it offers and because its accuracy suffices for many important applications. The exploitation of security mispricing to earn risk-free economic profits is called arbitrage. It typically involves the simultaneous purchase and sale of equivalent securities (often in different markets) in order to profit from discrepancies in their price relationship. The most basic principle of capital market theory is that equilibrium market prices should rule out arbitrage opportunities. If actual security prices allow for arbitrage, the resulting opportunities for profitable trading will lead to strong pressure on security prices that will persist until equilibrium is restored. Only a few investors need be aware of arbitrage opportunities to bring about a large volume of trades, and these trades will bring prices back into alignment. Therefore, no-arbitrage restrictions on security prices are extremely powerful. The implications of no-arbitrage principles for financial economics were first explored by Modigliani and Miller, both Nobel Laureates (1985 and 1990).

T

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TA B L E 7.1 Share prices and market values of Bottom Up (BU) and Top Down (TD)

Price per share ($) Shares outstanding Market value ($ millions)

BU

TD

39.00 5,000,000 195

39.00 4,000,000 156

The Arbitrage Pricing Theory (APT) developed by Stephen Ross uses a no-arbitrage argument to derive the same relationship between expected return and risk as the CAPM. We explore the risk-return relationship using well-diversified portfolios and discuss the similarities and differences between the APT and the CAPM.

7.1

DEMAND FOR STOCKS AND EQUILIBRIUM PRICES

So far we have been concerned with efficient diversification, the optimal risky portfolio, and its risk-return profile. We haven’t had much to say about how expected returns are determined in a competitive securities market. To understand how market equilibrium is formed we must connect the determination of optimal portfolios with security analysis and actual buy/sell transactions of investors. We will show in this section how the quest for efficient diversification leads to a demand schedule for shares. In turn, the supply and demand for shares determine equilibrium prices and expected rates of return. Imagine a simple world with only two corporations: Bottom Up Inc. (BU) and Top Down Inc. (TD). Stock prices and market values are shown in Table 7.1. Investors can also invest in a money market fund (MMF) that yields a risk-free interest rate of 5%. Sigma Fund is a new actively managed mutual fund that has raised $220 million to invest in the stock market. The security analysis staff of Sigma believes that neither BU nor TD will grow in the future and, therefore, each firm will pay level annual dividends for the foreseeable future. This is a useful simplifying assumption because, if a stock is expected to pay a stream of level dividends, the income derived from each share is a perpetuity. The present value of each share—often called the intrinsic value of the share—equals the dividend divided by the appropriate discount rate. A summary of the report of the security analysts appears in Table 7.2. The expected returns in Table 7.2 are based on the assumption that next year’s dividends will conform to Sigma’s forecasts, and share prices will be equal to intrinsic values at yearend. The standard deviations and the correlation coefficient between the two stocks were estimated by Sigma’s security analysts from past returns and assumed to remain at these levels for the coming year. Using these data and assumptions Sigma easily generates the efficient frontier shown in Figure 7.1 and computes the optimal portfolio proportions corresponding to the tangency portfolio. These proportions, combined with the total investment budget, yield the Fund’s buy orders. With a budget of $220 million, Sigma wants a position in BU of $220,000,000 ⫻ .8070 ⫽ $177,540,000, or $177,540,000/39 ⫽ 4,552,308 shares, and a position in TD of $220,000,000 ⫻ .1930 ⫽ $42,460,000, which corresponds to 1,088,718 shares.

Sigma’s Demand for Shares The expected rates of return that Sigma used to derive its demand for shares of BU and TD were computed from the forecast of year-end stock prices and the current prices. If, say, a share of BU could be purchased at a lower price, Sigma’s forecast of the rate of return on BU would be higher. Conversely, if BU shares were selling at a higher price, expected returns would be lower. A new expected return would result in a different optimal portfolio and a different demand for shares.

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TA B L E 7.2 Capital market expectations of Sigma’s portfolio manager and optimal portfolio weights

Expected annual dividend ($/share) Discount rate ⫽ Required return* (%) Expected end-of-year price† ($/share) Current price Expected return (%): Dividend yield (div/price) Capital gain (P1 ⫺ P0)/P0 Total rate of return Standard deviation of rate of return (%) Correlation coefficient between BU and TD () Risk-free rate (%) Optimal portfolio weight‡

BU

TD

6.40 16 40 39 16.41 2.56 18.97 40

3.80 10 38 39 9.74 ⫺2.56 7.18 20 .20 5

.8070

.1930

*Based on assessment of risk. †

Obtained by discounting the dividend perpetuity at the required rate of return.

‡

Using footnote 3 of Chapter 6, we obtain the weight in BU as

wBU ⫽

[E(rBU) ⫺ rf ]2TD ⫺ [E(rTD) ⫺ rf ]BUTD [E(rBU) ⫺ rf ]2TD ⫹ [E(rTD) ⫺ rf ]2BU ⫺ [E(rBU) ⫺ rf ⫹ E(rTD) ⫺ rf ]BUTD

The weight in TD equals 1.0 ⫺ wBU.

F I G U R E 7.1

45 Optimal Portfolio wBU ⫽ 80.70% wTD ⫽ 19.30% Mean ⫽ 16.69% Standard deviation ⫽ 33.27%

40

Expected return (%)

35 30

Sigma’s efficient frontier and optimal portfolio

CAL

Efficient frontier of risky assets

25 20 BU 15 10

Optimal portfolio TD

5 0 0

20

40 60 Standard deviation (%)

80

100

We can think of Sigma’s demand schedule for a stock as the number of shares Sigma would want to hold at different share prices. In our simplified world, producing the demand for BU

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TA B L E 7.3 Calculation of Sigma’s demand for BU shares

Current Price ($)

Capital Gain (%)

Dividend Yield (%)

Expected Return (%)

BU Optimal Proportion

Desired BU Shares

45.0 42.5 40.0 37.5 35.0

⫺11.11 ⫺5.88 0 6.67 14.29

14.22 15.06 16.00 17.07 18.29

3.11 9.18 16.00 23.73 32.57

⫺.4113 .3192 .7011 .9358 1.0947

⫺2,010,582 1,652,482 3,856,053 5,490,247 6,881,225

46

Supply ⫽ 5 million shares

Price per share ($)

44 Sigma demand

42 40

Equilibrium price $40.85 Aggregate (total) demand

Index fund demand

38 36 34 32 ⫺3

⫺1

0

1 3 5 Number of shares (millions)

7

9

11

F I G U R E 7.2 Supply and demand for BU shares

shares is not difficult. First, we revise Table 7.2 to recompute the expected return on BU at different current prices given the forecasted year-end price. Then, for each price and associated expected return, we construct the optimal portfolio and find the implied position in BU. A few samples of these calculations are shown in Table 7.3. The first four columns in Table 7.3 show the expected returns on BU shares given their current price. The optimal proportion (column 5) is calculated using these expected returns. Finally, Sigma’s investment budget, the optimal proportion in BU, and the current price of a BU share determine the desired number of shares. Note that we compute the demand for BU shares given the price and expected return for TD. This means that the entire demand schedule must be revised whenever the price and expected return on TD are changed.

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40

Price per share ($)

Supply ⫽ 4 million shares

Aggregate demand

40 Sigma demand

39

Equilibrium price $38.41

39 Index fund demand

38 38 37 ⫺3

⫺2

⫺1

0

1

2

3

4

Number of shares (millions)

F I G U R E 7.3 Supply and demand for TD shares

Sigma’s demand curve for BU stock is given by the Desired Shares column in Table 7.3 and is plotted in Figure 7.2. Notice that the demand curve for the stock slopes downward. When BU’s stock price falls, Sigma will desire more shares for two reasons: (1) an income effect—at a lower price Sigma can purchase more shares with the same budget—and (2) a substitution effect—the increased expected return at the lower price will make BU shares more attractive relative to TD shares. Notice that one can desire a negative number of shares, that is, a short position. If the stock price is high enough, its expected return will be so low that the desire to sell will overwhelm diversification motives and investors will want to take a short position. Figure 7.2 shows that when the price exceeds $44, Sigma wants a short position in BU. The demand curve for BU shares assumes that the price of TD remains constant. A similar demand curve can be constructed for TD shares given a price for BU shares. As before, we would generate the demand for TD shares by revising Table 7.2 for various current prices of TD, leaving the price of BU unchanged. We use the revised expected returns to calculate the optimal portfolio for each possible price of TD, ultimately obtaining the demand curve shown in Figure 7.3.

Index Funds’ Demands for Stock We will see shortly that index funds play an important role in portfolio selection, so let’s see how an index fund would derive its demand for shares. Suppose that $130 million of investor funds in our hypothesized economy are given to an index fund—named Index—to manage. What will it do? Index is looking for a portfolio that will mimic the market. Suppose current prices and market values are as in Table 7.1. Then the required proportions to mimic the market portfolio are: wBU ⫽ 195/(195 ⫹ 156) ⫽ .5556 (55.56%); wTD ⫽ 1 ⫺ .5556 ⫽ .4444 (44.44%)

5

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With $130 million to invest, Index will place .5556 ⫻ $130 million ⫽ $72.22 million in BU shares. Table 7.4 shows a few other points on Index’s demand curve for BU shares. The second column of the table shows the proportion of BU in total stock market value at each assumed price. In our two-stock example, this is BU’s value as a fraction of the combined value of BU and TD. The third column is Index’s desired dollar investment in BU and the last column shows shares demanded. The bold row corresponds to the case we analyzed in Table 7.1, for which BU is selling at $39. Index’s demand curve for BU shares is plotted in Figure 7.2 next to Sigma’s demand, and in Figure 7.3 for TD shares. Index’s demand is smaller than Sigma’s because its budget is smaller. Moreover, the demand curve of the index fund is very steep, or “inelastic,” that is, demand hardly responds to price changes. This is because an index fund’s demand for shares does not respond to expected returns. Index funds seek only to replicate market proportions. As the stock price goes up, so does its proportion in the market. This leads the index fund to invest more in the stock. Nevertheless, because each share costs more, the fund will desire fewer shares.

Equilibrium Prices and the Capital Asset Pricing Model Market prices are determined by supply and demand. At any one time, the supply of shares of a stock is fixed, so supply is vertical at 5,000,000 shares of BU in Figure 7.2 and 4,000,000 shares of TD in Figure 7.3. Market demand is obtained by “horizontal aggregation,” that is, for each price we add up the quantity demanded by all investors. You can examine the horizontal aggregation of the demand curves of Sigma and Index in Figures 7.2 and 7.3. The equilibrium prices are at the intersection of supply and demand. However, the prices shown in Figures 7.2 and 7.3 will likely not persist for more than an instant. The reason is that the equilibrium price of BU ($40.85) was generated by demand curves derived by assuming that the price of TD was $39. Similarly, the equilibrium price of TD ($38.41) is an equilibrium price only when BU is at $39, which also is not the case. A full equilibrium would require that the demand curves derived for each stock be consistent with the actual prices of all other stocks. Thus, our model is only a beginning. But it does illustrate the important link between security analysis and the process by which portfolio demands, market prices, and expected returns are jointly determined. In the next section we will introduce the capital asset pricing model, which treats the problem of finding a set of mutually consistent equilibrium prices and expected rates of return across all stocks. When we argue there that market expected returns adjust to demand pressures, you will understand the process that underlies this adjustment.

TA B L E 7.4 Calculation of index demand for BU shares

Current Price

BU Market-Value Proportion

Dollar Investment* ($ million)

Shares Desired

$45.00 42.50 40.00 39.00 37.50 35.00

.5906 .5767 .5618 .5556 .5459 .5287

76.772 74.966 73.034 72.222 70.961 68.731

1,706,037 1,763,908 1,825,843 1,851,852 1,892,285 1,963,746

*Dollar investment ⫽ BU proportion ⫻ $130 million.

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221

THE CAPITAL ASSET PRICING MODEL

The capital asset pricing model, or CAPM, was developed by Treynor, Sharpe, Lintner, and Mossin in the early 1960s, and further refined later. The model predicts the relationship between the risk and equilibrium expected returns on risky assets. We will approach the CAPM in a simplified setting. Thinking about an admittedly unrealistic world allows a relatively easy leap to the solution. With this accomplished, we can add complexity to the environment, one step at a time, and see how the theory must be amended. This process allows us to develop a reasonably realistic and comprehensible model. A number of simplifying assumptions lead to the basic version of the CAPM. The fundamental idea is that individuals are as alike as possible, with the notable exceptions of initial wealth and risk aversion. The list of assumptions that describes the necessary conformity of investors follows:

capital asset pricing model (CAPM) A model that relates the required rate of return for a security to its risk as measured by beta.

1. Investors cannot affect prices by their individual trades. This means that there are many investors, each with an endowment of wealth that is small compared with the total endowment of all investors. This assumption is analogous to the perfect competition assumption of microeconomics. 2. All investors plan for one identical holding period. 3. Investors form portfolios from a universe of publicly traded financial assets, such as stocks and bonds, and have access to unlimited risk-free borrowing or lending opportunities. 4. Investors pay neither taxes on returns nor transaction costs (commissions and service charges) on trades in securities. In such a simple world, investors will not care about the difference between returns from capital gains and those from dividends. 5. All investors attempt to construct efficient frontier portfolios; that is, they are rational mean-variance optimizers. 6. All investors analyze securities in the same way and share the same economic view of the world. Hence, they all end with identical estimates of the probability distribution of future cash flows from investing in the available securities. This means that, given a set of security prices and the risk-free interest rate, all investors use the same expected returns, standard deviations, and correlations to generate the efficient frontier and the unique optimal risky portfolio. This assumption is called homogeneous expectations. Obviously, these assumptions ignore many real-world complexities. However, they lead to some powerful insights into the nature of equilibrium in security markets. Given these assumptions, we summarize the equilibrium that will prevail in this hypothetical world of securities and investors. We elaborate on these implications in the following sections. 1. All investors will choose to hold the market portfolio (M), which includes all assets of the security universe. For simplicity, we shall refer to all assets as stocks. The proportion of each stock in the market portfolio equals the market value of the stock (price per share times the number of shares outstanding) divided by the total market value of all stocks. 2. The market portfolio will be on the efficient frontier. Moreover, it will be the optimal risky portfolio, the tangency point of the capital allocation line (CAL) to the efficient frontier. As a result, the capital market line (CML), the line from the risk-free rate through the market portfolio, M, is also the best attainable capital allocation line. All investors hold M as their optimal risky portfolio, differing only in the amount invested in it as compared to investment in the risk-free asset.

market portfolio The portfolio for which each security is held in proportion to its market value.

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3. The risk premium on the market portfolio will be proportional to the variance of the market portfolio and investors’ typical degree of risk aversion. Mathematically E(rM) ⫺ rf ⫽ A*M2

(7.1)

where M is the standard deviation of the return on the market portfolio and A* is a scale factor representing the degree of risk aversion of the average investor. 4. The risk premium on individual assets will be proportional to the risk premium on the market portfolio (M) and to the beta coefficient of the security on the market portfolio. This implies that the rate of return on the market portfolio is the single factor of the security market. The beta measures the extent to which returns on the stock respond to the returns of the market portfolio. Formally, beta is the regression (slope) coefficient of the security return on the market portfolio return, representing the sensitivity of the stock return to fluctuations in the overall security market.

Why All Investors Would Hold the Market Portfolio Given all our assumptions, it is easy to see why all investors hold identical risky portfolios. If all investors use identical mean-variance analysis (assumption 5), apply it to the same universe of securities (assumption 3), with an identical time horizon (assumption 2), use the same security analysis (assumption 6), and experience identical tax consequences (assumption 4), they all must arrive at the same determination of the optimal risky portfolio. That is, they all derive identical efficient frontiers and find the same tangency portfolio for the capital allocation line (CAL) from T-bills (the risk-free rate, with zero standard deviation) to that frontier, as in Figure 7.4. With everyone choosing to hold the same risky portfolio, stocks will be represented in the aggregate risky portfolio in the same proportion as they are in each investor’s (common) risky portfolio. If GM represents 1% in each common risky portfolio, GM will be 1% of the aggregate risky portfolio. This in fact is the market portfolio since the market is no more than the aggregate of all individual portfolios. Because each investor uses the market portfolio for the optimal risky portfolio, the CAL in this case is called the capital market line, or CML, as in Figure 7.4.

F I G U R E 7.4

E(r)

The efficient frontier and the capital market line CML E(rM)

M

rf

σM

σ

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Suppose the optimal portfolio of our investors does not include the stock of some company, say, Delta Air Lines. When no investor is willing to hold Delta stock, the demand is zero, and the stock price will take a free fall. As Delta stock gets progressively cheaper, it begins to look more attractive, while all other stocks look (relatively) less attractive. Ultimately, Delta will reach a price at which it is desirable to include it in the optimal stock portfolio, and investors will buy. This price adjustment process guarantees that all stocks will be included in the optimal portfolio. The only issue is the price. At a given price level, investors will be willing to buy a stock; at another price, they will not. The bottom line is this: If all investors hold an identical risky portfolio, this portfolio must be the market portfolio.

The Passive Strategy Is Efficient A passive strategy, using the CML as the optimal CAL, is a powerful alternative to an active strategy. The market portfolio proportions are a result of profit-oriented “buy” and “sell” orders that cease only when there is no more profit to be made. And in the simple world of the CAPM, all investors use precious resources in security analysis. A passive investor who takes a free ride by simply investing in the market portfolio benefits from the efficiency of that portfolio. In fact, an active investor who chooses any other portfolio will end on a CAL that is less efficient than the CML used by passive investors. We sometimes call this result a mutual fund theorem because it implies that only one mutual fund of risky assets—the market portfolio—is sufficient to satisfy the investment demands of all investors. The mutual fund theorem is another incarnation of the separation property discussed in Chapter 6. Assuming all investors choose to hold a market index mutual fund, we can separate portfolio selection into two components: (1) a technical side, in which an efficient mutual fund is created by professional management; and (2) a personal side, in which an investor’s risk aversion determines the allocation of the complete portfolio between the mutual fund and the risk-free asset. Here, all investors agree that the mutual fund they would like to hold is the market portfolio. While different investment managers do create risky portfolios that differ from the market index, we attribute this in part to the use of different estimates of risk and expected return. Still, a passive investor may view the market index as a reasonable first approximation to an efficient risky portfolio. The logical inconsistency of the CAPM is this: If a passive strategy is costless and efficient, why would anyone follow an active strategy? But if no one does any security analysis, what brings about the efficiency of the market portfolio? We have acknowledged from the outset that the CAPM simplifies the real world in its search for a tractable solution. Its applicability to the real world depends on whether its predictions are accurate enough. The model’s use is some indication that its predictions are reasonable. We discuss this issue in Section 7.4 and in greater depth in Chapter 8. 1. If only some investors perform security analysis while all others hold the market portfolio (M), would the CML still be the efficient CAL for investors who do not engage in security analysis? Explain.

The Risk Premium of the Market Portfolio In Chapters 5 and 6 we showed how individual investors decide how much to invest in the risky portfolio when they can include a risk-free asset in the investment budget. Returning now to the decision of how much to invest in the market portfolio M and how much in the risk-free asset, what can we deduce about the equilibrium risk premium of portfolio M?

mutual fund theorem States that all investors desire the same portfolio of risky assets and can be satisfied by a single mutual fund composed of that portfolio.

E(rM) ⫽ rf ⫹ Equilibrium risk premium ⫽ 0.05 ⫹ 0.08 ⫽ 0.13 ⫽ 13% If investors were more risk averse, it would take a higher risk premium to induce them to hold shares. For example, if the average degree of risk aversion were 3, the market risk premium would be 3 ⫻ 0.202 ⫽ 0.12, or 12%, and the expected return would be 17%.

2. Historical data for the S&P 500 index show an average excess return over Treasury bills of about 8.5% with standard deviation of about 20%. To the extent that these averages approximate investor expectations for the sample period, what must have been the coefficient of risk aversion of the average investor? If the coefficient of risk aversion were 3.5, what risk premium would have been consistent with the market’s historical standard deviation?

Expected Returns on Individual Securities The CAPM is built on the insight that the appropriate risk premium on an asset will be determined by its contribution to the risk of investors’ overall portfolios. Portfolio risk is what matters to investors, and portfolio risk is what governs the risk premiums they demand. We know that nonsystematic risk can be reduced to an arbitrarily low level through diversification (Chapter 6); therefore, investors do not require a risk premium as compensation for bearing nonsystematic risk. They need to be compensated only for bearing systematic risk, which cannot be diversified. We know also that the contribution of a single security to the risk of a large diversified portfolio depends only on the systematic risk of the security as measured by its beta.2 Therefore, it should not be surprising that the risk premium of an asset is proportional to its beta; for example, if you double a security’s systematic risk, you must double its risk premium for investors still to be willing to hold the security. Thus, the ratio of risk premium to beta should be the same for any two securities or portfolios. 1

To use Equation 7.1, we must express returns in decimal form rather than as percentages. See Section 6.5. This is literally true with a sufficient number of securities so that all nonsystematic risk is diversified away. In a market as diversified as the U.S. stock market, this would be true for all practical purposes. 2

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For example, if we were to compare the ratio of risk premium to systematic risk for the market portfolio, which has a beta of 1.0, with the corresponding ratio for Dell stock, we would conclude that E(rM) ⫺ rf E(rD) ⫺ rf ⫽ 1 D Rearranging this relationship results in the CAPM’s expected return–beta relationship E(rD) ⫽ rf ⫹ D [E(rM) ⫺ rf]

(7.2)

In words, the rate of return on any asset exceeds the risk-free rate by a risk premium equal to the asset’s systematic risk measure (its beta) times the risk premium of the (benchmark) market portfolio. This expected return–beta relationship is the most familiar expression of the CAPM. The expected return–beta relationship of the CAPM makes a powerful economic statement. It implies, for example, that a security with a high variance but a relatively low beta of 0.5 will carry one-third the risk premium of a low-variance security with a beta of 1.5. Thus, Equation 7.2 quantifies the conclusion we reached in Chapter 6 that only systematic risk matters to investors who can diversify and that systematic risk is measured by the beta of the security.

Suppose the risk premium of the market portfolio is 9%, and we estimate the beta of Dell as D ⫽ 1.3. The risk premium predicted for the stock is therefore 1.3 times the market risk premium, or 1.3 ⫻ 9% ⫽ 11.7%. The expected rate of return on Dell is the risk-free rate plus the risk premium. For example, if the T-bill rate were 5%, the expected rate of return would be 5% ⫹ 11.7% ⫽ 16.7%, or using Equation 7.2 directly, E(rD) ⫽ rf ⫹ D[Market risk premium] ⫽ 5% ⫹ 1.3 ⫻ 9% ⫽ 16.7% If the estimate of the beta of Dell were only 1.2, the required risk premium for Dell would fall to 10.8%. Similarly, if the market risk premium were only 8% and D ⫽ 1.3, Dell’s risk premium would be only 10.4%.

The fact that few real-life investors actually hold the market portfolio does not necessarily invalidate the CAPM. Recall from Chapter 6 that reasonably well-diversified portfolios shed (for practical purposes) firm-specific risk and are subject only to systematic or market risk. Even if one does not hold the precise market portfolio, a well-diversified portfolio will be so highly correlated with the market that a stock’s beta relative to the market still will be a useful risk measure. In fact, several researchers have shown that modified versions of the CAPM will hold despite differences among individuals that may cause them to hold different portfolios. A study by Brennan (1970) examines the impact of differences in investors’ personal tax rates on market equilibrium. Another study by Mayers (1972) looks at the impact of nontraded assets such as human capital (earning power). Both find that while the market portfolio is no longer each investor’s optimal risky portfolio, a modified version of the expected return–beta relationship still holds. If the expected return–beta relationship holds for any individual asset, it must hold for any combination of assets. The beta of a portfolio is simply the weighted average of the betas of the stocks in the portfolio, using as weights the portfolio proportions. Thus, beta also predicts the portfolio’s risk premium in accordance with Equation 7.2.

expected return–beta relationship Implication of the CAPM that security risk premiums (expected excess returns) will be proportional to beta.

EXAMPLE 7.2 Expected Returns and Risk Premiums

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Consider the following portfolio:

7.3 EXAMPLE Portfolio Beta and Risk Premium

Asset

Beta

Risk Premium

Portfolio Weight

Microsoft Con Edison Gold

1.2 0.8 0.0

9.0% 6.0 0.0

0.5 0.3 0.2

Portfolio

0.84

?

1.0

If the market risk premium is 7.5%, the CAPM predicts that the risk premium on each stock is its beta times 7.5%, and the risk premium on the portfolio is 0.84 ⫻ 7.5% ⫽ 6.3%. This is the same result that is obtained by taking the weighted average of the risk premiums of the individual stocks. (Verify this for yourself.)

A word of caution: We often hear that well-managed firms will provide high rates of return. We agree this is true if one measures the firm’s return on investments in plant and equipment. The CAPM, however, predicts returns on investments in the securities of the firm. Say that everyone knows a firm is well run. Its stock price should, therefore, be bid up, and returns to stockholders who buy at those high prices will not be extreme. Security prices reflect public information about a firm’s prospects, but only the risk of the company (as measured by beta in the context of the CAPM) should affect expected returns. In a rational market, investors receive high expected returns only if they are willing to bear risk.

Concept CHECK

>

3. Suppose the risk premium on the market portfolio is estimated at 8% with a standard deviation of 22%. What is the risk premium on a portfolio invested 25% in GM with a beta of 1.15 and 75% in Ford with a beta of 1.25?

The Security Market Line

security market line (SML) Graphical representation of the expected return–beta relationship of the CAPM.

We can view the expected return–beta relationship as a reward-risk equation. The beta of a security is the appropriate measure of its risk because beta is proportional to the risk the security contributes to the optimal risky portfolio. Risk-averse investors measure the risk of the optimal risky portfolio by its standard deviation. In this world, we would expect the reward, or the risk premium on individual assets, to depend on the risk an individual asset contributes to the overall portfolio. Because the beta of a stock measures the stock’s contribution to the standard deviation of the market portfolio, we expect the required risk premium to be a function of beta. The CAPM confirms this intuition, stating further that the security’s risk premium is directly proportional to both the beta and the risk premium of the market portfolio; that is, the risk premium equals [E(rM ) ⫺ rf ]. The expected return–beta relationship is graphed as the security market line (SML) in Figure 7.5. Its slope is the risk premium of the market portfolio. At the point where  ⫽ 1.0 (which is the beta of the market portfolio) on the horizontal axis, we can read off the vertical axis the expected return on the market portfolio. It is useful to compare the security market line to the capital market line. The CML graphs the risk premiums of efficient portfolios (that is, complete portfolios made up of the risky market portfolio and the risk-free asset) as a function of portfolio standard deviation. This is appropriate because standard deviation is a valid measure of risk for portfolios that are candidates for an investor’s complete (overall) portfolio.

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F I G U R E 7.5

E(r) (%)

The security market line and a positivealpha stock

SML

Stock

17 15.6 14

α M

6

1.0 1.2

β

The SML, in contrast, graphs individual asset risk premiums as a function of asset risk. The relevant measure of risk for individual assets (which are held as parts of a well-diversified portfolio) is not the asset’s standard deviation; it is, instead, the contribution of the asset to the portfolio standard deviation as measured by the asset’s beta. The SML is valid both for portfolios and individual assets. The security market line provides a benchmark for evaluation of investment performance. Given the risk of an investment as measured by its beta, the SML provides the required rate of return that will compensate investors for the risk of that investment, as well as for the time value of money. Because the security market line is the graphical representation of the expected return–beta relationship, “fairly priced” assets plot exactly on the SML. The expected returns of such assets are commensurate with their risk. Whenever the CAPM holds, all securities must lie on the SML in market equilibrium. Underpriced stocks plot above the SML: Given their betas, their expected returns are greater than is indicated by the CAPM. Overpriced stocks plot below the SML. The difference between the fair and actually expected rate of return on a stock is called the stock’s alpha, denoted ␣. Suppose the return on the market is expected to be 14%, a stock has a beta of 1.2, and the T-bill rate is 6%. The SML would predict an expected return on the stock of E(r) ⫽ rf ⫹ [E(rM) ⫺ rf ] ⫽ 6 ⫹ 1.2 (14 ⫺ 6) ⫽ 15.6% If one believes the stock will provide instead a return of 17%, its implied alpha would be 1.4%, as shown in Figure 7.5.

Applications of the CAPM One place the CAPM may be used is in the investment management industry. Suppose the SML is taken as a benchmark to assess the fair expected return on a risky asset. Then an analyst calculates the return he or she actually expects. Notice that we depart here from the

alpha The abnormal rate of return on a security in excess of what would be predicted by an equilibrium model such as the CAPM.

EXAMPLE 7.4 The Alpha of a Security

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simple CAPM world in that some investors apply their own analysis to derive an “input list” that may differ from their competitors’. If a stock is perceived to be a good buy, or underpriced, it will provide a positive alpha, that is, an expected return in excess of the fair return stipulated by the SML. The CAPM also is useful in capital budgeting decisions. If a firm is considering a new project, the CAPM can provide the return the project needs to yield to be acceptable to investors. Managers can use the CAPM to obtain this cutoff internal rate of return (IRR) or “hurdle rate” for the project.

7.5 EXAMPLE The CAPM and Capital Budgeting

Suppose Silverado Springs Inc. is considering a new spring-water bottling plant. The business plan forecasts an internal rate of return of 14% on the investment. Research shows the beta of similar products is 1.3. Thus, if the risk-free rate is 4%, and the market risk premium is estimated at 8%, the hurdle rate for the project should be 4 ⫹ 1.3 ⫻ 8 ⫽ 14.4%. Because the IRR is less than the risk-adjusted discount or hurdle rate, the project has a negative net present value and ought to be rejected.

Yet another use of the CAPM is in utility rate-making cases. Here the issue is the rate of return a regulated utility should be allowed to earn on its investment in plant and equipment.

7.6 EXAMPLE The CAPM and Regulation

Concept CHECK

>

Suppose equityholders’ investment in the firm is $100 million, and the beta of the equity is 0.6. If the T-bill rate is 6%, and the market risk premium is 8%, then a fair annual profit will be 6 ⫹ (0.6 ⫻ 8) ⫽ 10.8% of $100 million, or $10.8 million. Since regulators accept the CAPM, they will allow the utility to set prices at a level expected to generate these profits.

4. a. Stock XYZ has an expected return of 12% and risk of  ⴝ 1.0. Stock ABC is expected to return 13% with a beta of 1.5. The market’s expected return is 11% and rf ⴝ 5%. According to the CAPM, which stock is a better buy? What is the alpha of each stock? Plot the SML and the two stocks and show the alphas of each on the graph. b. The risk-free rate is 8% and the expected return on the market portfolio is 16%. A firm considers a project with an estimated beta of 1.3. What is the required rate of return on the project? If the IRR of the project is 19%, what is the project alpha?

7.3

THE CAPM AND INDEX MODELS

The CAPM has two limitations: It relies on the theoretical market portfolio, which includes all assets (such as real estate, foreign stocks, etc.), and it deals with expected as opposed to actual returns. To implement the CAPM, we cast it in the form of an index model and use realized, not expected, returns. An index model uses actual portfolios, such as the S&P 500, rather than the theoretical market portfolio to represent the relevant systematic factors in the economy. The important advantage of index models is that the composition and rate of return of the index is easily measured and unambiguous.

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In contrast to an index model, the CAPM revolves around the “market portfolio.” However, because many assets are not traded, investors would not have full access to the market portfolio even if they could exactly identify it. Thus, the theory behind the CAPM rests on a shaky real-world foundation. But, as in all science, a theory may be viewed as legitimate if its predictions approximate real-world outcomes with a sufficient degree of accuracy. In particular, the reliance on the market portfolio shouldn’t faze us if we can verify that the predictions of the CAPM are sufficiently accurate when the index portfolio is substituted for the market. We can start with one central prediction of the CAPM: The market portfolio is meanvariance efficient. An index model can be used to test this hypothesis by verifying that an index chosen to be representative of the full market is a mean-variance efficient portfolio. Another aspect of the CAPM is that it predicts relationships among expected returns, while all we can observe are realized (historical) holding-period returns; actual returns in a particular holding period seldom, if ever, match our initial expectations. To test the mean-variance efficiency of an index portfolio, we would have to show that the reward-to-variability ratio of the index is not surpassed by any other portfolio. The reward-to-variability ratio, however, is set in terms of expectations, and we can measure it only in terms of realizations.

The Index Model, Realized Returns, and the Expected Return–Beta Relationship To move from a model cast in expectations to a realized-return framework, we start with a form of the single-index regression equation in realized excess returns, similar to that of Equation 6.6 in Chapter 6: ri ⫺ rf ⫽ ␣i ⫹ i (rM ⫺ rf ) ⫹ ei

(7.3)

where ri is the holding-period return (HPR) on asset i, and ␣i and i are the intercept and slope of the line that relates asset i’s realized excess return to the realized excess return of the index. We denote the index return by rM to emphasize that the index portfolio is proxying for the market. The ei measures firm-specific effects during the holding period; it is the deviation of security i’s realized HPR from the regression line, that is, the deviation from the forecast that accounts for the index’s HPR. We set the relationship in terms of excess returns (over the riskfree rate, rf ), for consistency with the CAPM’s logic of risk premiums. Given that the CAPM is a statement about the expectation of asset returns, we look at the expected return of security i predicted by Equation 7.3. Recall that the expectation of ei is zero (the firm-specific surprise is expected to average zero over time), so the relationship expressed in terms of expectations is E(ri) ⫺ rf ⫽ ␣i ⫹ i [E(rM ) ⫺ rf ]

(7.4)

Comparing this relationship to the expected return–beta relationship (Equation 7.2) of the CAPM reveals that the CAPM predicts ␣i ⫽ 0. Thus, we have converted the CAPM prediction about unobserved expectations of security returns relative to an unobserved market portfolio into a prediction about the intercept in a regression of observed variables: realized excess returns of a security relative to those of a specified index. Operationalizing the CAPM in the form of an index model has a drawback, however. If intercepts of regressions of returns on an index differ substantially from zero, you will not be able to tell whether it is because you chose a bad index to proxy for the market or because the theory is not useful. In actuality, few instances of persistent, positive significant alpha values have been identified; these will be discussed in Chapter 8. Among these are: (1) small versus large stocks; (2) stocks of companies that have recently announced unexpectedly good earnings; (3) stocks

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with high ratios of book value to market value; and (4) stocks that have experienced recent sharp price declines. In general, however, future alphas are practically impossible to predict from past values. The result is that index models are widely used to operationalize capital asset pricing theory.

Estimating the Index Model Equation 7.3 also suggests how we might go about actually measuring market and firm-specific risk. Suppose that we observe the excess return on the market index and a specific asset over a number of holding periods. We use as an example monthly excess returns on the S&P 500 index and GM stock for a particular year. We can summarize the results for a sample period in a scatter diagram, as illustrated in Figure 7.6. The horizontal axis in Figure 7.6 measures the excess return (over the risk-free rate) on the market index; the vertical axis measures the excess return on the asset in question (GM stock in our example). A pair of excess returns (one for the market index, one for GM stock) over a holding period constitutes one point on this scatter diagram. The points are numbered 1 through 12, representing excess returns for the S&P 500 and GM for each month from January through December. The single-index model states that the relationship between the excess returns on GM and the S&P 500 is given by RGMt ⫽ ␣GM ⫹ GMRMt ⫹ eGMt We have noted the resemblance of this relationship to a regression equation. In a single-variable linear regression equation, the dependent variable plots around a straight line with an intercept ␣ and a slope . The deviations from the line, ei , are assumed to

F I G U R E 7.6

8

Characteristic line for GM

7

5 11

6 1

Excess rate of return on GM stock (%)

5 4 3

12

2 1 6

0 –1

10

9

–2

7

–3 –4

2

8

–5 –6 –7 –8 –9 –5

4 3 –3 –1 0 1 3 5 7 Excess rate of return on the market index (%)

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be mutually independent and independent of the right-hand side variable. Because these assumptions are identical to those of the index model, we can look at the index model as a regression model. The sensitivity of GM to the market, measured by GM, is the slope of the regression line. The intercept of the regression line is ␣ (which represents the average firmspecific return), and deviations of particular observations from the regression line are denoted e. These residuals are the differences between the actual stock return and the return that would be predicted from the regression equation describing the usual relationship between the stock and the market; therefore, they measure the impact of firm-specific events during the particular month. The parameters of interest, ␣, , and Var(e), can be estimated using standard regression techniques. Estimating the regression equation of the single-index model gives us the security characteristic line (SCL), which is plotted in Figure 7.6. (The regression results and raw data appear in Table 7.5.) The SCL is a plot of the typical excess return on a security over the riskfree rate as a function of the excess return on the market. This sample of 12 monthly holding-period returns is, of course, too small to yield reliable statistics. We use it only for demonstration. For this sample period, we find that the beta coefficient of GM stock, as estimated by the slope of the regression line, is 1.136, and that the intercept for this SCL is ⫺2.59% per month. For each month, our estimate of the residual, e, which is the deviation of GM’s excess return from the prediction of the SCL, equals

security characteristic line (SCL) A plot of a security’s expected excess return over the riskfree rate as a function of the excess return on the market.

Residual ⫽ Actual ⫺ Predicted return eGMt ⫽ RGMt ⫺ (GMRMt ⫹ ␣GM)

TA B L E 7.5 Characteristic line for GM stock

Month January February March April May June July August September October November December Mean Standard deviation Regression results

GM Return

Market Return

Monthly T-Bill Rate

Excess GM Return

Excess Market Return

6.06 ⫺2.86 ⫺8.17 ⫺7.36 7.76 0.52 ⫺1.74 ⫺3.00 ⫺0.56 ⫺0.37 6.93 3.08

7.89 1.51 0.23 ⫺0.29 5.58 1.73 ⫺0.21 ⫺0.36 ⫺3.58 4.62 6.85 4.55

0.65 0.58 0.62 0.72 0.66 0.55 0.62 0.55 0.60 0.65 0.61 0.65

5.41 ⫺3.44 ⫺8.79 ⫺8.08 7.10 ⫺0.03 ⫺2.36 ⫺3.55 ⫺1.16 ⫺1.02 6.32 2.43

7.24 0.93 ⫺0.39 ⫺1.01 4.92 1.18 ⫺0.83 ⫺0.91 ⫺4.18 3.97 6.24 3.90

0.02 5.19

2.38 3.48

0.62 0.05

⫺0.60 5.19

1.76 3.46

rGM ⫺ rf ⫽ ␣ ⫹ (rM ⫺ rf)

␣ Estimated coefficient ⫺2.591 Standard error of estimate (1.59) Variance of residuals ⫽ 12.585 Standard deviation of residuals ⫽ 3.548 R-SQR ⫽ 0.575

 1.136 (0.309)

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TA B L E 7.6

A. Market index Expected excess return over T-bill rate, E(RM) ⫽ 8% Standard deviation of excess return, (RM) ⫽ 20% B. Individual stocks

True parameters of securities

Stock A Stock B

Beta

Standard Deviation of Residual, (e)

Total Standard Deviation of Returns*

1.30 0.70

54.07% 37.47

60% 40

*Standard deviation ⫽ [2M2 ⫹ 2(e)]1/2 Stock A: [1.32 ⫻ 202 ⫹ 54.072]1/2 ⫽ 60% Stock B: [0.72 ⫻ 202 ⫹ 37.472]1/2 ⫽ 40%

C. T-bills Average value in sample period ⫽ 5% Month-to-month variation results in a standard deviation across months of 1.5%

These residuals are estimates of the monthly unexpected firm-specific component of the rate of return on GM stock. Hence we can estimate the firm-specific variance by3 2(eGM) ⫽

1 12 2 兺 et ⫽ 12.60 10 t ⫽ 1

Therefore, the standard deviation of the firm-specific component of GM’s return, (eGM), equals 3.55% per month.

The CAPM and the Index Model We have introduced the CAPM and shown how the model can be made operational and how beta can be estimated with the additional simplification of the index model of security returns. Of course, when we estimate the statistical properties of security returns (e.g., betas or variances) using historical data, we are subject to sampling error. Regression parameters are only estimates and necessarily are subject to some imprecision. In this section, we put together much of the preceding material in an extended example. We show how historical data can be used in conjunction with the CAPM, but we also highlight some pitfalls to be avoided. Suppose that the true parameters for two stocks, A and B, and the market index portfolio are given in Table 7.6. However, investors cannot observe this information directly. They must estimate these parameters using historical returns. To illustrate the investor’s problem, we first produce 24 possible observations for the riskfree rate and the market index. Using the random number generator from a spreadsheet package (e.g., you can use “data analysis tools” in Microsoft Excel), we draw 24 observations from a normal distribution. These random numbers capture the phenomenon that actual returns will differ from expected returns: This is the “statistical noise” that accompanies all real-world return data. For the risk-free rate we set a mean of 5% and a standard deviation of 1.5% and

Because the mean of et is zero, e2t is the squared deviation from its mean. The average value of et2 is therefore the estimate of the variance of the firm-specific component. We divide the sum of squared residuals by the degrees of freedom of the regression, n ⫺ 2 ⫽ 12 ⫺ 2 ⫽ 10, to obtain an unbiased estimate of 2(e). 3

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TA B L E 7.7 Simulated data for estimation of security characteristic line (raw data from random number generator)

True mean True standard deviation Sample average Sample standard deviation

Residuals for Each Stock

Excess Returns

T-Bill Rate

Excess Return on Index

Stock A

Stock B

Stock A

Stock B

5.97 4.45 3.24 5.70 3.89 5.56 5.03 2.70 5.57 5.94 4.41 4.43 2.88 5.77 2.85 5.11 5.89 7.96 7.13 3.46 4.72 4.21 5.27 6.05

⫺3.75 ⫺9.46 26.33 6.06 38.97 ⫺1.35 ⫺24.18 15.20 39.52 ⫺2.84 ⫺0.97 29.82 0.73 16.54 ⫺39.43 ⫺4.94 3.01 36.98 42.22 24.67 ⫺11.64 19.15 ⫺19.13 5.05

7.52 26.14 18.09 ⫺0.88 48.37 ⫺30.80 ⫺10.74 68.91 ⫺14.09 0.43 73.75 25.31 ⫺83.07 ⫺33.45 60.21 3.84 47.37 ⫺32.91 ⫺58.15 77.05 ⫺51.49 14.06 ⫺80.44 ⫺91.90

44.13 ⫺38.79 ⫺65.43 69.24 61.51 26.25 0.93 ⫺18.53 16.80 ⫺36.15 ⫺20.33 68.88 ⫺10.82 43.85 ⫺11.82 2.95 12.80 ⫺30.88 ⫺58.68 3.89 ⫺16.87 ⫺18.79 59.07 ⫺67.83

2.64 13.85 52.32 7.00 99.03 ⫺32.56 ⫺42.18 88.66 37.29 ⫺3.26 72.48 64.08 ⫺82.13 ⫺11.95 8.95 ⫺2.59 51.29 15.16 ⫺3.26 109.11 ⫺66.62 38.95 ⫺105.31 ⫺85.33

41.50 ⫺45.41 ⫺46.99 73.49 88.78 25.30 ⫺16.00 ⫺7.89 44.46 ⫺38.14 ⫺21.01 89.76 ⫺10.31 55.43 ⫺39.42 ⫺0.51 14.91 ⫺4.99 ⫺29.12 21.15 ⫺25.02 ⫺5.39 45.69 ⫺64.29

5.00 1.50 4.93 1.34

8.00 20.00 7.77 21.56

0.00 54.07 ⫺0.70 50.02

0.00 37.47 0.64 41.48

10.40 60.00 9.40 58.31

5.60 40.00 6.08 43.95

record the results in the first column of Table 7.7. We then generate 24 observations for excess returns of the market index, using a mean of 8% and a standard deviation of 20%. We record these observations in the second column of Table 7.7. The bottom four rows in Table 7.7 show the true values for the means and standard deviations as well as the actual sample averages and standard deviations. As you would expect, the sample averages and standard deviations are close but not precisely equal to the true parameters of the probability distribution. This is a reflection of the statistical variation that gives rise to sampling error. In the next step we wish to generate excess returns for stocks A and B that are consistent with the CAPM. According to the CAPM, the rate of return on any security is given by r ⫺ rf ⫽ (rM ⫺ rf ) ⫹ e or using capital letters to denote excess returns, R ⫽ RM ⫹ e

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Coefficients

TA B L E 7.8 Regression analysis for stock A

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Alpha—Stock A Beta—Stock A

⫺0.46 1.27

Standard Error 11.12 0.50

t Stat ⫺0.04 2.52

Residual Output—Stock A Observation

Predicted A

Residuals

Actual Returns

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

⫺5.22 ⫺12.45 32.93 7.23 48.94 ⫺2.17 ⫺31.12 4.86 49.65 ⫺4.06 ⫺1.69 37.35 0.46 20.51 ⫺50.45 ⫺6.73 3.36 46.43 53.08 30.82 ⫺15.22 23.81 ⫺15.83 5.95

7.86 26.29 19.40 ⫺0.23 50.08 ⫺30.38 ⫺11.05 69.50 ⫺12.36 0.80 74.17 26.73 ⫺82.59 ⫺32.46 59.40 4.14 47.92 ⫺31.27 ⫺56.33 78.30 ⫺51.40 15.13 ⫺80.38 ⫺91.28

2.64 13.85 52.32 7.00 99.03 ⫺32.56 ⫺42.18 74.36 37.29 ⫺3.26 72.48 64.08 ⫺82.13 ⫺11.95 8.95 ⫺2.59 51.29 15.16 ⫺3.26 109.11 ⫺66.62 38.95 ⫺96.21 ⫺85.33

Therefore, the CAPM hypothesizes an alpha of zero in Equation 7.3. Given the values of  and RM, we need only random residuals, e, to generate a simulated sample of returns on each stock. Using the random number generator once again, we generate 24 observations for the residuals of stock A from a normal distribution with a mean of zero and a standard deviation of 54.07%. These observations are recorded in the third column of Table 7.7. Similarly, the randomly generated residuals for stock B use a standard deviation of 37.47% and are recorded in the fourth column of Table 7.7. The excess rates of return of stocks A and B are computed by multiplying the excess return on the market index by beta and adding the residual. The results appear in the last two columns of Table 7.7. Thus, the first two and last two columns of Table 7.7 correspond to the type of historical data that we might observe if the CAPM adequately describes capital market equilibrium. The numbers come from probability distributions consistent with the CAPM, but, because of the residuals, the CAPM’s expected return–beta relationship will not hold exactly due to sampling error. We now use a regression program (again, from the “data analysis” menu of our spreadsheet) to regress the excess return of each stock against the excess return of the index. The regression routine allows us to save the predicted return for each stock, based on the market return in that period, as well as the regression residuals. These values, and the regression statistics, are presented in Table 7.8 for stock A and Table 7.9 for stock B.

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Regression analysis for stock B

Alpha—Stock B Beta—Stock B

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Coefficients

TA B L E 7.9

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0.39 0.73

Standard Error 9.22 0.42

t Stat 0.04 1.76

Residual Output—Stock B Observation

Predicted B

Residuals

Actual Returns

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

⫺2.36 ⫺6.55 19.70 4.83 28.96 ⫺0.60 ⫺17.35 3.46 29.37 ⫺1.70 ⫺0.33 22.25 0.92 12.52 ⫺28.52 ⫺3.24 2.60 27.51 31.35 18.48 ⫺8.15 14.43 ⫺8.50 4.09

43.87 ⫺38.86 ⫺66.69 68.65 59.82 25.91 1.35 ⫺19.05 15.09 ⫺36.45 ⫺20.68 67.50 ⫺11.23 42.91 ⫺10.90 2.72 12.31 ⫺32.50 ⫺60.47 2.68 ⫺16.87 ⫺19.82 59.09 ⫺68.38

41.50 ⫺45.41 ⫺46.99 73.49 88.78 25.30 ⫺16.00 ⫺15.59 44.46 ⫺38.14 ⫺21.01 89.76 ⫺10.31 55.43 ⫺39.42 ⫺0.51 14.91 ⫺4.99 ⫺29.12 21.15 ⫺25.02 ⫺5.39 50.59 ⫺64.29

Observe from the regression statistics in Tables 7.8 and 7.9 that the beta of stock A is estimated at 1.27 (versus the true value of 1.3) and the beta of stock B is estimated at 0.73 (versus the true value of 0.7). The regression also shows estimates of alpha as ⫺0.46% for A and 0.39% for B (versus a true value of zero for both stocks), but the standard error of these estimates is large and their t-values are low, indicating that these are not statistically significant. The regression estimates allow us to plot the security characteristic line (SCL) for both stocks, shown in Figure 7.7 for stock A and Figure 7.8 for stock B. The CAPM representation of the securities is shown in Figures 7.9 and 7.10. Figure 7.9 shows the security market line (SML) supported by the risk-free rate and the market index. Stock A has a negative estimated alpha and is therefore below the line. This suggests that stock A is overpriced, that is, its expected return is below that which can be obtained with efficient portfolios and the risk-free rate. The negative estimated alpha is due to the effect of the firm-specific residuals. Similarly, stock B plots above the SML. Here, it appears that stock B is underpriced and has an expected return above that which can be obtained with the market index and the risk-free asset (given by the SML). Figure 7.10 shows the capital market line (CML) that is supported by the risk-free rate and the market index. The efficient frontier is generated by the Markowitz algorithm applied to the

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rA - rf (%) 150

100

50

–30

–10

rM - rf (%)

0 –50

10

30

50

10

30

50

–50

–100

F I G U R E 7.7 Security characteristic line for stock A

rB - rf (%) 150

100

50

–30

–10

rM - rf (%)

0 –50

–50

–100

F I G U R E 7.8 Security characteristic line for stock B

means, standard deviations, and correlation coefficients of the full set of risky assets in the universe of securities. (This additional information is not shown here.) Stocks A and B plot far

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20

SML Expected return (%)

15 A

B

M

10

5

rf

0 0

0.2

0.4

0.6

0.8

1

1.2

1.4

Beta

F I G U R E 7.9 Security market line

20

CML

Expected return (%)

15 M

Efficient frontier of risky assets

A

B

10

5

rf

0 0

10

20

30 40 Standard deviation (%)

50

F I G U R E 7.10 Capital market line

below the CML and below the efficient frontier, demonstrating that undiversified individual securities are dominated by efficiently diversified portfolios.

60

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E XC E L Applications

>

www.mhhe.com/bkm

Beta

This Excel model contains a data set that can be used to estimate beta coefficients for a number of stocks. The data contain individual stock and index returns and returns on Treasury bills. These were obtained from the Standard & Poor’s Educational Version of Market Insight, available at www.mhhe.com/edumarketinsight.com, and are analyzed using the regression function in Excel that was discussed in section 6.5, “A Single-Factor Asset Market.” You can learn more about this spreadsheet model by using the interactive version available on our website at www.mhhe.com/bkm.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

A B SUMMARY OUTPUT AXP

C

D

E

F

G

H

I

Regression Statistics Multiple R 0.69288601 R Square 0.48009103 Adjusted R Square 0.47112708 Standard Error 0.05887426 Observations 60 ANOVA

df Regression Residual Total

Intercept X Variable 1

SS MS F Significance F 1 0.185641557 0.1856416 53.55799 8.55186E-10 58 0.201038358 0.0034662 59 0.386679915

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 0.01181687 0.00776211 1.522379 0.133348 ⫺0.003720666 0.027354414 ⫺0.0037207 0.02735441 1.20877413 0.165170705 7.3183324 8.55E-10 0.878149288 1.539398969 0.87814929 1.53939897

Predicting Betas Even if a single-index model representation is not fully consistent with the CAPM, the concept of systematic versus diversifiable risk is still useful. Systematic risk is approximated well by the regression equation beta and nonsystematic risk by the residual variance of the regression. Often, we estimate betas in order to forecast the rate of return of an asset. The beta from the regression equation is an estimate based on past history; it will not reveal possible changes in future beta. As an empirical rule, it appears that betas exhibit a statistical property called “regression toward the mean.” This means that high  (that is,  ⬎ 1) securities in one period tend to exhibit a lower  in the future, while low  (that is,  ⬍ 1) securities exhibit a higher  in future periods. Researchers who desire predictions of future betas often adjust beta estimates derived from historical data to account for regression toward the mean. For this reason, it is necessary to verify whether the estimates are already “adjusted betas.” A simple way to account for the tendency of future betas to “regress” toward the average value of 1.0 is to use as your forecast of beta a weighted average of the sample estimate with the value 1.0. 238

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Suppose that past data yield a beta estimate of 0.65. A common weighting scheme is 2⁄3 on the sample estimate and 1⁄3 on the value 1.0. Thus, the final forecast of beta will be Adjusted beta ⫽ 2⁄3 ⫻ 0.65 ⫹ 1⁄3 ⫻ 1.0 ⫽ 0.77 The final forecast of beta is in fact closer to 1.0 than the sample estimate.

A more sophisticated technique would base the weight assigned to the sample estimate of beta on its statistical reliability. That is, if we have a more precise estimate of beta from historical data, we increase the weight placed on the sample estimate. However, obtaining a precise statistical estimate of beta from past data on individual stocks is a formidable task, because the volatility of rates of return is so large. In other words, there is a lot of “noise” in the data due to the impact of firm-specific events. The problem is less severe with diversified portfolios because diversification reduces the effect of firm-specific events. One might hope that more precise estimates of beta could be obtained by using more data, that is, by using a long time series of the returns on the stock. Unfortunately, this is not a solution, because regression analysis presumes that the regression coefficient (the beta) is constant over the sample period. If betas change over time, old data could provide a misleading guide to current betas. More complicated regression techniques that allow for time-varying coefficients also have not proved to be very successful. One promising avenue is an application of a technique that goes by the name of ARCH models.4 An ARCH model posits that changes in stock volatility, and covariance with other stocks, are partially predictable and analyzes recent levels and trends in volatility and covariance. This technique has penetrated the industry only recently and so has not yet produced truly reliable betas. Thus, the problem of estimating the critical parameters of the CAPM and index models has been a stick in the wheels of testing and applying the theory.

7.4

THE CAPM AND THE REAL WORLD

In limited ways, portfolio theory and the CAPM have become accepted tools in the practitioner community. Many investment professionals think about the distinction between firmspecific and systematic risk and are comfortable with the use of beta to measure systematic

WEBMA STER Beta Comparisons Go to http://moneycentral.msn.com/investor/research and http:nasdaq.com. Obtain the beta coefficients for IMB, PG, HWP, AEIS, and INTC. (Betas on the Nasdaq site can be found by using the info quotes and fundamental locations.) Compare the betas reported by these two sites. Then, answer the following questions:

4

1.

Are there any significant differences in the reported beta coefficients?

2.

What factors could lead to such differences?

ARCH stands for autoregressive conditional heteroskedasticity. This is a fancy way of saying that the volatility (and covariance) of stocks changes over time in ways that can be at least partially predicted from their past levels.

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EXAMPLE 7.7 Forecast of Beta

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Beta Beaten A battle between some of the top names in financial economics is attracting attention on Wall Street. Under attack is the famous capital asset pricing model (CAPM), widely used to assess risk and return. A new paper by two Chicago economists, Eugene Fama and Kenneth French, explodes that model by showing that its key analytical tool does not explain why returns on shares differ. According to the CAPM, returns reflect risk. The model uses a measure called beta—shorthand for relative volatility—to compare the riskiness of one share with that of the whole market, on the basis of past price changes. A share with a beta of one is just as risky as the market; one with a beta of 0.5 is less risky. Because investors need to earn more on riskier investments, share prices will reflect the requirement for higher-thanaverage returns on shares with higher betas. Whether beta does predict returns has long been debated. Studies have found that market capitalization, price/earnings ratios, leverage and book-to-market ratios do just as well. Messrs Fama and French are clear: Beta is not a good guide. The two economists look at all nonfinancial shares traded on the NYSE, Amex and Nasdaq between 1963 and 1990. The shares were grouped into portfolios. When grouped solely on the basis of size (that is, market capitalization), the CAPM worked—but each portfolio contained a wide range of betas. So the authors grouped shares of similar beta and size. Betas now were a bad guide to returns. Instead of beta, say Messrs Fama and French, differences in firm size and in the ratio of book value to market value explain differences in returns—especially the latter. When shares were grouped by book-to-

market ratios, the gap in returns between the portfolio with the lowest ratio and that with the highest was far wider than when shares were grouped by size. So should analysts stop using the CAPM? Probably not. Although Mr. Fama and Mr. French have produced intriguing results, they lack a theory to explain them. Their best hope is that size and book-to-market ratios are proxies for other fundamentals. For instance, a high book-to-market ratio may indicate a firm in trouble; its earnings prospects might thus be especially sensitive to economic conditions, so its shares would need to earn a higher return than its beta suggested. Advocates of CAPM—including Fischer Black, of Goldman Sachs, an investment bank, and William Sharpe of Stanford University, who won the Nobel Prize for economics in 1990—reckon the results of the new study can be explained without discarding beta. Investors may irrationally favor big firms. Or they may lack the cash to buy enough shares to spread risk completely, so that risk and return are not perfectly matched in the market. Those looking for a theoretical alternative to CAPM will find little satisfaction, however. Voguish rivals, such as the “arbitrage pricing theory,” are no better than CAPM and betas at explaining actual share returns. Which leaves Wall Street with an awkward choice: Believe the Fama–French evidence, despite its theoretical vacuum, and use size and the book-to-market ratios as a guide to returns; or stick with a theory that, despite the data, is built on impeccable logic. SOURCE: “Beta Beaten,” The Economist, March 7, 1992, p. 87, based on Eugene Fama and Kenneth French, “The Cross-Section of Expected Stock Returns,” University of Chicago Center for Research in Security Prices, 1991.

risk. Still, the nuances of the CAPM are not nearly as well established in the community. For example, the compensation of portfolio managers is not based on appropriate performance measures (see Chapter 20). What can we make of this? New ways of thinking about the world (that is, new models or theories) displace old ones when the old models become either intolerably inconsistent with data or when the new model is demonstrably more consistent with available data. For example, when Copernicus overthrew the age-old belief that the Earth is fixed in the center of the Universe and that the stars orbit about it in circular motions, it took many years before astronomers and navigators replaced old astronomical tables with superior ones based on his theory. The old tools fit the data available from astronomical observation with sufficient precision to suffice for the needs of the time. To some extent, the slowness with which the CAPM has permeated daily practice in the money management industry also has to do with its precision in fitting data, that is, in precisely explaining variation in rates of return across assets. Let’s review some of the evidence on this score. 240

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The CAPM was first published by Sharpe in the Journal of Finance (the journal of the American Finance Association) in 1964 and took the world of finance by storm. Early tests by Black, Jensen, and Scholes (1972) and Fama and MacBeth (1973) were only partially supportive of the CAPM: average returns were higher for higher-beta portfolios, but the reward for beta risk was less than the predictions of the simple theory. While all this accumulating evidence against the CAPM remained largely within the ivory towers of academia, Roll’s (1977) paper “A Critique of Capital Asset Pricing Tests” shook the practitioner world as well. Roll argued that since the true market portfolio can never be observed, the CAPM is necessarily untestable. The publicity given the now classic “Roll’s critique” resulted in popular articles such as “Is Beta Dead?” that effectively slowed the permeation of portfolio theory through the world of finance.5 This is quite ironic since, although Roll is absolutely correct on theoretical grounds, some tests suggest that the error introduced by using a broad market index as proxy for the true, unobserved market portfolio is perhaps the lesser of the problems involved in testing the CAPM. Fama and French (1992) published a study that dealt the CAPM an even harsher blow. They claimed that once you control for a set of widely followed characteristics of the firm, such as the size of the firm and its ratio of market value to book value, the firm’s beta (that is, its systematic risk) does not contribute anything to the prediction of future returns. This time, the piece was picked up by The Economist and the New York Times (see the nearby box) even before it was published in the Journal of Finance. Fama and French and several others have published many follow-up studies of this topic. We will review some of this literature in the next chapter. However, it seems clear from these studies that beta does not tell the whole story of risk. There seem to be risk factors that affect security returns beyond beta’s one-dimensional measurement of market sensitivity. In fact, in the next section of this chapter, we will introduce a theory of risk premiums that explicitly allows for multiple risk factors. Liquidity, a different kind of risk factor, has been ignored for a long time. Although first analyzed by Amihud and Mendelson as early as 1986, it is yet to be accurately measured and incorporated in portfolio management. Measuring liquidity and the premium commensurate with illiquidity is part of a larger field in financial economics, namely, market structure. We now know that trading mechanisms on stock exchanges affect the liquidity of assets traded on these exchanges and thus significantly affect their market value. Despite all these issues, beta is not dead. Other research shows that when we use a more inclusive proxy for the market portfolio than the S&P 500 (specifically, an index that includes human capital) and allow for the fact that beta changes over time, the performance of beta in explaining security returns is considerably enhanced (Jagannathan and Wang, 1996). We know that the CAPM is not a perfect model and that ultimately it will be far from the last word on security pricing. Still, the logic of the model is compelling, and more sophisticated models of security pricing all rely on the key distinction between systematic versus diversifiable risk. The CAPM therefore provides a useful framework for thinking rigorously about the relationship between security risk and return. This is as much as Copernicus had when he was shown the prepublication version of his book just before he passed away.

7.5

ARBITRAGE PRICING THEORY

In the 1970s, as researchers were working on test methodologies for variants of the CAPM, Stephen Ross (1976) stunned the world of finance with the arbitrage pricing theory (APT). 5

A. Wallace, “Is Beta Dead?” Institutional Investor 14 (July 1980), pp. 22–30.

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Moving away from construction of mean-variance efficient portfolios, Ross instead calculated relations among expected rates of return that would rule out riskless profits by any investor in well-functioning capital markets. This generated a theory of risk and return similar to the CAPM.

Arbitrage Opportunities and Profits arbitrage Creation of riskless profits made possible by relative mispricing among securities.

zero-investment portfolio A portfolio of zero net value, established by buying and shorting component securities, usually in the context of an arbitrage strategy.

To explain the APT, we begin with the concept of arbitrage, which is the exploitation of relative mispricing among two or more securities to earn risk-free economic profits. A riskless arbitrage opportunity arises when an investor can construct a zero-investment portfolio that will yield a sure profit. Zero investment means investors need not use any of their own money. To construct a zero-investment portfolio, one has to be able to sell short at least one asset and use the proceeds to purchase (go long) one or more assets. Even a small investor, using borrowed money in this fashion, can take a large position in such a portfolio. An obvious case of an arbitrage opportunity arises in the violation of the law of one price: When an asset is trading at different prices in two markets (and the price differential exceeds transaction costs), a simultaneous trade in the two markets will produce a sure profit (the net price differential) without any net investment. One simply sells short the asset in the highpriced market and buys it in the low-priced market. The net proceeds are positive, and there is no risk because the long and short positions offset each other. In modern markets with electronic communications and instantaneous execution, such opportunities have become rare but not extinct. The same technology that enables the market to absorb new information quickly also enables fast operators to make large profits by trading huge volumes at the instant an arbitrage opportunity opens. This is the essence of program trading and index arbitrage, to be discussed in Part Five. From the simple case of a violation of the law of one price, let us proceed to a less obvious (yet just as profitable) arbitrage opportunity. Imagine that four stocks are traded in an economy with only four possible scenarios. The rates of return on the four stocks for each inflation-interest rate scenario appear in Table 7.10. The current prices of the stocks and rate of return statistics are shown in Table 7.11. The rate of return data give no immediate clue to any arbitrage opportunity lurking in this set of investments. The expected returns, standard deviations, and correlations do not reveal any abnormality to the naked eye. Consider, however, an equally weighted portfolio of the first three stocks (Apex, Bull, and Crush), and contrast its possible future rates of return with those of the fourth stock, Dreck. We do this in Table 7.12. Table 7.12 reveals that in all four scenarios, the equally weighted portfolio will outperform Dreck. The rate of return statistics of the two alternatives are Mean

Standard Deviation

Three-stock portfolio

25.83

6.40

Dreck

22.25

8.58

Correlation 0.94

The two investments are not perfectly correlated and are not perfect substitutes. Nevertheless, the equally weighted portfolio will fare better under any circumstances. Any investor, no matter how risk averse, can take advantage of this dominance by taking a short position in Dreck and using the proceeds to purchase the equally weighted portfolio. Let us see how it would work.

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Probability: Stock Apex (A) Bull (B) Crush (C ) Dreck (D)

TA B L E 7.11 Rate of return statistics

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High Real Interest Rates

TA B L E 7.10 Rate of return projections

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Low Real Interest Rates

High Inflation

Low Inflation

High Inflation

Low Inflation

0.25

0.25

0.25

0.25

⫺20 0 90 15

20 70 ⫺20 23

40 30 ⫺10 15

60 ⫺20 70 36

Correlation Matrix

Stock

Current Price

Expected Return (%)

Standard Deviation (%)

A

B

C

D

A B C D

$10 10 10 10

25.0% 20.0 32.5 22.25

29.58% 33.91 48.15 8.58

1.00 ⫺0.15 ⫺0.29 0.68

⫺0.15 1.00 ⫺0.87 ⫺0.38

⫺0.29 ⫺0.87 1.00 0.22

0.68 ⫺0.38 0.22 1.00

TA B L E 7.12 Rate of return projections

Equally weighted portfolio: A, B, and C Dreck (D)

High Real Interest Rates

Low Real Interest Rates

Rate of Inflation

Rate of Inflation

High

Low

High

Low

23.33 15.00

23.33 23.00

20.00 15.00

36.67 36.00

Suppose we sell short 300,000 shares of Dreck and use the $3 million proceeds to buy 100,000 shares each of Apex, Bull, and Crush. The dollar profits in each of the four scenarios will be as follows. High Real Interest Rates

Low Real Interest Rates

Inflation Rate

Inflation Rate

Stock

Dollar Investment

High

Low

High

Low

Apex Bull Crush Dreck

$ 1,000,000 1,000,000 1,000,000 ⫺3,000,000

$⫺200,000 0 900,000 ⫺450,000

$ 200,000 700,000 ⫺200,000 ⫺690,000

$ 400,000 300,000 ⫺100,000 ⫺450,000

$

600,000 ⫺200,000 700,000 ⫺1,080,000

Portfolio

$

$ 250,000

$

$ 150,000

$

20,000

0

10,000

The first column verifies that the net investment in our portfolio is zero. Yet this portfolio yields a positive profit in all scenarios. It is therefore a money machine. Investors will want to

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take an infinite position in such a portfolio, for larger positions entail no risk of losses yet yield ever-growing profits.6 In principle, even a single investor would take such large positions that the market would react to the buying and selling pressure: The price of Dreck would come down, and/or the prices of Apex, Bull, and Crush would go up. The pressure would persist until the arbitrage opportunity was eliminated.

Concept CHECK

>

5. Suppose Dreck’s price starts falling without any change in its per-share dollar payoffs. How far must the price fall before arbitrage between Dreck and the equally weighted portfolio is no longer possible? (Hint: Account for the amount of the equally weighted portfolio that can be purchased with the proceeds of the short sale as Dreck’s price falls.) The critical property of an arbitrage portfolio is that any investor, regardless of risk aversion or wealth, will want to take an infinite position in it so that profits will be driven to an infinite level. Because those large positions will force some prices up and/or some down until the opportunity vanishes, we can derive restrictions on security prices that satisfy the condition that no arbitrage opportunities are left in the marketplace. The idea that equilibrium market prices ought to be rational in the sense that they rule out arbitrage opportunities is perhaps the most fundamental concept in capital market theory. Violation of this principle would indicate the grossest form of market irrationality. There is an important distinction between arbitrage and CAPM risk-versus-return dominance arguments in support of equilibrium price relationships. A dominance argument, as in the CAPM, holds that when an equilibrium price relationship is violated, many investors will make portfolio changes. Each individual investor will make a limited change, though, depending on wealth and degree of risk aversion. Aggregation of these limited portfolio changes over many investors is required to create a large volume of buying and selling, which restores equilibrium prices. When arbitrage opportunities exist, by contrast, each investor wants to take as large a position as possible; in this case, it will not take many investors to bring about the price pressures necessary to restore equilibrium. Implications derived from the no-arbitrage argument, therefore, are stronger than implications derived from a risk-versus-return dominance argument, because they do not depend on a large, well-educated population of investors. The CAPM argues that all investors hold mean-variance efficient portfolios. When a security (or a bundle of securities) is mispriced, investors will tilt their portfolios toward the underpriced and away from the overpriced securities. The resulting pressure on prices comes from many investors shifting their portfolios, each by a relatively small dollar amount. The assumption that a large number of investors are mean-variance optimizers, is critical; in contrast, even few arbitrageurs will mobilize large dollar amounts to take advantage of an arbitrage opportunity.

arbitrage pricing theory (APT) A theory of risk-return relationships derived from no-arbitrage considerations in large capital markets

Well-Diversified Portfolios and the Arbitrage Pricing Theory The arbitrage opportunity described in the previous section is further obscured by the fact that it is almost always impossible to construct a precise scenario analysis for individual stocks that would uncover an event of such straightforward mispricing. Using the concept of well-diversified portfolios, the arbitrage pricing theory, or APT, resorts to statistical modeling to attack the problem more systematically. By showing that 6

We have described pure arbitrage: the search for a costless sure profit. Practitioners often use the terms arbitrage and arbitrageurs more loosely. An arbitrageur may be a professional searching for mispriced securities in specific areas such as merger-target stocks, rather than one looking for strict (risk-free) arbitrage opportunities in the sense that no loss is possible. The search for mispriced securities is called risk arbitrage to distinguish it from pure arbitrage.

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mispriced portfolios would give rise to arbitrage opportunities, the APT arrives at an expected return–beta relationship for portfolios identical to that of the CAPM. In the next section, we will compare and contrast the two theories. In its simple form, just like the CAPM, the APT posits a single-factor security market. Thus, the excess rate of return on each security, Ri ⫽ ri ⫺ rf, can be represented by Ri ⫽ ␣i ⫹ iRM ⫹ e

(7.5)

where alpha, ␣i, and beta, i, are known, and where we treat RM as the single factor. Suppose now that we construct a highly diversified portfolio with a given beta. If we use enough securities to form the portfolio, the resulting diversification will strip the portfolio of nonsystematic risk. Because such a well-diversified portfolio has for all practical purposes zero firm-specific risk, we can write its returns as RP ⫽ ␣P ⫹ PRM

(7.6)

(This portfolio is risky, however, because the excess return on the index, RM, is random.) Figure 7.11 illustrates the difference between a single security with a beta of 1.0 and a welldiversified portfolio with the same beta. For the portfolio (Panel A), all the returns plot exactly on the security characteristic line. There is no dispersion around the line, as in Panel B, because the effects of firm-specific events are eliminated by diversification. Therefore, in Equation 7.6, there is no residual term, e. Notice that Equation 7.6 implies that if the portfolio beta is zero, then RP ⫽ ␣P. This implies a riskless rate of return: There is no firm-specific risk because of diversification and no factor risk because beta is zero. Remember, however, that R denotes excess returns. So the equation implies that a portfolio with a beta of zero has a riskless excess return of ␣P, that is, a return higher than the risk-free rate by the amount ␣P. But this implies that ␣P must equal zero, or else an immediate arbitrage opportunity opens up. For example, if ␣P is greater than zero, you can borrow at the risk-free rate and use the proceeds to buy the well-diversified zero-beta portfolio. You borrow risklessly at rate rf and invest risklessly at rate rf ⫹ ␣P, clearing the riskless differential of ␣P.

Return (%)

10

0

A: Well-diversified portfolio

Security characteristic lines

A portfolio sufficiently diversified that nonsystematic risk is negligible.

Return (%)

10

F I G U R E 7.11

well-diversified portfolio

RM

0

B: Single stock

RM

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7.8 EXAMPLE Arbitrage with a Zero-Beta Portfolio

Suppose that the risk-free rate is 6%, and a well-diversified zero-beta portfolio earns (a sure) rate of return of 7%, that is, an excess return of 1%. Then borrow at 6% and invest in the zerobeta portfolio to earn 7%. You will earn a sure profit of 1% of the invested funds without putting up any of your own money. If the zero-beta portfolio earns 5%, then you can sell it short and lend at 6% with the same result.

In fact, we can go further and show that the alpha of any well-diversified portfolio in Equation 7.6 must be zero, even if the beta is not zero. The proof is similar to the easy zero-beta case. If the alphas were not zero, then we could combine two of these portfolios into a zerobeta riskless portfolio with a rate of return not equal to the risk-free rate. But this, as we have just seen, would be an arbitrage opportunity. To see how the arbitrage strategy would work, suppose that portfolio V has a beta of v and an alpha of ␣v. Similarly, suppose portfolio U has a beta of u and an alpha of ␣u. Taking advantage of any arbitrage opportunity involves buying and selling assets in proportions that create a risk-free profit on a costless position. To eliminate risk, we buy portfolio V and sell portfolio U in proportions chosen so that the combination portfolio (V ⫹ U) will have a beta of zero. The portfolio weights that satisfy this condition are wv ⫽

⫺u v ⫺ u

wu ⫽

v v ⫺ u

Note that wv plus wu add up to 1.0 and that the beta of the combination is in fact zero: Beta(V ⫹ U) ⫽ v

⫺u v ⫹ u ⫽0 v ⫺ u v ⫺ u

Therefore, the portfolio is riskless: It has no sensitivity to the factor. But the excess return of the portfolio is not zero unless ␣v and ␣u equal zero. R(V ⫹ U) ⫽ ␣v

⫺u v ⫹ ␣u ⫽0 v ⫺ u v ⫺ u

Therefore, unless ␣v and ␣u equal zero, the zero-beta portfolio has a certain rate of return that differs from the risk-free rate (its excess return is different from zero). We have seen that this gives rise to an arbitrage opportunity.

7.9 EXAMPLE Arbitrage with Mispriced Portfolios

Suppose that the risk-free rate is 7% and a well-diversified portfolio, V, with beta of 1.3 has an alpha of 2% and another well-diversified portfolio, U, with beta of 0.8 has an alpha of 1%. We go long on V and short on U with proportions 1.3 ⫺0.8 wv ⫽ ⫽ ⫺1.6 wu ⫽ ⫽ 2.6 1.3 ⫺ 0.8 1.3 ⫺ 0.8 These proportions add up to 1.0 and result in a portfolio with beta ⫽ ⫺1.6 ⫻ 1.3 ⫹ 2.6 ⫻ 0.8 ⫽ 0. The alpha of the portfolio is: ⫺1.6 ⫻ 2% ⫹ 2.6 ⫻ 1% ⫽ ⫺0.6%. This means that the riskless portfolio will earn a rate of return that is less than the risk-free rate by .6%. We now complete the arbitrage by selling (or going short on) the combination portfolio and investing the proceeds at 7%, risklessly profiting by the 60 basis point differential in returns.

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We conclude that the only value for alpha that rules out arbitrage opportunities is zero. Therefore, rewrite Equation 7.6 setting alpha equal to zero RP ⫽ PRM rP ⫺ rf ⫽ P(rM ⫺ rf) E(rP) ⫽ rf ⫹ P[E(rM) ⫺ rf ] Hence, we arrive at the same expected return–beta relationship as the CAPM without any assumption about either investor preferences or access to the all-inclusive (and elusive) market portfolio.

The APT and the CAPM Why did we need so many restrictive assumptions to derive the CAPM when the APT seems to arrive at the expected return–beta relationship with seemingly fewer and less objectionable assumptions? The answer is simple: The APT applies only to well-diversified portfolios. Absence of riskless arbitrage alone cannot guarantee that, in equilibrium, the expected return–beta relationship will hold for any and all assets. With additional effort, however, one can use the APT to show that the relationship must hold approximately even for individual assets. The essence of the proof is that if the expected return–beta relationship were violated by many individual securities, it would be virtually impossible for all well-diversified portfolios to satisfy the relationship. So the relationship must almost surely hold true for individual securities. We say “almost” because, according to the APT, there is no guarantee that all individual assets will lie on the SML. If only a few securities violated the SML, their effect on welldiversified portfolios could conceivably be offsetting. In this sense, it is possible that the SML relationship is violated for single securities. If many securities violate the expected return–beta relationship, however, the relationship will no longer hold for well-diversified portfolios comprising these securities, and arbitrage opportunities will be available. The APT serves many of the same functions as the CAPM. It gives us a benchmark for fair rates of return that can be used for capital budgeting, security evaluation, or investment performance evaluation. Moreover, the APT highlights the crucial distinction between nondiversifiable risk (systematic or factor risk) that requires a reward in the form of a risk premium and diversifiable risk that does not. The bottom line is that neither of these theories dominates the other. The APT is more general in that it gets us to the expected return–beta relationship without requiring many of the unrealistic assumptions of the CAPM, particularly the reliance on the market portfolio. The latter improves the prospects for testing the APT. But the CAPM is more general in that it applies to all assets without reservation. The good news is that both theories agree on the expected return–beta relationship. It is worth noting that because past tests of the expected return–beta relationship examined the rates of return on highly diversified portfolios, they actually came closer to testing the APT than the CAPM. Thus, it appears that econometric concerns, too, favor the APT.

Multifactor Generalization of the APT and CAPM We’ve assumed all along that there is only one systematic factor affecting stock returns. This assumption may be too simplistic. It is easy to think of several factors that might affect stock returns: business cycles, interest rate fluctuations, inflation rates, oil prices, and so on. Presumably, exposure to any of these factors singly or together will affect a stock’s perceived

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riskiness and appropriate expected rate of return. We can use a multifactor version of the APT to accommodate these multiple sources of risk. Suppose we generalize the single-factor model expressed in Equation 7.5 to a two-factor model: Ri ⫽ ␣i ⫹ i1RM1 ⫹ i2RM2 ⫹ ei

factor portfolio A well-diversified portfolio constructed to have a beta of 1.0 on one factor and a beta of zero on any other factor.

(7.7)

where RM1 and RM2 are the excess returns on portfolios that represent the two systematic factors. Factor 1 might be, for example, unanticipated changes in industrial production, while factor 2 might represent unanticipated changes in short-term interest rates. We assume again that there are many securities available with any combination of betas. This implies that we can form well-diversified factor portfolios, that is, portfolios that have a beta of 1.0 on one factor and a beta of zero on all others. Thus, a factor portfolio with a beta of 1.0 on the first factor will have a rate of return of RM1; a factor portfolio with a beta of 1.0 on the second factor will have a rate of return of RM2; and so on. Factor portfolios can serve as the benchmark portfolios for a multifactor generalization of the security market line relationship. Suppose the two-factor portfolios, here called portfolios 1 and 2, have expected returns E(r1) ⫽ 10% and E(r2) ⫽ 12%. Suppose further that the risk-free rate is 4%. The risk premium on the first factor portfolio is therefore 6%, while that on the second factor portfolio is 8%. Now consider an arbitrary well-diversified portfolio (A), with beta on the first factor, A1 ⫽ 0.5, and on the second factor, A2 ⫽ 0.75. The multifactor APT states that the portfolio risk premium must equal the sum of the risk premiums required as compensation to investors for each source of systematic risk. The risk premium attributable to risk factor 1 is the portfolio’s exposure to factor 1, A1, times the risk premium earned on the first factor portfolio, E(r1) ⫺ rf . Therefore, the portion of portfolio A’s risk premium that is compensation for its exposure to the first risk factor is A1[E(r1) ⫺ rf ] ⫽ 0.5 (10% ⫺ 4%) ⫽ 3%, while the risk premium attributable to risk factor 2 is A2[E(r2) ⫺ rf ] ⫽ 0.75 (12% ⫺ 4%) ⫽ 6%. The total risk premium on the portfolio, therefore, should be 3 ⫹ 6 ⫽ 9%, and the total return on the portfolio should be 13%. 4%

Risk-free rate

⫹ 3%

Risk premium for exposure to factor 1

⫹ 6%

Risk premium for exposure to factor 2

13%

Total expected return

To generalize this argument, note that the factor exposure of any portfolio P is given by its betas, P1 and P2. A competing portfolio, Q, can be formed from factor portfolios with the following weights: P1 in the first factor portfolio; P2 in the second factor portfolio; and 1 ⫺ P2 ⫺ P2 in T-bills. By construction, Q will have betas equal to those of portfolio P and an expected return of E(rQ) ⫽ P1E(r1) ⫹ P2E(r2) ⫹ (1 ⫺ P1 ⫺ P2)rf ⫽ rf ⫹ P1[E(r1) ⫺ rf ] ⫹ P2[E(r2) ⫺ rf ]

(7.8)

Using our numbers, E(rQ) ⫽ 4 ⫹ .5 ⫻ (10 ⫺ 4) ⫹ .75 ⫻ (12 ⫺ 4) ⫽ 13% Because portfolio Q has precisely the same exposures as portfolio A to the two sources of risk, their expected returns also ought to be equal. So portfolio A also ought to have an expected return of 13%.

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E XCEL Applications

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Estimating the Index Model

The spreadsheet below (available at www.mhhe.com/bkm) also contains monthly returns for the stocks that comprise the Dow Jones Industrial Average. The spreadsheet contains workbooks that show raw returns, risk premiums, correlation coefficients, and beta coefficients for the stocks that are in the DJIA. The security characteristic lines are estimated with five years of monthly returns.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

A B SUMMARY OUTPUT AXP

C

D

E

F

G

H

I

Regression Statistics Multiple R 0.69288601 R Square 0.48009103 Adjusted R Square 0.47112708 Standard Error 0.05887426 Observations 60 ANOVA

df Regression Residual Total

Intercept X Variable 1

SS MS F Significance F 1 0.185641557 0.1856416 53.55799 8.55186E-10 58 0.201038358 0.0034662 59 0.386679915

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 0.01181687 0.00776211 1.522379 0.133348 ⫺0.003720666 0.027354414 ⫺0.0037207 0.02735441 1.20877413 0.165170705 7.3183324 8.55E-10 0.878149288 1.539398969 0.87814929 1.53939897

Suppose, however, that the expected return on portfolio A is 12% rather than 13%. This return would give rise to an arbitrage opportunity. Form a portfolio from the factor portfolios with the same betas as portfolio A. This requires weights of 0.5 on the first factor portfolio, 0.75 on the second portfolio, and ⫺ 0.25 on the risk-free asset. This portfolio has exactly the same factor betas as portfolio A: a beta of 0.5 on the first factor because of its 0.5 weight on the first factor portfolio and a beta of 0.75 on the second factor. Now invest $1 in portfolio Q and sell (short) $1 in portfolio A. Your net investment is zero, but your expected dollar profit is positive and equal to $1 ⫻ E(rQ) ⫺ $1 ⫻ E(rA) ⫽ $1 ⫻ .13 ⫺ $1 ⫻ .12 ⫽ $.01. Moreover, your net position is riskless. Your exposure to each risk factor cancels out because you are long $1 in portfolio Q and short $1 in portfolio A, and both of these well-diversified portfolios have exactly the same factor betas. Thus, if portfolio A’s expected return differs from that of portfolio Q’s, you can earn positive risk-free profits on a zero net investment position. This is an arbitrage opportunity. Hence, any well-diversified portfolio with betas P1 and P2 must have the return given in Equation 7.8 if arbitrage opportunities are to be ruled out. A comparison of Equations 7.2 and 7.8 shows that 7.8 is simply a generalization of the one-factor SML. Finally, extension of the multifactor SML of Equation 7.8 to individual assets is precisely the same as for the one-factor APT. Equation 7.8 cannot be satisfied by every well-diversified portfolio unless it is satisfied by virtually every security taken individually. Equation 7.8 thus represents the multifactor SML for an economy with multiple sources of risk. 249

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The generalized APT must be qualified with respect to individual assets just as in the single-factor case. A multifactor CAPM would, at the cost of additional assumptions, apply to any and all individual assets. As we have seen, the result will be a security market equation (a multidimensional SML) that is identical to that of the multifactor APT.

>

6. Using the factor portfolios just considered, find the fair rate of return on a security with 1 ⴝ 0.2 and 2 ⴝ 1.4.

SUMMARY

• The CAPM assumes investors are rational, single-period planners who agree on a common input list from security analysis and seek mean-variance optimal portfolios. • The CAPM assumes ideal security markets in the sense that: (a) markets are large and investors are price takers, (b) there are no taxes or transaction costs, (c) all risky assets are publicly traded, and (d) any amount can be borrowed and lent at a fixed, risk-free rate. • These assumptions mean that all investors will hold identical risky portfolios. The CAPM implies that, in equilibrium, the market portfolio is the unique mean-variance efficient tangency portfolio, which indicates that a passive strategy is efficient. • The market portfolio is a value-weighted portfolio. Each security is held in a proportion equal to its market value divided by the total market value of all securities. The risk premium on the market portfolio is proportional to its variance, M2 , and to the risk aversion of the average investor. • The CAPM implies that the risk premium on any individual asset or portfolio is the product of the risk premium of the market portfolio and the asset’s beta. The security market line shows the return demanded by investors as a function of the beta of their investment. This expected return is a benchmark for evaluating investment performance. • In a single-index security market, once an index is specified, a security beta can be estimated from a regression of the security’s excess return on the index’s excess return. This regression line is called the security characteristic line (SCL). The intercept of the SCL, called alpha, represents the average excess return on the security when the index excess return is zero. The CAPM implies that alphas should be zero. • An arbitrage opportunity arises when the disparity between two or more security prices enables investors to construct a zero net investment portfolio that will yield a sure profit. Rational investors will want to take infinitely large positions in arbitrage portfolios regardless of their degree of risk aversion. • The presence of arbitrage opportunities and the resulting volume of trades will create pressure on security prices that will persist until prices reach levels that preclude arbitrage. Only a few investors need to become aware of arbitrage opportunities to trigger this process because of the large volume of trades in which they will engage. • When securities are priced so that there are no arbitrage opportunities, the market satisfies the no-arbitrage condition. Price relationships that satisfy the no-arbitrage condition are important because we expect them to hold in real-world markets. • Portfolios are called well diversified if they include a large number of securities in such proportions that the residual or diversifiable risk of the portfolio is negligible. • In a single-factor security market, all well-diversified portfolios must satisfy the expected return–beta relationship of the SML in order to satisfy the no-arbitrage condition. • If all well-diversified portfolios satisfy the expected return–beta relationship, then all but a small number of securities also must satisfy this relationship.

Concept

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CHECK

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• The APT implies the same expected return–beta relationship as the CAPM, yet does not require that all investors be mean-variance optimizers. The price of this generality is that the APT does not guarantee this relationship for all securities at all times. • A multifactor APT generalizes the single-factor model to accommodate several sources of systematic risk. expected return–beta relationship, 225 factor portfolio, 248 market portfolio, 221 mutual fund theorem, 223 security characteristic line (SCL), 231

security market line (SML), 226 well-diversified portfolio, 245 zero-investment portfolio, 242

1. Which of the following statements about the security market line (SML) are true? a. The SML provides a benchmark for evaluating expected investment performance. b. The SML leads all investors to invest in the same portfolio of risky assets. c. The SML is a graphic representation of the relationship between expected return and beta. d. Properly valued assets plot exactly on the SML. 2. Risk aversion has all of the following implications for the investment process except: a. The security market line is upward sloping. b. The promised yield on AAA-rated bonds is higher than on A-rated bonds. c. Investors expect a positive relationship between expected return and risk. d. Investors prefer portfolios that lie on the efficient frontier to other portfolios with equal expected rates of return. 3. What is the beta of a portfolio with E(rP) ⫽ 20%, if rf ⫽ 5% and E(rM) ⫽ 15%? 4. The market price of a security is $40. Its expected rate of return is 13%. The risk-free rate is 7%, and the market risk premium is 8%. What will the market price of the security be if its beta doubles (and all other variables remain unchanged)? Assume the stock is expected to pay a constant dividend in perpetuity. 5. You are a consultant to a large manufacturing corporation considering a project with the following net after-tax cash flows (in millions of dollars) Years from Now

After-Tax CF

0 1–9 10

⫺20 10 20

The project’s beta is 1.7. Assuming rf ⫽ 9% and E(rM) ⫽ 19%, what is the net present value of the project? What is the highest possible beta estimate for the project before its NPV becomes negative? 6. Are the following statements true or false? Explain. a. Stocks with a beta of zero offer an expected rate of return of zero. b. The CAPM implies that investors require a higher return to hold highly volatile securities. c. You can construct a portfolio with a beta of 0.75 by investing 0.75 of the budget in T-bills and the remainder in the market portfolio.

KEY TERMS

PROBLEM SETS

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alpha, 227 arbitrage, 242 arbitrage pricing theory (APT), 244 capital asset pricing model (CAPM), 221

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7. Consider the following table, which gives a security analyst’s expected return on two stocks for two particular market returns: Market Return

Aggressive Stock

Defensive Stock

5% 20

2% 32

3.5% 14

a. What are the betas of the two stocks? b. What is the expected rate of return on each stock if the market return is equally likely to be 5% or 20%? c. If the T-bill rate is 8%, and the market return is equally likely to be 5% or 20%, draw the SML for this economy. d. Plot the two securities on the SML graph. What are the alphas of each? e. What hurdle rate should be used by the management of the aggressive firm for a project with the risk characteristics of the defensive firm’s stock? If the simple CAPM is valid, which of the situations in problems 8–14 below are possible? Explain. Consider each situation independently. 8. Portfolio

Expected Return

Beta

A B

20% 25

1.4 1.2

9. Portfolio

Expected Return

Standard Deviation

A B

30% 40

35% 25

Portfolio

Expected Return

Standard Deviation

Risk-free Market A

10% 18 16

0% 24 12

Portfolio

Expected Return

Standard Deviation

Risk-free Market A

10% 18 20

0% 24 22

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10.

11.

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Portfolio

Expected Return

Beta

Risk-free Market A

10% 18 16

0 1.0 1.5

Portfolio

Expected Return

Beta

Risk-free Market A

10% 18 16

0 1.0 .9

13.

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Portfolio

Expected Return

Standard Deviation

Risk-free Market A

10% 18 16

0% 24 22

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15. A share of stock is now selling for $100. It will pay a dividend of $9 per share at the end of the year. Its beta is 1.0. What do investors expect the stock to sell for at the end of the year? 16. I am buying a firm with an expected perpetual cash flow of $1,000 but am unsure of its risk. If I think the beta of the firm is zero, when the beta is really 1.0, how much more will I offer for the firm than it is truly worth? 17. A stock has an expected return of 6%. What is its beta? 18. Two investment advisers are comparing performance. One averaged a 19% return and the other a 16% return. However, the beta of the first adviser was 1.5, while that of the second was 1.0. a. Can you tell which adviser was a better selector of individual stocks (aside from the issue of general movements in the market)? b. If the T-bill rate were 6%, and the market return during the period were 14%, which adviser would be the superior stock selector? c. What if the T-bill rate were 3% and the market return 15%? 19. In 2002, the yield on short-term government securities (perceived to be risk-free) was about 4%. Suppose the expected return required by the market for a portfolio with a beta of 1.0 is 12%. According to the capital asset pricing model: a. What is the expected return on the market portfolio? b. What would be the expected return on a zero-beta stock? c. Suppose you consider buying a share of stock at a price of $40. The stock is expected to pay a dividend of $3 next year and to sell then for $41. The stock risk has been evaluated at  ⫽ ⫺0.5. Is the stock overpriced or underpriced?

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In problems 15–17 below, assume the risk-free rate is 8% and the expected rate of return on the market is 18%.

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20. Based on current dividend yields and expected capital gains, the expected rates of return on portfolio A and B are 11% and 14%, respectively. The beta of A is 0.8 while that of B is 1.5. The T-bill rate is currently 6%, while the expected rate of return of the S&P 500 Index is 12%. The standard deviation of portfolio A is 10% annually, while that of B is 31%, and that of the index is 20%. a. If you currently hold a market index portfolio, would you choose to add either of these portfolios to your holdings? Explain. b. If instead you could invest only in bills and one of these portfolios, which would you choose? 21. Consider the following data for a one-factor economy. All portfolios are well diversified. Portfolio

E(r)

Beta

A F

10% 4

1.0 0

Suppose another portfolio E is well diversified with a beta of 2/3 and expected return of 9%. Would an arbitrage opportunity exist? If so, what would the arbitrage strategy be? 22. Following is a scenario for three stocks constructed by the security analysts of PF Inc.

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Scenario Rate of Return (%) Stock

Price ($)

Recession

Average

Boom

A B C

10 15 50

⫺15 25 12

20 10 15

30 ⫺10 12

a. Construct an arbitrage portfolio using these stocks. b. How might these prices change when equilibrium is restored? Give an example where a change in stock C’s price is sufficient to restore equilibrium, assuming the dollar payoffs to stock C remain the same. 23. Assume both portfolios A and B are well diversified, that E(rA) ⫽ 14% and E(rB) ⫽ 14.8%. If the economy has only one factor, and A ⫽ 1.0 while B ⫽ 1.1, what must be the risk-free rate? 24. Assume a market index represents the common factor, and all stocks in the economy have a beta of 1.0. Firm-specific returns all have a standard deviation of 30%. Suppose an analyst studies 20 stocks and finds that one-half have an alpha of 3%, and one-half have an alpha of ⫺3%. The analyst then buys $1 million of an equally weighted portfolio of the positive alpha stocks and sells short $1 million of an equally weighted portfolio of the negative alpha stocks. a. What is the expected profit (in dollars), and what is the standard deviation of the analyst’s profit? b. How does your answer change if the analyst examines 50 stocks instead of 20? 100 stocks? 25. If the APT is to be a useful theory, the number of systematic factors in the economy must be small. Why?

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Portfolio

Beta on M1

Beta on M2

Expected Return (%)

A B

1.8 2.0

2.1 ⫺0.5

40 10

What is the expected return–beta relationship in this economy? 29. The security market line depicts: a. A security’s expected return as a function of its systematic risk. b. The market portfolio as the optimal portfolio of risky securities. c. The relationship between a security’s return and the return on an index. d. The complete portfolio as a combination of the market portfolio and the risk-free asset. 30. Within the context of the capital asset pricing model (CAPM), assume: • Expected return on the market ⫽ 15%. • Risk-free rate ⫽ 8%. • Expected rate of return on XYZ security ⫽ 17%. • Beta of XYZ security ⫽ 1.25. Which one of the following is correct? a. XYZ is overpriced. b. XYZ is fairly priced. c. XYZ’s alpha is ⫺.25%. d. XYZ’s alpha is .25%. 31. What is the expected return of a zero-beta security? a. Market rate of return. b. Zero rate of return. d. Negative rate of return. d. Risk-free rate of return. 32. Capital asset pricing theory asserts that expected returns are best explained by: a. Economic factors b. Specific risk c. Systematic risk d. Diversification 33. According to CAPM, the expected rate of return of a portfolio with a beta of 1.0 and an alpha of 0 is: a. Between rM and rf . b. The risk-free rate, rf .

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26. The APT itself does not provide information on the factors that one might expect to determine risk premiums. How should researchers decide which factors to investigate? Is industrial production a reasonable factor to test for a risk premium? Why or why not? 27. Suppose two factors are identified for the U.S. economy: the growth rate of industrial production, IP, and the inflation rate, IR. IP is expected to be 4% and IR 6%. A stock with a beta of 1.0 on IP and 0.4 on IR currently is expected to provide a rate of return of 14%. If industrial production actually grows by 5%, while the inflation rate turns out to be 7%, what is your best guess for the rate of return on the stock? 28. Suppose there are two independent economic factors, M1 and M2. The risk-free rate is 7%, and all stocks have independent firm-specific components with a standard deviation of 50%. Portfolios A and B are both well diversified.

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c. (rM ⫺ rf). d. The expected return on the market, rM. The following table shows risk and return measures for two portfolios.

Portfolio

Average Annual Rate of Return

Standard Deviation

Beta

R S&P 500

11% 14%

10% 12%

0.5 1.0

34. When plotting portfolio R on the preceding table relative to the SML, portfolio R lies: a. On the SML. b. Below the SML. c. Above the SML. d. Insufficient data given. 35. When plotting portfolio R relative to the capital market line, portfolio R lies: a. On the CML. b. Below the CML. c. Above the CML. d. Insufficient data given. 36. Briefly explain whether investors should expect a higher return from holding portfolio A versus portfolio B under capital asset pricing theory (CAPM). Assume that both portfolios are fully diversified.

Systematic risk (beta) Specific risk for each individual security

Portfolio A

Portfolio B

1.0

1.0

High

Low

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37. Assume that both X and Y are well-diversified portfolios and the risk-free rate is 8%. Portfolio

Expected Return

Beta

X Y

16% 12%

1.00 0.25

In this situation you could conclude that portfolios X and Y: a. Are in equilibrium. b. Offer an arbitrage opportunity. c. Are both underpriced. d. Are both fairly priced. 38. According to the theory of arbitrage: a. High-beta stocks are consistently overpriced. b. Low-beta stocks are consistently overpriced. c. Positive alpha investment opportunities will quickly disappear. d. Rational investors will pursue arbitrage consistent with their risk tolerance.

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39. A zero-investment portfolio with a positive alpha could arise if: a. The expected return of the portfolio equals zero. b. The capital market line is tangent to the opportunity set. c. The law of one price remains unviolated. d. A risk-free arbitrage opportunity exists. 40. The APT differs from the single-factor CAPM because the APT: a. Places more emphasis on market risk. b. Minimizes the importance of diversification. c. Recognizes multiple unsystematic risk factors. d. Recognizes multiple systematic risk factors. 41. An investor takes as large a position as possible when an equilibrium price relationship is violated. This is an example of: a. A dominance argument. b. The mean-variance efficient frontier. c. Arbitrage activity. d. The capital asset pricing model. 42. The feature of APT that offers the greatest potential advantage over the simple CAPM is the: a. Identification of anticipated changes in production, inflation, and term structure of interest rates as key factors explaining the risk-return relationship. b. Superior measurement of the risk-free rate of return over historical time periods. c. Variability of coefficients of sensitivity to the APT factors for a given asset over time. d. Use of several factors instead of a single market index to explain the risk-return relationship. 43. In contrast to the capital asset pricing model, arbitrage pricing theory: a. Requires that markets be in equilibrium. b. Uses risk premiums based on micro variables. c. Specifies the number and identifies specific factors that determine expected returns. d. Does not require the restrictive assumptions concerning the market portfolio.

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STANDARD & POOR’S 1.

In the previous chapter, you used data from Market Insight to calculate the beta of Apple Computer (AAPL). Now let’s compute the alpha of the stock in two consecutive periods. Estimate the index model regression using the first two years of monthly data. (You can get monthly T-bill rates to calculate excess returns from the Federal Reserve website at http://www.federalreserve.gov/releases/h15/data. htm.) The intercept of the regression is Apple’s alpha over that 2-year period. Now repeat this exercise using the next two years of monthly data. This will give you alpha and beta estimates for two consecutive time periods. Finally, repeat this regression exercise for several (e.g., a dozen) other firms.

2.

Given your results for question 1, we can now investigate the extent to which beta in one period predicts beta in future periods and whether alpha in one period predicts alpha in future periods. Regress the beta of each firm in the second period against the beta in the first period. (If you estimated regressions for a dozen firms in question 1, you will have 12 observations in this regression.) Do the same for the alphas of each firm.

3.

We would expect that beta in the first period predicts beta in the next period, but that alpha in the first period has no power to predict alpha in the next period. (The regression coefficient on first-period beta will be statistically significant, but the coefficient on alpha will not be.) Why does this expectation make sense? Is it borne out by the data?

WEBMA STER Beta Coefficients

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Go to www.mhhe.com/edumarketinsight. Click on Monthly Valuation Data. The report summarizes seven months of data related to stock market activity and contains several comparison reports to the market indexes. Pull the monthly valuation data for General Electric, The Home Depot, Johnson and Johnson, Honeywell, and H.J. Heinz. After reviewing the reports, answer the following questions: 1.

Which of the firms are low-beta firms?

2.

Does the beta coefficient for these low-beta firms make sense given what type of firms they are? Briefly explain.

3.

Describe the variation in the reported beta coefficients over the seven months of data.

SOLUTIONS TO 1. The CML would still represent efficient investments. We can characterize the entire population by

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two representative investors. One is the “uninformed” investor, who does not engage in security analysis and holds the market portfolio, while the other optimizes using the Markowitz algorithm with input from security analysis. The uninformed investor does not know what input the informed investor uses to make portfolio purchases. The uninformed investor knows, however, that if the other investor is informed, the market portfolio proportions will be optimal. Therefore, to depart from these proportions would constitute an uninformed bet, which will, on average, reduce the efficiency of diversification with no compensating improvement in expected returns.

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2. Substituting the historical mean and standard deviation in Equation 7.1 yields a coefficient of risk aversion of A* ⫽

E(rM) ⫺ rf M2

⫽

.085 0.202

⫽ 2.1

This relationship also tells us that for the historical standard deviation and a coefficient of risk aversion of 3.5, the risk premium would be E(rM) ⫺ rf ⫽ A*M2 ⫽ 3.5 ⫻ 0.202 ⫽ 0.14 ⫽ 14% 3. Ford ⫽ 1.25, GM ⫽ 1.15. Therefore, given the investment proportions, the portfolio beta is P ⫽ wFordFord ⫹ wGMGM ⫽ (0.75 ⫻ 1.25) ⫹ (0.25 ⫻ 1.15) ⫽ 1.225 and the risk premium of the portfolio will be E(rP) ⫺ rf ⫽ P[E(rM) ⫺ rf] ⫽ 1.225 ⫻ 8% ⫽ 9.8% 4. a. The alpha of a stock is its expected return in excess of that required by the CAPM. ␣ ⫽ E(r) ⫺ {rf ⫹ [E(rM) ⫺ rf]} ␣XYZ ⫽ 12 ⫺ [5 ⫹ 1.0(11 ⫺ 5)] ⫽ 1 ␣ABC ⫽ 13 ⫺ [5 ⫹ 1.5(11 ⫺ 5)] ⫽ ⫺ 1% b. The project-specific required rate of return is determined by the project beta coupled with the market risk premium and the risk-free rate. The CAPM tells us that an acceptable expected rate of return for the project is rf ⫹ [E(rM) ⫺ rf] ⫽ 8 ⫹ 1.3(16 ⫺ 8) ⫽ 18.4% which becomes the project’s hurdle rate. If the IRR of the project is 19%, then it is desirable. Any project (of similar beta) with an IRR less than 18.4% should be rejected.

Stock

Dollar Investment

Apex Bull Crush Dreck

$

985,714 985,714 985,714 ⫺2,957,142

Total

$

Rate of Return (%)

Dollar Return

20 70 ⫺20 NA*

$ 197,143 690,000 ⫺197,143 ⫺690,000

0

$

0

*The dollar return on Dreck is assumed to be held fixed as its price falls. Therefore, Dreck’s rate of return will depend on the price to which its stock price falls, but in any case the rate of return is not necessary to answer the question.

At any price for Dreck stock below $10 ⫻ (1 ⫺ 1/70) ⫽ $9.857, profits will be negative, which means the arbitrage opportunity is eliminated. Note: $9.857 is not the equilibrium price of Dreck. It is simply the upper bound on Dreck’s price that rules out the simple arbitrage opportunity. 6. Using Equation 7.8, the expected return is 4 ⫹ (0.2 ⫻ 6) ⫹ (1.4 ⫻ 8) ⫽ 16.4%

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5. The least profitable scenario currently yields a profit of $10,000 and gross proceeds from the equally weighted portfolio of $700,000. As the price of Dreck falls, less of the equally weighted portfolio can be purchased from the proceeds of the short sale. When Dreck’s price falls by more than a factor of 10,000/700,000, arbitrage no longer will be feasible, because the profits in the worst state will be driven below zero. To see this, suppose Dreck’s price falls to $10 ⫻ (1 ⫺ 1/70). The short sale of 300,000 shares now yields $2,957,142, which allows dollar investments of only $985,714 in each of the other shares. In the high real interest rate, low inflation scenario, profits will be driven to zero.

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8 THE EFFICIENT MARKET HYPOTHESIS

AFTER STUDYING THIS CHAPTER YOU SHOULD BE ABLE TO:

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260

Demonstrate why security price movements should be essentially unpredictable. Cite evidence that supports and contradicts the efficient market hypothesis. Formulate investment strategies that make sense in informationally efficient markets.

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Related Websites http://www.efficientfrontier.com This site has an online journal entitled Efficient Frontier: An Online Journal of Practical Asset Allocation. The journal contains short articles related to assessment of strategies.

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http://my.zacks.com http://www.wsrn.com http://www.corporateinformation.com http://www.businessweek.com/investor

http://www.superstarinvestor.com/index.html

These sites contain information related to market efficiency issues surrounding individual stocks as well as mutual funds.

This site contains many references to other sites that have data on technical and fundamental analysis as well as sites containing information on earnings and investor conference calls.

http://www.newyorkfed.org http://www.frbsf.org http://www.bos.frb.org These sites contain research reports and shorter summaries of articles with information on various aspects of market efficiency.

ne of the early applications of computers in economics in the 1950s was to analyze economic time series. Business cycle theorists believed tracing the evolution of several economic variables over time would clarify and predict the progress of the economy through boom and bust periods. A natural candidate for analysis was the behavior of stock market prices over time. Assuming stock prices reflect the prospects of the firm, recurring patterns of peaks and troughs in economic performance ought to show up in those prices. Maurice Kendall (1953) was one of the first to examine this proposition. He found to his great surprise that he could identify no predictable patterns in stock prices. Prices seemed to evolve randomly. They were as likely to go up as they were to go down on any particular day regardless of past performance. The data provided no way to predict price movements. At first blush, Kendall’s results disturbed some financial economists. They seemed to imply that the stock market is dominated by erratic market psychology, or “animal spirits,” and that it follows no logical rules. In short, the results appeared to confirm the irrationality of the market. On further reflection, however, economists reversed their interpretation of Kendall’s study. It soon became apparent that random price movements indicated a wellfunctioning or efficient market, not an irrational one. In this chapter, we will explore the reasoning behind what may seem to be a surprising conclusion. We show how competition among analysts leads naturally to market efficiency, and we examine the implications of the efficient market hypothesis for investment policy. We also consider empirical evidence that supports and contradicts the notion of market efficiency.

O

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The notion that stock price changes are random and unpredictable.

efficient market hypothesis The hypothesis that prices of securities fully reflect available information about securities.

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8.1

random walk

II. Portfolio Theory

RANDOM WALKS AND THE EFFICIENT MARKET HYPOTHESIS

Suppose Kendall had discovered that stock prices are predictable. Imagine the gold mine for investors! If they could use Kendall’s equations to predict stock prices, investors would reap unending profits simply by purchasing stocks the computer model implied were about to increase in price and selling those stocks about to fall in price. A moment’s reflection should be enough to convince you that this situation could not persist for long. For example, suppose the model predicts with great confidence that XYZ’s stock price, currently at $100 per share, will rise dramatically in three days to $110. All investors with access to the model’s prediction would place a great wave of immediate buy orders to cash in on the prospective increase in stock price. No one in the know holding XYZ, however, would be willing to sell, and the net effect would be an immediate jump in the stock price to $110. The forecast of a future price increase leads instead to an immediate price increase. Another way of putting this is that the stock price will immediately reflect the “good news” implicit in the model’s forecast. This simple example illustrates why Kendall’s attempts to find recurring patterns in stock price movements were in vain. A forecast about favorable future performance leads instead to favorable current performance, as market participants all try to get in on the action before the price jump. More generally, one could say that any publicly available information that might be used to predict stock performance, including information on the macroeconomy, the firm’s industry, and its operations, plans, and management, should already be reflected in stock prices. As soon as there is any information indicating a stock is underpriced and offers a profit opportunity, investors flock to buy the stock and immediately bid up its price to a fair level, where again only ordinary rates of return can be expected. These “ordinary rates” are simply rates of return commensurate with the risk of the stock. But if prices are bid immediately to fair levels, given all available information, it must be that prices increase or decrease only in response to new information. New information, by definition, must be unpredictable; if it could be predicted, then that prediction would be part of today’s information! Thus, stock prices that change in response to new (unpredictable) information also must move unpredictably. This is the essence of the argument that stock prices should follow a random walk, that is, that price changes should be random and unpredictable. Far from being a proof of market irrationality, randomly evolving stock prices are the necessary consequence of intelligent investors competing to discover relevant information before the rest of the market becomes aware of that information. Don’t confuse randomness in price changes with irrationality in the level of prices. If prices are determined rationally, then only new information will cause them to change. Therefore, a random walk would be the natural consequence of prices that always reflect all current knowledge. Indeed, if stock price movements were predictable, that would be damning evidence of stock market inefficiency, because the ability to predict prices would indicate that all available information was not already impounded in stock prices. Therefore, the notion that stocks already reflect all available information is referred to as the efficient market hypothesis (EMH). Figure 8.1 illustrates the response of stock prices to new information in an efficient market. The graph plots the price response of a sample of 194 firms that were targets of takeover attempts. In most takeovers, the acquiring firm pays a substantial premium over current market prices. Therefore, announcement of a takeover attempt should cause the stock price to jump.

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The Efficient Market Hypothesis

F I G U R E 8.1

Cumulative abnormal return, % 36

Cumulative abnormal returns surrounding takeover attempts: Target companies. Returns are adjusted to net out effects of broad market movements.

32 28 24 20 16

Source: Arthur Keown and John Pinkerton, “Merger Announcements and Insider Trading Activity,” Journal of Finance 36 (September 1981).

12 8 4 0 ⫺4 ⫺8 ⫺12 ⫺16 ⫺135 ⫺120 ⫺105

263

⫺90 ⫺75 ⫺60 ⫺45 ⫺30 ⫺15 Days relative to announcement date

0

15

30

The figure shows that stock prices jump dramatically on the day the news becomes public. However, there is no further drift in prices after the announcement date, suggesting that prices reflect the new information, including the likely magnitude of the takeover premium, by the end of the trading day. An even more dramatic demonstration of the speed of price response appears in Figure 8.2. Suppose that you bought shares of firms announcing positive earnings surprises and sold short shares of firms with negative earnings surprises. (A positive surprise is defined as earnings that exceed the prior forecast published by the Value Line Investment Survey.) The figure tracks the average profits to this strategy for each half-hour period following the public announcement. The figure demonstrates that the vast majority of the profits to this strategy would be realized in the first half-hour following the announcement. Only 30 minutes after the public announcement, it is virtually too late to profitably trade on the information, suggesting that the market responds to the news within that short time period.

Competition as the Source of Efficiency Why should we expect stock prices to reflect all available information? After all, if you were to spend time and money gathering information, you would hope to turn up something that had been overlooked by the rest of the investment community. When information costs you money to uncover and analyze, you expect your investment analysis to result in an increased expected return. Investors will have an incentive to spend time and resources to analyze and uncover new information only if such activity is likely to generate higher investment returns. Therefore, in

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F I G U R E 8.2

25

Returns following earnings announcements

20

Note: Only the return in the first 30 minutes was statistically significantly different from that of a control sample at 5 or 10% confidence levels. Source: James M. Patell and Mark A. Wolfson, “The Intraday Speed of Stock Prices to Earnings and Dividend Announcements,” Journal of Financial Economics, June 1984, pp. 223–52.

Return (%)

15 10 5 0

0–30

30–60

60–90

90–120 120–150 150–180

⫺5 ⫺10 Minutes since public announcement

market equilibrium, efficient informational gathering activity should be fruitful.1 Moreover, it would not be surprising to find that the degree of efficiency across various markets may differ. For example, emerging markets, which are less intensively analyzed than U.S. markets and in which information is harder to come by, may be less efficient than U.S. markets. Small stocks, which receive less coverage by Wall Street analysts, may be less efficiently priced than large ones. Still, while we would not go so far as to say you absolutely cannot come up with new information, it makes sense to consider and respect your competition. Assume an investment management firm is managing a $5 billion portfolio. Suppose the fund manager can devise a research program that could increase the portfolio rate of return by one-tenth of 1% per year, a seemingly modest amount. This program would increase the dollar return to the portfolio by $5 billion ⫻ .001, or $5 million. Therefore, the fund is presumably willing to spend up to $5 million per year on research to increase stock returns by a mere one-tenth of 1% per year. With such large rewards for such small increases in investment performance, is it any surprise that professional portfolio managers are willing to spend large sums on industry analysts, computer support, and research effort? With so many well-backed analysts willing to spend considerable resources on research, there cannot be many easy pickings in the market. Moreover, the incremental rates of return on research activity are likely to be so small that only managers of the largest portfolios will find them worth pursuing. While it may not literally be true that all relevant information will be uncovered, it is virtually certain there are many investigators hot on the trail of any leads that seem likely to improve investment performance. Competition among these many well-backed, highly paid, aggressive analysts ensures that, as a general rule, stock prices ought to reflect available information regarding their proper levels.

1

A challenging and insightful discussion of this point may be found in Sanford J. Grossman and Joseph E. Stiglitz, “On the Impossibility of Informationally Efficient Markets,” American Economic Review 70 (June 1980).

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The Efficient Market Hypothesis

Versions of the Efficient Market Hypothesis It is common to distinguish among three versions of the EMH: the weak, the semistrong, and the strong forms of the hypothesis. These versions differ according to their notions of what is meant by the term all available information. The weak-form EMH asserts that stock prices already reflect all information that can be derived by examining market trading data such as the history of past prices, trading volume, or short interest. This version of the hypothesis implies that trend analysis is fruitless. Past stock price data are publicly available and virtually costless to obtain. The weak-form hypothesis holds that if such data ever conveyed reliable signals about future performance, all investors would have learned long since to exploit the signals. Ultimately, the signals lose their value as they become widely known, because a buy signal, for instance, would result in an immediate price increase. The semistrong-form EMH states that all publicly available information regarding the prospects of a firm must be already reflected in the stock price. Such information includes, in addition to past prices, fundamental data on the firm’s product line, quality of management, balance sheet composition, patents held, earnings forecasts, accounting practices, and so forth. Again, if any investor has access to such information from publicly available sources, one would expect it to be reflected in stock prices. Finally, the strong-form EMH states that stock prices reflect all information relevant to the firm, even including information available only to company insiders. This version of the hypothesis is quite extreme. Few would argue with the proposition that corporate officers have access to pertinent information long enough before public release to enable them to profit from trading on that information. Indeed, much of the activity of the Securities and Exchange Commission (SEC) is directed toward preventing insiders from profiting by exploiting their privileged situation. Rule 10b-5 of the Security Exchange Act of 1934 limits trading by corporate officers, directors, and substantial owners, requiring them to report trades to the SEC. Anyone trading on information supplied by insiders is considered in violation of the law. Defining insider trading is not always easy, however. After all, stock analysts are in the business of uncovering information not already widely known to market participants. As we saw in Chapter 3, the distinction between private and inside information is sometimes murky. 1. a. Suppose you observed that high-level managers were making superior returns on investments in their company’s stock. Would this be a violation of weakform market efficiency? Would it be a violation of strong-form market efficiency? b. If the weak form of the efficient market hypothesis is valid, must the strong form also hold? Conversely, does strong-form efficiency imply weak-form efficiency?

8.2

IMPLICATIONS OF THE EMH

Technical Analysis Technical analysis is essentially the search for recurring and predictable patterns in stock prices. Although technicians recognize the value of information that has to do with future economic prospects of the firm, they believe such information is not necessary for a successful trading

weak-form EMH The assertion that stock prices already reflect all information contained in the history of past trading.

semistrongform EMH The assertion that stock prices already reflect all publicly available information.

strong-form EMH The assertion that stock prices reflect all relevant information, including inside information.

2. What would happen to market efficiency if all investors attempted to follow a passive strategy?

The Role of Portfolio Management in an Efficient Market If the market is efficient, why not throw darts at The Wall Street Journal instead of trying to choose a stock portfolio rationally? It’s tempting to draw this sort of conclusion from the notion that security prices are fairly set, but it’s a far too simple one. There is a role for rational portfolio management, even in perfectly efficient markets. A basic principle in portfolio selection is diversification. Even if all stocks are priced fairly, each still poses firm-specific risk that can be eliminated through diversification. Therefore, rational security selection, even in an efficient market, calls for the selection of a carefully diversified portfolio. Moreover, that portfolio should provide the systematic risk level the investor wants. Even in an efficient market, investors must choose the risk-return profiles they deem appropriate. Rational investment policy also requires that investors take tax considerations into account in security choice. If you are in a high tax bracket, you generally will not want the same securities that low-bracket investors find favorable. At an obvious level, high-bracket investors find it advantageous to buy tax-exempt municipal bonds despite their relatively low pretax yields, while those same bonds are unattractive to low-bracket investors. At a more subtle level, high-bracket investors might want to tilt or specialize their portfolios toward securities that provide capital gains as opposed to dividend or interest income, because capital gains are taxed less heavily, and the option to defer the realization of capital gains income is more valuable, the higher the investor’s current tax bracket. High tax bracket investors also will be more attracted to investment opportunities where returns are sensitive to tax benefits, such as real estate ventures. A third argument for rational portfolio management relates to the particular risk profile of the investor. For example, a General Motors executive whose annual bonus depends on GM’s profits generally should not invest additional amounts in auto stocks. To the extent that his or her compensation already depends on GM’s well-being, the executive is overinvested in GM now and should not exacerbate the lack of diversification. Investors of varying ages also might warrant different portfolio policies with regard to risk bearing. For example, older investors who are essentially living off savings might avoid longterm bonds, whose market values fluctuate dramatically with changes in interest rates. Because these investors rely on accumulated savings, they require conservation of principal. In contrast, younger investors might be more inclined toward long-term inflation-indexed bonds. The steady flow of real income over long periods that is locked in with these bonds can be more important than preservation of principal to those with long life expectancies. In short, there is a role for portfolio management even in an efficient market. Investors’ optimal positions will vary according to factors such as age, tax bracket, risk aversion, and employment. The role of the portfolio manager in an efficient market is to tailor the portfolio to these needs, rather than to attempt to beat the market.

Resource Allocation We’ve focused so far on the investment implications of the efficient market hypothesis. Deviations from efficiency may offer profit opportunities to better-informed traders at the expense of less-informed traders.

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The Efficient Market Hypothesis

However, deviations from informational efficiency would also result in a large cost that will be borne by all citizens, namely, inefficient resource allocation. Recall that in a capitalist economy, investments in real assets such as plant, equipment, and know-how are guided in large part by the prices of financial assets. For example, if the values of biotech assets as reflected in the stock market prices of biotech firms exceed the cost of acquiring those assets, the managers of such firms have a strong signal that further investments in the firm will be regarded by the market as a positive net present value venture. In this manner, capital market prices guide resource allocation. Security mispricing thus could entail severe social costs by fostering inappropriate investments on the real side of the economy. Section 7.1 demonstrates how security analysis impounds information into security prices. To the extend that only part of this information is reflected in prices, corporations with overpriced securities will be able to obtain capital too cheaply and corporations with undervalued securities might forego investment opportunities because the cost of raising capital will be too high. Therefore, inefficient capital markets will diminish one of the most potent benefits of a market economy.

8.3

ARE MARKETS EFFICIENT?

The Issues Not surprisingly, the efficient market hypothesis is not enthusiastically hailed by professional portfolio managers. It implies that a great deal of the activity of portfolio managers—the search for undervalued securities—is at best wasted effort and possibly harmful to clients because it costs money and leads to imperfectly diversified portfolios. Consequently, the EMH has never been widely accepted on Wall Street, and debate continues today on the degree to which security analysis can improve investment performance. Before discussing empirical tests of the hypothesis, we want to note three factors that together imply the debate probably never will be settled: the magnitude issue, the selection bias issue, and the lucky event issue.

The magnitude issue We noted that an investment manager overseeing a $5 billion portfolio who can improve performance by only one-tenth of 1% per year will increase investment earnings by .001 ⫻ $5 billion ⫽ $5 million annually. This manager clearly would be worth her salary! Yet we, as observers, probably cannot statistically measure her contribution. A onetenth of 1% contribution would be swamped by the yearly volatility of the market. Remember, the annual standard deviation of the well-diversified S&P 500 index has been approximately 20% per year. Against these fluctuations, a small increase in performance would be hard to detect. Nevertheless, $5 million remains an extremely valuable improvement in performance. All might agree that stock prices are very close to fair values, and that only managers of large portfolios can earn enough trading profits to make the exploitation of minor mispricing worth the effort. According to this view, the actions of intelligent investment managers are the driving force behind the constant evolution of market prices to fair levels. Rather than ask the qualitative question, Are markets efficient? we ought instead to ask the quantitative question, How efficient are markets? The selection bias issue Suppose you discover an investment scheme that could really make money. You have two choices: Either publish your technique in The Wall Street Journal to win fleeting fame or keep your technique secret and use it to earn millions of dollars. Most investors would choose the latter option, which presents us with a conundrum. Only investors who find that an investment scheme cannot generate abnormal returns will be willing to report their findings to the whole world. Hence, opponents of the efficient market’s view of the world always can use evidence that various techniques do not provide investment

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rewards as proof that the techniques that do work simply are not being reported to the public. This is a problem in selection bias; the outcomes we are able to observe have been preselected in favor of failed attempts. Therefore, we cannot fairly evaluate the true ability of portfolio managers to generate winning stock market strategies.

The lucky event issue In virtually any month, it seems we read an article in The Wall Street Journal about some investor or investment company with a fantastic investment performance over the recent past. Surely the superior records of such investors disprove the efficient market hypothesis. This conclusion is far from obvious, however. As an analogy to the “contest” among portfolio managers, consider a contest to flip the most heads out of 50 trials using a fair coin. The expected outcome for any person is 50% heads and 50% tails. If 10,000 people, however, compete in this contest, it would not be surprising if at least one or two contestants flipped more than 75% heads. In fact, elementary statistics tells us that the expected number of contestants flipping 75% or more heads would be two. It would be silly, though, to crown these people the head-flipping champions of the world. They are simply the contestants who happened to get lucky on the day of the event (see the nearby box). The analogy to efficient markets is clear. Under the hypothesis that any stock is fairly priced given all available information, any bet on a stock is simply a coin toss. There is equal likelihood of winning or losing the bet. Yet, if many investors using a variety of schemes make fair bets, statistically speaking, some of those investors will be lucky and win a great majority of bets. For every big winner, there may be many big losers, but we never hear of these managers. The winners, though, turn up in The Wall Street Journal as the latest stock market gurus; then they can make a fortune publishing market newsletters. Our point is that after the fact there will have been at least one successful investment scheme. A doubter will call the results luck; the successful investor will call it skill. The proper test would be to see whether the successful investors can repeat their performance in another period, yet this approach is rarely taken. With these caveats in mind, we now turn to some of the empirical tests of the efficient market hypothesis.

Concept CHECK

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3. Fidelity’s Magellan Fund outperformed the S&P 500 in 11 of the 13 years that Peter Lynch managed the fund, resulting in an average annual return for this period more than 10% better than that of the index. Is Lynch’s performance sufficient to cause you to doubt the efficient markets theory? If not, would any performance record be sufficient to dissuade you?

Weak-Form Tests: Predictability in Stock Returns Returns over short horizons Early tests of efficient markets were tests of the weak form. Could speculators find trends in past prices that would enable them to earn abnormal profits? This is essentially a test of the efficacy of technical analysis. The already-cited work of Kendall and of Roberts (1959), both of whom analyzed the possible existence of patterns in stock prices, suggests that such patterns are not to be found. One way of discerning trends in stock prices is by measuring the serial correlation of stock market returns. Serial correlation refers to the tendency for stock returns to be related to past returns. Positive serial correlation means that positive returns tend to follow positive returns (a momentum type of property). Negative serial correlation means that positive returns tend to be followed by negative returns (a reversal or “correction” property). Both Conrad and Kaul (1988) and Lo and MacKinlay (1988) examine weekly returns of NYSE stocks and find positive serial correlation over short horizons. However, the correlation

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How to Guarantee Successful Market Timing Suppose you want to make your fortune publishing a market newsletter. You need first to convince potential subscribers that you have talent worth paying for. But what if you have no market prediction talent? The solution is simple: Start eight market newsletters. In year one, let four of your newsletters predict an up market and four a down market. In year two, let half of the originally optimistic group of newsletters continue to predict an up market and the other half a down market. Do the same for the originally pessimistic group. Continue in this manner to obtain the following pattern of predictions (U ⫽ prediction of an up market, D ⫽ prediction of a down market). After three years, no matter what has happened to the market, one of the newsletters would have had a perfect prediction record. This is because after three years, there are 23 ⫽ 8 outcomes for the market, and we’ve covered all eight possibilities with the eight letters. Now, we simply slough off the seven unsuccessful newsletters and market the eighth letter based on its perfect track record. If we want to establish a letter with a perfect track record over a four-year period, we need 24 ⫽ 16 newsletters. A five-year period requires 32 newsletters, and so on.

After the fact, the one newsletter that was always right will attract attention for your uncanny foresight and investors will rush to pay large fees for its advice. Your fortune is made, and you never even researched the market! WARNING: This scheme is illegal! The point, however, is that with hundreds of market newsletters, you can find one that has stumbled onto an apparently remarkable string of successful predictions without any real degree of skill. After the fact, someone’s prediction history can seem to imply great forecasting skill. This person is the one we will read about in The Wall Street Journal; the others will be forgotten. Newsletter Predictions Year

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coefficients of weekly returns tend to be fairly small, at least for large stocks for which price data are the most reliably up-to-date. Thus, while these studies demonstrate price trends over short periods, the evidence does not clearly suggest the existence of trading opportunities. A more sophisticated version of trend analysis is a filter rule. A filter technique gives a rule for buying or selling a stock depending on past price movements. One rule, for example, might be: “Buy if the last two trades each resulted in a stock price increase.” A more conventional one might be: “Buy a security if its price increased by 1%, and hold it until its price falls by more than 1% from the subsequent high.” Alexander (1964) and Fama and Blume (1966) found that such filter rules generally could not generate trading profits. These very short-horizon studies offer the suggestion of momentum in stock market prices, albeit of a magnitude that may be too small to exploit. However, in an investigation of intermediate horizon stock price behavior (using 3- to 12-month holding periods), Jegadeesh and Titman (1993) found that stocks exhibit a momentum property in which good or bad recent performance continues. They conclude that while the performance of individual stocks is highly unpredictable, portfolios of the best-performing stocks in the recent past appear to outperform other stocks with enough reliability to offer profit opportunities.

filter rule A rule for buying or selling stock according to recent price movements.

Returns over long horizons While studies of short-horizon returns have detected minor positive serial correlation in stock market prices, tests2 of long-horizon returns (that is, returns over multiyear periods) have found suggestions of pronounced negative long-term serial 2 Eugene F. Fama and Kenneth R. French, “Permanent and Temporary Components of Stock Prices,” Journal of Political Economy 96 (April 1988), pp. 246–73; James Poterba and Lawrence Summers, “Mean Reversion in Stock Prices: Evidence and Implications,” Journal of Financial Economics 22 (October 1988), pp. 27–59.

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correlation. The latter result has given rise to a “fads hypothesis,” which asserts that stock prices might overreact to relevant news. Such overreaction leads to positive serial correlation (momentum) over short time horizons. Subsequent correction of the overreaction leads to poor performance following good performance and vice versa. The corrections mean that a run of positive returns eventually will tend to be followed by negative returns, leading to negative serial correlation over longer horizons. These episodes of apparent overshooting followed by correction give stock prices the appearance of fluctuating around their fair values and suggest that market prices exhibit excessive volatility compared to intrinsic value.3 These long-horizon results are dramatic, but the studies offer far from conclusive evidence regarding efficient markets. First, the study results need not be interpreted as evidence for stock market fads. An alternative interpretation of these results holds that they indicate only that market risk premiums vary over time: The response of market prices to variation in the risk premium can lead one to incorrectly infer the presence of mean reversion and excess volatility in prices. For example, when the risk premium and the required return on the market rises, stock prices will fall. When the market then rises (on average) at this higher rate of return, the data convey the impression of a stock price recovery. The impression of overshooting and correction is in fact no more than a rational response of market prices to changes in discount rates. Second, these studies suffer from statistical problems. Because they rely on returns measured over long time periods, these tests of necessity are based on few observations of longhorizon returns.

reversal effect The tendency of poorly performing stocks and wellperforming stocks in one period to experience reversals in the following period.

Reversals While some of the studies just cited suggest momentum in stock market prices over short horizons (of less than one year), other studies suggest that over longer horizons, extreme stock market performance tends to reverse itself: The stocks that have performed best in the recent past seem to underperform the rest of the market in the following periods, while the worst past performers tend to offer above-average future performance. DeBondt and Thaler (1985) and Chopra, Lakonishok, and Ritter (1992) find strong tendencies for poorly performing stocks in one period to experience sizable reversals over the subsequent period, while the best-performing stocks in a given period tend to follow with poor performance in the following period. For example, the DeBondt and Thaler study found that if one were to rank order the performance of stocks over a five-year period and then group stocks into portfolios based on investment performance, the base-period “loser” portfolio (defined as the 35 stocks with the worst investment performance) would outperform the “winner” portfolio (the top 35 stocks) by an average of 25% (cumulative return) in the following three-year period. This reversal effect, in which losers rebound and winners fade back, seems to suggest that the stock market overreacts to relevant news. After the overreaction is recognized, extreme investment performance is reversed. This phenomenon would imply that a contrarian investment strategy— investing in recent losers and avoiding recent winners—should be profitable. Moreover, these returns seem pronounced enough to be exploited profitably. The reversal effect also seems to depend on the time horizon of the investment. While DeBondt and Thaler (1992) found reversals over long (multiyear) horizons, and studies by Jegadeesh (1990) and Lehmann (1990) documented reversals over short horizons of a month 3

The fads debate started as a controversy over whether stock prices exhibit excess volatility. See Robert J. Shiller, “Do Stock Prices Move Too Much to Be Justified by Subsequent Changes in Dividends?” American Economic Review 71 (June 1971), pp. 421–36. However, it is now apparent that excess volatility and fads are essentially different ways of describing the same phenomenon.

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or less, we note above that an investigation of intermediate-term stock price behavior (using 3- to 12-month holding periods) by Jegadeesh and Titman (1993) found that stocks exhibit a momentum property in which good or bad recent performance continues. This of course is the opposite of a reversal phenomenon. Thus it appears that there may be short-run momentum but long-run reversal patterns in price behavior. One interpretation of these patterns is that short-run overreaction (which causes momentum in prices) may lead to long-term reversals (when the market recognizes and corrects its past errors). This interpretation is emphasized by Haugen (1995).

Predictors of Broad Market Movements Several studies have documented the ability of easily observed variables to predict market returns. For example, Fama and French (1988) show that the return on the aggregate stock market tends to be higher when the dividend/price ratio, or the dividend yield, is high. Campbell and Shiller (1988) find that the earnings yield can predict market returns. Keim and Stambaugh (1986) show that bond market data such as the spread between yields on high- and lowgrade corporate bonds also help predict broad market returns. Again, the interpretation of these results is difficult. On the one hand, they may imply that stock returns can be predicted, in violation of the efficient market hypothesis. More probably, however, these variables are proxying for variation in the market risk premium. For example, given a level of dividends or earnings, stock prices will be lower and dividend and earnings yields will be higher when the risk premium (and therefore the expected market return) is larger. Thus, a high dividend or earnings yield will be associated with higher market returns. This does not indicate a violation of market efficiency. The predictability of market returns is due to predictability in the risk premium, not in risk-adjusted abnormal returns. Fama and French (1989) show that the yield spread between high- and low-grade bonds has greater predictive power for returns on low-grade bonds than for returns on high-grade bonds, and greater predictive power for stock returns than for bond returns, suggesting that the predictability in returns is in fact a risk premium rather than evidence of market inefficiency. Similarly, the fact that the dividend yield on stocks helps to predict bond market returns suggests that the yield captures a risk premium common to both markets rather than mispricing in the equity market.

Semistrong-Form Tests: Market Anomalies Fundamental analysis uses a much wider range of information to create portfolios than does technical analysis. Investigations of the efficacy of fundamental analysis ask whether publicly available information beyond the trading history of a security can be used to improve investment performance and, therefore, are tests of semistrong-form market efficiency. Surprisingly, several easily accessible statistics, for example a stock’s price–earnings ratio or its market capitalization, seem to predict abnormal risk-adjusted returns. Findings such as these, which we will review in the following pages, are inconsistent with the efficient market hypothesis and, therefore, are often referred to as market anomalies. A difficulty in interpreting these tests is that we usually need to adjust for portfolio risk before evaluating the success of an investment strategy. For example, many tests use the CAPM to adjust for risk. However, we know that even if beta is a relevant descriptor of stock risk, the empirically measured quantitative trade-off between risk as measured by beta and expected return differs from the predictions of the CAPM. If we use the CAPM to adjust portfolio returns for risk, inappropriate adjustments might lead to the incorrect conclusion that various portfolio strategies can generate superior returns.

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P/E effect Portfolios of low P/E stocks have exhibited higher average riskadjusted returns than high P/E stocks.

small-firm effect Stocks of small firms have earned abnormal returns, primarily in the month of January.

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Tests of risk-adjusted returns are joint tests of the efficient market hypothesis and the risk adjustment procedure. If it appears that a portfolio strategy can generate superior returns, we then must choose between rejecting the EMH or rejecting the risk adjustment technique. Usually, the risk adjustment technique is based on more questionable assumptions than the EMH; if we reject the procedure, we are left with no conclusion about market efficiency. An example of this problem is the discovery by Basu (1977, 1983) that portfolios of low price/earnings ratio stocks have higher average returns than high P/E portfolios. The P/E effect holds up even if returns are adjusted for portfolio beta. Is this a confirmation that the market systematically misprices stocks according to the P/E ratio? This would be a surprising and, to us, disturbing conclusion, because analysis of P/E ratios is such a simple procedure. While it may be possible to earn superior returns using hard work and much insight, it hardly seems likely that following such a basic technique is enough to generate abnormal returns. One possible interpretation of these results is that the model of capital market equilibrium is at fault in that the returns are not properly adjusted for risk. This makes sense, since if two firms have the same expected earnings, then the riskier stock will sell at a lower price and lower P/E ratio. Because of its higher risk, the low P/E stock also will have higher expected returns. Therefore, unless the CAPM beta fully adjusts for risk, P/E will act as a useful additional descriptor of risk and will be associated with abnormal returns if the CAPM is used to establish benchmark performance.

The small-firm-in-January effect One of the most frequently cited anomalies with respect to the efficient market hypothesis is the so-called size or small-firm effect, originally documented by Banz (1981). Figure 8.3 illustrates the size effect. It shows the historical performance of portfolios formed by dividing the NYSE stocks into 10 portfolios each year according to firm size (i.e., the total value of outstanding equity). Average annual returns are consistently higher on the small-firm portfolios. The difference in average annual return between portfolio 10 (with the largest firms) and portfolio 1 (with the smallest firms) is 8.59%. Of course, the smaller-firm portfolios tend to be riskier. But even when returns are adjusted for risk by using the CAPM, there is still a consistent premium for the smaller-sized portfolios. Even on a risk-adjusted basis, the smallest-size portfolio outperforms the largest-firm portfolio by an average of 4.3% annually. This is a huge premium; imagine earning an extra return of this amount on a billion-dollar portfolio. Yet it is remarkable that following a simple (even simplistic) rule such as “invest in

Source: Stocks, Bonds, Bills, and Inflation 2000 Yearbook, Ibbotson Associates, 2000.

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F I G U R E 8.3 Returns in excess of risk-free rate and in excess of the Security Market Line for 10 size-based portfolios

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low capitalization stocks” should enable an investor to earn excess returns. After all, any investor can measure firm size costlessly. One would not expect such minimal effort to yield such large rewards. Later studies (Keim, 1983; Reinganum, 1983; and Blume and Stambaugh, 1983) showed that the small-firm effect occurs virtually entirely in the first two weeks of January. The size effect is in fact a small-firm-in-January effect. Some researchers believe the January effect is tied to tax-loss selling at the end of the year. The hypothesis is that many people sell stocks that have declined in price during the previous months to realize their capital losses before the end of the tax year. Such investors do not put the proceeds from these sales back into the stock market until after the turn of the year. At that point, the rush of demand for stock places an upward pressure on prices that results in the January effect. Finally, the January effect is said to show up most dramatically for the smallest firms because the small-firm group includes, as an empirical matter, stocks with the greatest variability of prices during the year. The group, therefore, includes a relatively large number of firms that have declined sufficiently to induce tax-loss selling. Some empirical evidence supports the belief that the January effect is connected to tax-loss selling. For example, Ritter (1988) shows that the ratio of stock purchases to sales by individual investors is below normal in late December and above normal in early January. This is consistent with tax-loss rebalancing. The fundamental question is why market participants do not exploit the January effect and thereby ultimately eliminate it by bidding stock prices to appropriate levels. One possible explanation lies in segmentation of the market into two groups: institutional investors who invest primarily in large firms and individual investors who invest disproportionately in smaller firms. According to this view, managers of large institutional portfolios are the moving force behind efficient markets. It is professionals who seek out profit opportunities and bid prices to their appropriate levels. Institutional investors do not seem to buy at the small-size end of the market, perhaps because of limits on allowed portfolio positions, so the small-firm anomaly persists without the force of their participation. 4. Does this market segmentation theory get the efficient market hypothesis off the hook, or are there still market mechanisms that, in theory, ought to eliminate the small-firm anomaly?

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Compute a bond’s price given its yield to maturity, and compute its yield to maturity given its price. Calculate how bond prices will change over time for a given interest rate projection. Identify the determinants of bond safety and rating. Analyze how call, convertibility, and sinking fund provisions will affect a bond’s equilibrium yield to maturity. Analyze the factors likely to affect the shape of the yield curve at any time.

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Related Websites http://www.bankrate.com/brm/default.asp http://www.bloomberg.com/markets http://cnnfn.cnn.com/markets/bondcenter/ rates.html

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http://www.standardandpoors.com/ratings/ corporates/index.htm http://www.moodys.com http://www.fitchinv.com The above sites provide information on bond ratings.

These sites give general price information.

http://www.stls.frb.org/fred

http://www.bondresources.com http://www.investinginbonds.com/ http://www.bondsonline.com/docs/ bondprofessor-glossary.html

This site has extended information on various interest rates. These rates can be downloaded into a spreadsheet format for analysis.

These sites contain detailed information on bonds. They are comprehensive and have many related links.

n the previous chapters on risk and return relationships, we have treated securities at a high level of abstraction. We have assumed implicitly that a prior, detailed analysis of each security already has been performed, and that its risk and return features have been assessed. We turn now to specific analyses of particular security markets. We examine valuation principles, determinants of risk and return, and portfolio strategies commonly used within and across the various markets. We begin by analyzing debt securities. A debt security is a claim on a specified periodic stream of income. Debt securities are often called fixed-income securities, because they promise either a fixed stream of income or a stream of income that is determined according to a specified formula. These securities have the advantage of being relatively easy to understand because the payment formulas are specified in advance. Uncertainty surrounding cash flows paid to the security holder is minimal as long as the issuer of the security is sufficiently creditworthy. That makes these securities a convenient starting point for our analysis of the universe of potential investment vehicles. The bond is the basic debt security, and this chapter starts with an overview of bond markets, including Treasury, corporate, and international bonds. We turn next to bond pricing, showing how bond prices are set in accordance with market interest rates and why bond prices change with those rates. Given this background, we can compare the myriad measures of bond returns such as yield to maturity, yield to call, holding-period return, or realized compound yield to maturity. We show how bond prices evolve over time, discuss certain tax rules that apply to debt securities, and show how to calculate after-tax returns. Next, we consider the impact of default or

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credit risk on bond pricing and look at the determinants of credit risk and the default premium built into bond yields. Finally, we turn to the term structure of interest rates, the relationship between yield to maturity and time to maturity.

A security such as a bond that pays a specified cash flow over a specific period.

bond A security that obligates the issuer to make specified payments to the holder over a period of time.

face value, par value The payment to the bondholder at the maturity of the bond.

coupon rate A bond’s annual interest payment per dollar of par value.

zero-coupon bond A bond paying no coupons that sells at a discount and provides only a payment of par value at maturity.

callable bonds Bonds that may be repurchased by the issuer at a specified call price during the call period.

9.1

BOND CHARACTERISTICS

A bond is a security that is issued in connection with a borrowing arrangement. The borrower issues (i.e., sells) a bond to the lender for some amount of cash; the bond is in essence the “IOU” of the borrower. The arrangement obligates the issuer to make specified payments to the bondholder on specified dates. A typical coupon bond obligates the issuer to make semiannual payments of interest, called coupon payments, to the bondholder for the life of the bond. These are called coupon payments because, in precomputer days, most bonds had coupons that investors would clip off and mail to the issuer of the bond to claim the interest payment. When the bond matures, the issuer repays the debt by paying the bondholder the bond’s par value (or equivalently, its face value). The coupon rate of the bond serves to determine the interest payment: The annual payment equals the coupon rate times the bond’s par value. The coupon rate, maturity date, and par value of the bond are part of the bond indenture, which is the contract between the issuer and the bondholder. To illustrate, a bond with a par value of $1,000 and a coupon rate of 8% might be sold to a buyer for $1,000. The issuer then pays the bondholder 8% of $1,000, or $80 per year, for the stated life of the bond, say 30 years. The $80 payment typically comes in two semiannual installments of $40 each. At the end of the 30-year life of the bond, the issuer also pays the $1,000 par value to the bondholder. Bonds usually are issued with coupon rates set high enough to induce investors to pay par value to buy the bond. Sometimes, however, zero-coupon bonds are issued that make no coupon payments. In this case, investors receive par value at the maturity date, but receive no interest payments until then: The bond has a coupon rate of zero. These bonds are issued at prices considerably below par value, and the investor’s return comes solely from the difference between issue price and the payment of par value at maturity. We will return to these bonds below.

Treasury Bonds and Notes Figure 9.1 is an excerpt from the listing of Treasury issues in The Wall Street Journal. Treasury note maturities range up to 10 years, while Treasury bonds with maturities ranging from 10 to 30 years appear in the figure. In 2001, the Treasury suspended new issues of 30-year bonds, making the 10-year note the longest currently issued Treasury. As of 2002, there have been no announcements of any plans to resume issuing the 30-year bond. Both bonds and notes are issued in denominations of $1,000 or more. Both make semiannual coupon payments. Aside from their differing maturities at issue date, the only major distinction between T-notes and T-bonds is that in the past, some T-bonds were callable for a given period, usually during the last five years of the bond’s life. The call provision gives the Treasury the right to repurchase the bond at par value during the call period. The highlighted bond in Figure 9.1 matures in October 2006. Its coupon rate is 61⁄2%. Par value is $1,000; thus, the bond pays interest of $65 per year in two semiannual payments of $32.50. Payments are made in April and October of each year. The bid and ask prices1 are quoted 1

Recall that the bid price is the price at which you can sell the bond to a dealer. The ask price, which is slightly higher, is the price at which you can buy the bond from a dealer.

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F I G U R E 9.1 Listing of Treasury issues Source: The Wall Street Journal, November 29, 2001. Reprinted by permission of Dow Jones & Company, Inc. via Copyright Clearance Center, Inc. © 2001 Dow Jones & Company. All Rights Reserved Worldwide.

in points plus fractions of 1⁄32 of a point (the numbers after the colons are the fractions of a point). Although bonds are sold in denominations of $1,000 par value, the prices are quoted as a percentage of par value. Therefore, the bid price of the bond is 109:08 1098⁄32 109.25% of par value or $1,092.50, while the ask price is 10911⁄32 percent of par, or $1,093.44. The last column, labeled Ask Yld, is the bond’s yield to maturity based on the ask price. The yield to maturity is often interpreted as a measure of the average rate of return to an investor who purchases the bond for the ask price and holds it until its maturity date. We will have much to say about yield to maturity below.

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Accrued interest and quoted bond prices The bond prices that you see quoted in the financial pages are not actually the prices that investors pay for the bond. This is because the quoted price does not include the interest that accrues between coupon payment dates. If a bond is purchased between coupon payments, the buyer must pay the seller for accrued interest, the prorated share of the upcoming semiannual coupon. For example, if 40 days have passed since the last coupon payment, and there are 182 days in the semiannual coupon period, the seller is entitled to a payment of accrued interest of 40/182 of the semiannual coupon. The sale, or invoice price of the bond, which is the amount the buyer actually pays, would equal the stated price plus the accrued interest. In general, the formula for the amount of accrued interest between two dates is Accrued interest

9.1 EXAMPLE Accrued Interest

Annual coupon payment Days since last coupon payment 2 Days separating coupon payments

Suppose that the coupon rate is 8%. Then the semiannual coupon payment is $40. Because 40 days have passed since the last coupon payment, the accrued interest on the bond is $40 (40/182) $8.79. If the quoted price of the bond is $990, then the invoice price will be $990 $8.79 $998.79.

The practice of quoting bond prices net of accrued interest explains why the price of a maturing bond is listed at $1,000 rather than $1,000 plus one coupon payment. A purchaser of an 8% coupon bond one day before the bond’s maturity would receive $1,040 on the following day and so should be willing to pay a total price of $1,040 for the bond. In fact, $40 of that total payment constitutes the accrued interest for the preceding half-year period. The bond price is quoted net of accrued interest in the financial pages and thus appears as $1,000.

Corporate Bonds Like the government, corporations borrow money by issuing bonds. Figure 9.2 is a sample of corporate bond listings in The Wall Street Journal. The data presented here differ only slightly from U.S. Treasury bond listings. For example, the highlighted AT&T bond pays a coupon rate of 81⁄8% and matures in 2022. Like Treasury bonds, corporate bonds trade in increments of 1⁄32 point. AT&T’s current yield is 8.1%, which is simply the annual coupon payment divided by the bond price ($81.25/$997.50). Note that current yield measures only the annual interest income the bondholder receives as a percentage of the price paid for the bond. It ignores the fact that an investor who buys the bond for $997.50 will be able to redeem it for $1,000 on the maturity date. Prospective price appreciation or depreciation does not enter the computation of the current yield. The trading volume column shows that 300 bonds traded on that day. The change from yesterday’s closing price is given in the last column. Like government bonds, corporate bonds sell in units of $1,000 par value but are quoted as a percentage of par value. Although the bonds listed in Figure 9.2 trade on a formal exchange operated by the New York Stock Exchange, most bonds are traded over-the-counter in a loosely organized network of bond dealers linked by a computer quotation system. (See Chapter 3 for a comparison of exchange versus OTC trading.) In practice, the bond market can be quite “thin,” in that there are few investors interested in trading a particular bond at any particular time. Figure 9.2 shows that trading volume of many bonds on the New York exchange is quite low. Bonds issued in the United States today are registered, meaning that the issuing firm keeps records of the owner of the bond and can mail interest checks to the owner. Registration of

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F I G U R E 9.2 Listing of corporate bonds Source: The Wall Street Journal, September 7, 2000. Reprinted by permission of Dow Jones & Company, Inc. via Copyright Clearance Center, Inc. © 2000 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

bonds is helpful to tax authorities in the enforcement of tax collection. Bearer bonds are those traded without any record of ownership. The investor’s physical possession of the bond certificate is the only evidence of ownership. These are now rare in the United States, but less rare in Europe.

Call provisions on corporate bonds While the Treasury no longer issues callable bonds, some corporate bonds are issued with call provisions. The call provision allows the issuer to repurchase the bond at a specified call price before the maturity date. For example, if a company issues a bond with a high coupon rate when market interest rates are high, and interest rates later fall, the firm might like to retire the high-coupon debt and issue new bonds at a lower coupon rate to reduce interest payments. The proceeds from the new bond issue are used to pay for the repurchase of the existing higher coupon bonds at the call price. This is called refunding. Callable bonds typically come with a period of call protection, an initial time during which the bonds are not callable. Such bonds are referred to as deferred callable bonds. The option to call the bond is valuable to the firm, allowing it to buy back the bonds and refinance at lower interest rates when market rates fall. Of course, the firm’s benefit is the bondholder’s burden. Holders of called bonds forfeit their bonds for the call price, thereby giving up the prospect of an attractive rate of interest on their original investment. To compensate investors for this risk, callable bonds are issued with higher coupons and promised yields to maturity than noncallable bonds. 1. Suppose that General Motors issues two bonds with identical coupon rates and maturity dates. One bond is callable, however, while the other is not. Which bond will sell at a higher price?

Convertible bonds Convertible bonds give bondholders an option to exchange each bond for a specified number of shares of common stock of the firm. The conversion ratio gives the number of shares for which each bond may be exchanged. To see the value of this

2. Calculate the price of the bond for a market interest rate of 3% per half year. Compare the capital gains for the interest rate decline to the losses incurred when the rate increases to 5%. Corporate bonds typically are issued at par value. This means the underwriters of the bond issue (the firms that market the bonds to the public for the issuing corporation) must choose a coupon rate that very closely approximates market yields. In a primary issue of bonds, the underwriters attempt to sell the newly issued bonds directly to their customers. If the coupon rate is inadequate, investors will not pay par value for the bonds. After the bonds are issued, bondholders may buy or sell bonds in secondary markets, such as the one operated by the New York Stock Exchange or the over-the-counter market, where most bonds trade. In these secondary markets, bond prices move in accordance with market forces. The bond prices fluctuate inversely with the market interest rate. The inverse relationship between price and yield is a central feature of fixed-income securities. Interest rate fluctuations represent the main source of risk in the bond market, and we devote considerable attention in the next chapter to assessing the sensitivity of bond prices to market yields. For now, however, it is sufficient to highlight one key factor that determines that sensitivity, namely, the maturity of the bond. A general rule in evaluating bond price risk is that, keeping all other factors the same, the longer the maturity of the bond, the greater the sensitivity of its price to fluctuations in the interest rate. For example, consider Table 9.2, which presents the price of an 8% coupon bond at different market yields and times to maturity. For any departure of the interest rate from 8% (the rate at which the bond sells at par value), the change in the bond price is smaller for shorter times to maturity. This makes sense. If you buy the bond at par with an 8% coupon rate, and market rates subsequently rise, then you suffer a loss: You have tied up your money earning 8% when alternative investments offer higher returns. This is reflected in a capital loss on the bond—a fall in its market price. The longer the period for which your money is tied up, the greater the loss and, correspondingly, the greater the drop in the bond price. In Table 9.2, the row for one-year maturity bonds shows little price sensitivity—that is, with only one year’s earnings at stake, changes in interest rates are not too threatening. But for 30-year maturity bonds, interest rate swings have a large impact on bond prices. This is why short-term Treasury securities such as T-bills are considered to be the safest. They are free not only of default risk but also largely of price risk attributable to interest rate volatility.

9.3

yield to maturity (YTM) The discount rate that makes the present value of a bond’s payments equal to its price.

BOND YIELDS

We have noted that the current yield of a bond measures only the cash income provided by the bond as a percentage of bond price and ignores any prospective capital gains or losses. We would like a measure of rate of return that accounts for both current income as well as the price increase or decrease over the bond’s life. The yield to maturity is the standard measure of the total rate of return of the bond over its life. However, it is far from perfect, and we will explore several variations of this measure.

Yield to Maturity In practice, an investor considering the purchase of a bond is not quoted a promised rate of return. Instead, the investor must use the bond price, maturity date, and coupon payments to infer the return offered by the bond over its life. The yield to maturity (YTM) is defined as

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Bond Prices and Yields

the discount rate that makes the present value of a bond’s payments equal to its price. This rate is often viewed as a measure of the average rate of return that will be earned on a bond if it is bought now and held until maturity. To calculate the yield to maturity, we solve the bond price equation for the interest rate given the bond’s price. For example, suppose an 8% coupon, 30-year bond is selling at $1,276.76. What average rate of return would be earned by an investor purchasing the bond at this price? To answer this question, we find the interest rate at which the present value of the remaining 60 semiannual bond payments equals the bond price. This is the rate that is consistent with the observed price of the bond. Therefore, we solve for r in the following equation 60

$1,276.76

兺 t1

$40 $1,000 (1 r)t (1 r)60

or, equivalently, 1,276.76 40 Annuity factor(r, 60) 1,000 PV factor(r, 60) These equations have only one unknown variable, the interest rate, r. You can use a financial calculator to confirm that the solution to the equation is r .03, or 3% per half-year.6 This is considered the bond’s yield to maturity, as the bond would be fairly priced at $1,276.76 if the fair market rate of return on the bond over its entire life were 3% per half-year. The financial press reports yields on an annualized basis, however, and annualizes the bond’s semiannual yield using simple interest techniques, resulting in an annual percentage rate or APR. Yields annualized using simple interest are also called bond equivalent yields. Therefore, the semiannual yield would be doubled and reported in the newspaper as a bond equivalent yield of 6%. The effective annual yield of the bond, however, accounts for compound interest. If one earns 3% interest every six months, then after one year, each dollar invested grows with interest to $1 (1.03)2 1.0609, and the effective annual interest rate on the bond is 6.09%. The bond’s yield to maturity is the internal rate of return on an investment in the bond. The yield to maturity can be interpreted as the compound rate of return over the life of the bond under the assumption that all bond coupons can be reinvested at an interest rate equal to the bond’s yield to maturity.7 Yield to maturity therefore is widely accepted as a proxy for average return. Yield to maturity can be difficult to calculate without a financial calculator. However, it is easy to calculate with one. Financial calculators are designed with present value and future value formulas already programmed. The basic financial calculator uses five keys that correspond to the inputs for time value of money problems such as bond pricing: n

i

PV

FV

PMT

• n is the number of time periods. In the case of a bond, n equals the number of periods until the bond matures. If the bond makes semiannual payments, n is the number of half-year periods or, equivalently, the number of semiannual coupon payments. For example, if the bond has 10 years until maturity, you would enter 20 for n, since each payment period is one-half year. 6

Without a financial calculator, you still could solve the equation, but you would need to use a trial-and-error approach. 7 If the reinvestment rate does not equal the bond’s yield to maturity, the compound rate of return will differ from YTM. This is demonstrated in Examples 9.5 and 9.6.

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• i is the interest rate per period, expressed as a percentage (not a decimal). For example, if the interest rate is 6%, you would enter 6, not 0.06. • PV is the present value. Many calculators will require that PV be entered as a negative number, in recognition of the fact that purchase of the bond is a cash outflow, while the receipt of coupon payments and face value are cash inflows. • FV is the future value or face value of the bond. In general, FV is interpreted as a one-time future payment of a cash flow, which, for bonds, is the face (i.e., par) value. • PMT is the amount of any recurring payment. For coupon bonds, PMT is the coupon payment; for zero-coupon bonds, PMT will be zero. Given any four of these inputs, the calculator will solve for the fifth. We can illustrate with some examples.

9.3 EXAMPLE Bond Valuation Using a Financial Calculator

Consider the yield to maturity problem that we just solved. We would enter the following inputs (in any order): n

60

The bond has a maturity of 30 years, so it makes 60 semiannual payments.

PMT

40

Each semiannual coupon payment is $40.

PV

()1,276.76 The bond can be purchased for $1,276.76, which on some calculators must be entered as a negative number as it is a cash outflow.

FV

1,000

The bond will provide a one-time cash flow of $1,000 when it matures.

Given these inputs, you now use the calculator to find the interest rate at which $1,276.76 actually equals the present value of the 60 payments of $40 each plus the one-time payment of $1,000 at maturity. On most calculators, you first punch the “compute” key (labeled COMP or CPT) and then enter i to have the interest rate computed. If you do so, you will find that i 3, or 3% semiannually, as we claimed. (Notice that just as the cash flows are paid semiannually, the computed interest rate is a rate per semiannual time period.) You can also find bond prices given a yield to maturity. For example, we saw in Example 9.2 that if the yield to maturity is 5% semiannually, the bond price will be $810.71. You can confirm this with the following inputs on your calculator: n 60; i 5; FV 1,000; PMT 40 and then computing PV to find that PV 810.71. Once again, your calculator may report the result as 810.71.

current yield Annual coupon divided by bond price.

premium bonds Bonds selling above par value.

Yield to maturity is different from the current yield of a bond, which is the bond’s annual coupon payment divided by the bond price. For example, for the 8%, 30-year bond currently selling at $1,276.76, the current yield would be $80/$1,276.76 0.0627, or 6.27% per year. In contrast, recall that the effective annual yield to maturity is 6.09%. For this bond, which is selling at a premium over par value ($1,276 rather than $1,000), the coupon rate (8%) exceeds the current yield (6.27%), which exceeds the yield to maturity (6.09%). The coupon rate exceeds current yield because the coupon rate divides the coupon payments by par value ($1,000) rather than by the bond price ($1,276). In turn, the current yield exceeds yield to maturity because the yield to maturity accounts for the built-in capital loss on the bond; the bond bought today for $1,276 will eventually fall in value to $1,000 at maturity. This example illustrates a general role: for premium bonds (bonds selling above par value), coupon rate is greater than current yield, which in turn is greater than yield to maturity.

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309

For discount bonds (bonds selling below par value), these relationships are reversed (see Concept Check 3). It is common to hear people talking loosely about the yield on a bond. In these cases, they almost always are referring to the yield to maturity.

discount bonds

9

3. What will be the relationship among coupon rate, current yield, and yield to maturity for bonds selling at discounts from par? Illustrate using the 8% (semiannual payment) coupon bond assuming it is selling at a yield to maturity of 10%.

Bonds selling below par value.

4. A 20-year maturity 9% coupon bond paying coupons semiannually is callable in five years at a call price of $1,050. The bond currently sells at a yield to maturity of 8% (bond equivalent yield). What is the yield to call?

Realized Compound Yield versus Yield to Maturity We have noted that yield to maturity will equal the rate of return realized over the life of the bond if all coupons are reinvested at an interest rate equal to the bond’s yield to maturity. Consider for example, a two-year bond selling at par value paying a 10% coupon once a year. The yield to maturity is 10%. If the $100 coupon payment is reinvested at an interest rate of 10%, the $1,000 investment in the bond will grow after two years to $1,210, as illustrated in Figure 9.5, Panel A. The coupon paid in the first year is reinvested and grows with interest to a second-year value of $110, which, together with the second coupon payment and payment of par value in the second year, results in a total value of $1,210. The compound growth rate of invested funds, therefore, is calculated from

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F I G U R E 9.5

A. Reinvestment rate = 10% $1,100

Cash flow: Time: 0

311

Growth of invested funds

$100 1

2 $1,100

Future value:

= $1,100

100 x 1.10 = $ 110 $1,210

B. Reinvestment rate = 8% $1,100

Cash flow: Time: 0

$100 1

2 $1,100

Future value:

= $1,100

100 x 1.08 = $ 108 $1,208

$1,000 (1 yrealized)2 $1,210 yrealized 0.10 10% With a reinvestment rate equal to the 10% yield to maturity, the realized compound yield equals yield to maturity. But what if the reinvestment rate is not 10%? If the coupon can be invested at more than 10%, funds will grow to more than $1,210, and the realized compound return will exceed 10%. If the reinvestment rate is less than 10%, so will be the realized compound return. Consider the following example. If the interest rate earned on the first coupon is less than 10%, the final value of the investment will be less than $1,210, and the realized compound yield will be less than 10%. Suppose the interest rate at which the coupon can be invested equals 8%. The following calculations are illustrated in Panel B of Figure 9.5. Future value of first coupon payment with interest earnings Cash payment in second year (final coupon plus par value) Total value of investment with reinvested coupons

$100 1.08 $ 108 1,100 $1,208

The realized compound yield is computed by calculating the compound rate of growth of invested funds, assuming that all coupon payments are reinvested. The investor purchased the bond for par at $1,000, and this investment grew to $1,208. $1,000(1 yrealized)2 $1,208 yrealized 0.0991 9.91%

EXAMPLE 9.5 Realized Compound Yield

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horizon analysis Analysis of bond returns over multiyear horizon, based on forecasts of bond’s yield to maturity and reinvestment rate of coupons.

9.6 EXAMPLE Horizon Analysis

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Example 9.5 highlights the problem with conventional yield to maturity when reinvestment rates can change over time. However, in an economy with future interest rate uncertainty, the rates at which interim coupons will be reinvested are not yet known. Therefore, while realized compound yield can be computed after the investment period ends, it cannot be computed in advance without a forecast of future reinvestment rates. This reduces much of the attraction of the realized yield measure. We also can calculate realized compound yield over holding periods greater than one period. This is called horizon analysis and is similar to the procedure in Example 9.5. The forecast of total return will depend on your forecasts of both the yield to maturity of the bond when you sell it and the rate at which you are able to reinvest coupon income. With a longer investment horizon, however, reinvested coupons will be a larger component of your final proceeds.

Suppose you buy a 30-year, 7.5% (annual payment) coupon bond for $980 (when its yield to maturity is 7.67%) and plan to hold it for 20 years. Your forecast is that the bond’s yield to maturity will be 8% when it is sold and that the reinvestment rate on the coupons will be 6%. At the end of your investment horizon, the bond will have 10 years remaining until expiration, so the forecast sales price (using a yield to maturity of 8%) will be $966.45. The 20 coupon payments will grow with compound interest to $2,758.92. (This is the future value of a 20-year $75 annuity with an interest rate of 6%. Based on these forecasts, your $980 investment will grow in 20 years to $966.45 $2,758.92 $3,725.37. This corresponds to an annualized compound return of 6.90%, calculated by solving for r in the equation $980 (1 r)20 $3,725.37.

9.4

BOND PRICES OVER TIME

As we noted earlier, a bond will sell at par value when its coupon rate equals the market interest rate. In these circumstances, the investor receives fair compensation for the time value of money in the form of the recurring interest payments. No further capital gain is necessary to provide fair compensation. When the coupon rate is lower than the market interest rate, the coupon payments alone will not provide investors as high a return as they could earn elsewhere in the market. To receive a fair return on such an investment, investors also need to earn price appreciation on their bonds. The bonds, therefore, would have to sell below par value to provide a “built-in” capital gain on the investment. To illustrate this point, suppose a bond was issued several years ago when the interest rate was 7%. The bond’s annual coupon rate was thus set at 7%. (We will suppose for simplicity that the bond pays its coupon annually.) Now, with three years left in the bond’s life, the interest rate is 8% per year. The bond’s fair market price is the present value of the remaining annual coupons plus payment of par value. That present value is $70 Annuity factor(8%, 3) $1,000 PV factor(8%, 3) $974.23 which is less than par value. In another year, after the next coupon is paid, the bond would sell at $70 Annuity factor(8%, 2) $1,000 PV factor(8%, 2) $982.17 thereby yielding a capital gain over the year of $7.94. If an investor had purchased the bond at $974.23, the total return over the year would equal the coupon payment plus capital gain, or $70 $7.94 $77.94. This represents a rate of return of $77.94/$974.23, or 8%, exactly the current rate of return available elsewhere in the market.

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F I G U R E 9.6

Price ($) Premium bond

Price paths of coupon bonds in the case of constant market interest rates

1,000

Discount bond

0

Maturity date

Time

5. What will the bond price be in yet another year, when only one year remains until maturity? What is the rate of return to an investor who purchases the bond at $982.17 and sells it one year hence? When bond prices are set according to the present value formula, any discount from par value provides an anticipated capital gain that will augment a below-market coupon rate just sufficiently to provide a fair total rate of return. Conversely, if the coupon rate exceeds the market interest rate, the interest income by itself is greater than that available elsewhere in the market. Investors will bid up the price of these bonds above their par values. As the bonds approach maturity, they will fall in value because fewer of these above-market coupon payments remain. The resulting capital losses offset the large coupon payments so that the bondholder again receives only a fair rate of return. Problem 9 at the end of the chapter asks you to work through the case of the high coupon bond. Figure 9.6 traces out the price paths of high and low coupon bonds (net of accrued interest) as time to maturity approaches, at least for the case in which the market interest rate is constant. The low coupon bond enjoys capital gains, while the high coupon bond suffers capital losses.8 We use these examples to show that each bond offers investors the same total rate of return. Although the capital gain versus income components differ, the price of each bond is set to provide competitive rates, as we should expect in well-functioning capital markets. Security returns all should be comparable on an after-tax risk-adjusted basis. If they are not, investors will try to sell low-return securities, thereby driving down the prices until the total return at the now lower price is competitive with other securities. Prices should continue to adjust until all securities are fairly priced in that expected returns are appropriate (given necessary risk and tax adjustments).

Yield to Maturity versus Holding-Period Return We just considered an example in which the holding-period return and the yield to maturity were equal: in our example, the bond yield started and ended the year at 8%, and the bond’s holding-period return also equaled 8%. This turns out to be a general result. When the yield to 8

If interest rates are volatile, the price path will be “jumpy,” vibrating around the price path in Figure 9.6, and reflecting capital gains or losses as interest rates fall or rise. Ultimately, however, the price must reach par value at the maturity date, so on average, the price of the premium bond will fall over time while that of the discount bond will rise.

Consider a 30-year bond paying an annual coupon of $80 and selling at par value of $1,000. The bond’s initial yield to maturity is 8%. If the yield remains at 8% over the year, the bond price will remain at par, so the holding-period return also will be 8%. But if the yield falls below 8%, the bond price will increase. Suppose the price increases to $1,050. Then the holding-period return is greater than 8%: Holding-period return

$80 ($1,050 $1,000) $1,000

.13, or 13%

6. Show that if yield to maturity increases, then holding-period return is less than initial yield. For example, suppose that by the end of the first year, the bond’s yield to maturity is 8.5%. Find the one-year holding-period return and compare it to the bond’s initial 8% yield to maturity. Here is another way to think about the difference between yield to maturity and holdingperiod return. Yield to maturity depends only on the bond’s coupon, current price, and par value at maturity. All of these values are observable today, so yield to maturity can be easily calculated. Yield to maturity can be interpreted as a measure of the average rate of return if the investment in the bond is held until the bond matures. In contrast, holding-period return is the rate of return over a particular investment period and depends on the market price of the bond at the end of that holding period; of course this price is not known today. Since bond prices over the holding period will respond to unanticipated changes in interest rates, holding-period return can at most be forecast.

Zero-Coupon Bonds Original issue discount bonds are less common than coupon bonds issued at par. These are bonds that are issued intentionally with low coupon rates that cause the bond to sell at a discount from par value. An extreme example of this type of bond is the zero-coupon bond, which carries no coupons and must provide all its return in the form of price appreciation. Zeros provide only one cash flow to their owners, and that is on the maturity date of the bond. U.S. Treasury bills are examples of short-term zero-coupon instruments. The Treasury issues or sells a bill for some amount less than $10,000, agreeing to repay $10,000 at the bill’s maturity. All of the investor’s return comes in the form of price appreciation over time. Longer term zero-coupon bonds are commonly created from coupon-bearing notes and bonds with the help of the U.S. Treasury. A broker that purchases a Treasury coupon bond may ask the Treasury to break down the cash flows to be paid by the bond into a series of independent securities, where each security is a claim to one of the payments of the original bond. For example, a 10-year coupon bond would be “stripped” of its 20 semiannual coupons and

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F I G U R E 9.7

1,000 900 800 700 600 500 400 300 200 100 0 30

27

24

21

18

15

12

9

6

3

0

Price ($)

The price of a 30-year zero-coupon bond over time at a yield to maturity of 10%. Price equals 1000/(1.10)T where T is time until maturity.

Year Today

Maturity date

each coupon payment would be treated as a stand-alone zero-coupon bond. The maturities of these bonds would thus range from six months to 10 years. The final payment of principal would be treated as another stand-alone zero-coupon security. Each of the payments would then be treated as an independent security and assigned its own CUSIP number, the security identifier that allows for electronic trading over the Fedwire system. The payments are still considered obligations of the U.S. Treasury. The Treasury program under which coupon stripping is performed is called STRIPS (Separate Trading of Registered Interest and Principal of Securities), and these zero-coupon securities are called Treasury strips. Turn back to Figure 9.1 for a listing of these bonds appearing in The Wall Street Journal. What should happen to prices of zeros as time passes? On their maturity dates, zeros must sell for par value. Before maturity, however, they should sell at discounts from par, because of the time value of money. As time passes, price should approach par value. In fact, if the interest rate is constant, a zero’s price will increase at exactly the rate of interest. To illustrate this property, consider a zero with 30 years until maturity, and suppose the market interest rate is 10% per year. The price of the bond today will be $1,000/(1.10)30 $57.31. Next year, with only 29 years until maturity, if the yield to maturity is still 10%, the price will be $1,000/(1.10)29 $63.04, a 10% increase over its previous-year value. Because the par value of the bond is now discounted for one fewer year, its price has increased by the one-year discount factor. Figure 9.7 presents the price path of a 30-year zero-coupon bond until its maturity date for an annual market interest rate of 10%. The bond’s price rises exponentially, not linearly, until its maturity.

After-Tax Returns The tax authorities recognize that the “built-in” price appreciation on original-issue discount (OID) bonds such as zero-coupon bonds represents an implicit interest payment to the holder of the security. The Internal Revenue Service (IRS), therefore, calculates a price appreciation schedule to impute taxable interest income for the built-in appreciation during a tax year, even if the asset is not sold or does not mature until a future year. Any additional gains or losses that arise from changes in market interest rates are treated as capital gains or losses if the OID bond is sold during the tax year.

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9.8 EXAMPLE Taxation of OID Bonds

If the interest rate originally is 10%, the 30-year zero would be issued at a price of $1,000/(1.10)30 $57.31. The following year, the IRS calculates what the bond price would be if the yield remains at 10%. This is $1,000/(1.10)29 $63.04. Therefore, the IRS imputes interest income of $63.04 $57.31 $5.73. This amount is subject to tax. Notice that the imputed interest income is based on a “constant yield method” that ignores any changes in market interest rates. If interest rates actually fall, let’s say to 9.9%, the bond price actually will be $1,000/ (1.099)29 $64.72. If the bond is sold, then the difference between $64.72 and $63.04 will be treated as capital gains income and taxed at the capital gains tax rate. If the bond is not sold, then the price difference is an unrealized capital gain and does not result in taxes in that year. In either case, the investor must pay taxes on the $5.73 of imputed interest at the ordinary income tax rate.

The procedure illustrated in Example 9.8 is applied to the taxation of other original issue discount bonds, even if they are not zero-coupon bonds. Consider, as another example, a 30-year maturity bond that is issued with a coupon rate of 4% and a yield to maturity of 8%. For simplicity, we will assume that the bond pays coupons once annually. Because of the low coupon rate, the bond will be issued at a price far below par value, specifically at a price of $549.69. (Confirm this for yourself.) If the bond’s yield to maturity remains at 8%, then its price in one year will rise to $553.66. (Confirm this also.) This provides a pretax holdingperiod return of exactly 8%: HPR

$40 ($553.66 $549.69) 0.08 $549.69

The increase in the bond price based on a constant yield, however, is treated as interest income, so the investor is required to pay taxes on imputed interest income of $553.66 $549.69 $3.97, as well as on the explicit coupon income of $40. If the bond’s yield actually changes during the year, the difference between the bond’s price and the “constant yield value” of $553.66 would be treated as capital gains income if the bond were sold at year-end.

Concept CHECK

>

7. Suppose that the yield to maturity of the 4% coupon, 30-year maturity bond actually falls to 7% by the end of the first year, and that the investor sells the bond after the first year. If the investor’s tax rate on interest income is 36% and the tax rate on capital gains is 28%, what is the investor’s after-tax rate of return?

9.5 investment grade bond A bond rated BBB and above by Standard & Poor’s, or Baa and above by Moody’s.

speculative grade or junk bond A bond rated BB or lower by Standard & Poor’s, Ba or lower by Moody’s, or an unrated bond.

DEFAULT RISK AND BOND PRICING

Although bonds generally promise a fixed flow of income, that income stream is not riskless unless the investor can be sure the issuer will not default on the obligation. While U.S. government bonds may be treated as free of default risk, this is not true of corporate bonds. If the company goes bankrupt, the bondholders will not receive all the payments they have been promised. Therefore, the actual payments on these bonds are uncertain, for they depend to some degree on the ultimate financial status of the firm. Bond default risk is measured by Moody’s Investor Services, Standard & Poor’s Corporation, Duff and Phelps, and Fitch Investors Service, all of which provide financial information on firms as well as quality ratings of large corporate and municipal bond issues. Each firm assigns letter grades to the bonds of corporations and municipalities to reflect their assessment of the safety of the bond issue. The top rating is AAA or Aaa. Moody’s modifies each rating class with a 1, 2, or 3 suffix (e.g., Aaa1, Aaa2, Aaa3) to provide a finer gradation of ratings. The other agencies use a or modification. Those rated BBB or above (S&P, Duff and Phelps, Fitch) or Baa and above (Moody’s) are considered investment grade bonds, while lower-rated bonds are classified as speculative

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Bond Ratings

Standard & Poor’s Moody’s

317

Very High Quality

High Quality

Speculative

Very Poor

AAA AA Aaa Aa

A BBB A Baa

BB B Ba B

CCC D Caa C

At times both Moody’s and Standard & Poor’s use adjustments to these ratings. S&P uses plus and minus signs: A is the strongest A rating and A the weakest. Moody’s uses a 1, 2, or 3 designation—with 1 indicating the strongest. Moody’s S&P Aaa

AAA Debt rated Aaa and AAA has the highest rating. Capacity to pay interest and principal is extremely strong.

Aa

AA

Debt rated Aa and AA has a very strong capacity to pay interest and repay principal. Together with the highest rating, this group comprises the high-grade bond class.

A

A

Debt rated A has a strong capacity to pay interest and repay principal, although it is somewhat more susceptible to the adverse effects of changes in circumstances and economic conditions than debt in higherrated categories.

Baa

BBB

Debt rated Baa and BBB is regarded as having an adequate capacity to pay interest and repay principal. Whereas it normally exhibits adequate protection parameters, adverse economic conditions or changing circumstances are more likely to lead to a weakened capacity to pay interest and repay principal for debt in this category than in higher-rated categories. These bonds are medium grade obligations.

Ba

BB

Debt rated in these categories is regarded, on balance, as predomi-

B

B

antly speculative with respect to capacity to pay interest and repay

Caa

CCC

principal in accordance with the terms of the obligation. BB and Ba

Ca

CC

indicate the lowest degree of speculation, and CC and Ca the highest degree of speculation. Although such debt will likely have some quality and protective characteristics, these are outweighed by large uncertainties or major risk exposures to adverse conditions. Some issues may be in default.

C

C

This rating is reserved for income bonds on which no interest is being paid.

D

D

Debt rated D is in default, and payment of interest and/or repayment of principal is in arrears.

grade or junk bonds. Certain regulated institutional investors such as insurance companies have not always been allowed to invest in speculative grade bonds. Figure 9.8 provides the definitions of each bond rating classification.

Junk Bonds Junk bonds, also known as high-yield bonds, are nothing more than speculative grade (lowrated or unrated) bonds. Before 1977, almost all junk bonds were “fallen angels,” that is, bonds issued by firms that originally had investment grade ratings but that had since been downgraded. In 1977, however, firms began to issue “original-issue junk.”

Definitions of each bond rating class Sources: From Stephen A. Ross, Randolph W. Westerfield, and Jeffrey A. Jaffe, Corporate Finance, McGraw-Hill Publishing. Data from various editions of Standard & Poor’s Bond Guide and Moody’s Bond Guide.

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Much of the credit for this innovation is given to Drexel Burnham Lambert, and especially its trader, Michael Milken. Drexel had long enjoyed a niche as a junk bond trader and had established a network of potential investors in junk bonds. Firms not able to muster an investment grade rating were happy to have Drexel (and other investment bankers) market their bonds directly to the public, as this opened up a new source of financing. Junk issues were a lower-cost financing alternative than borrowing from banks. High-yield bonds gained considerable notoriety in the 1980s when they were used as financing vehicles in leveraged buyouts and hostile takeover attempts. Shortly ther

Sample Chapter Table of Contents About the Authors Preface What's New Feature Summary Supplements PageOut About the Team Overview Mobile Resources

Essentials of Investments, 5/e Zvi Bodie, Boston University Alex Kane, University of California, San Diego Alan J. Marcus, Boston College ISBN: 0072510773 Copyright year: 2004

Table of Contents

Part ONE Elements of Investments 1

Investments: Background and Issues

2

Financial Instruments

First Time Users

3

How Securities Are Traded

Student Edition

4

Mutual Funds and Other Investment Companies

Instructor Edition

Part TWO Portfolio Theory 5

Risk and Return: Past and Prologue

6

Efficient Diversification

7

Capital Asset Pricing and Arbitrage Pricing Theory

8

The Efficient Market Hypothesis

Part THREE Debt Securities 9 10

Bond Prices and Yields Managing Bond Portfolios

Part FOUR Security Analysis 11

Macroeconomic and Industry Analysis

12

Equity Valuation

13

Financial Statement Analysis

Part FIVE Derivative Markets 14

Options Markets

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15

Option Valuation

16

Futures Markets

Part SIX Active Investment Management 17

Investors and the Investment Process

18

Taxes, Inflation, and Investment Strategy

19

Behavioral Finance and Technical Analysis

20 Performance Evaluation and Active Portfolio Management 21

International Investing

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Bodie−Kane−Marcus: Essentials of Investments, Fifth Edition

Front Matter

A Note from the Authors

© The McGraw−Hill Companies, 2003

A Note from the Authors . . .

The last decade has been one of rapid, profound, and ongoing change in the investments industry. This is due in part to an abundance of newly designed securities, in part to the creation of new trading strategies that would have been impossible without concurrent advances in computer and communications technology, and in part to continuing advances in the theory of investments. Of necessity, our text has evolved along with the financial markets. In this edition, we address many of the changes in the investment environment. At the same time, many basic principles remain important. We continue to organize our book around one basic theme—that security markets are nearly efficient, meaning that most securities are usually priced appropriately given their risk and return attributes. There are few free lunches found in markets as competitive as the financial market. This simple observation is, nevertheless, remarkably powerful in its implications for the design of investment strategies, and our discussions of strategy are always guided by the implications of the efficient markets hypothesis. While the degree of market efficiency is, and will always be, a matter of debate, we hope our discussions throughout the book convey a good dose of healthy criticism concerning much conventional wisdom. This text also continues to emphasize asset allocation more than most other books. We prefer this emphasis for two important reasons. First, it corresponds to the procedure that most individuals actually follow when building an investment portfolio. Typically, you start with all of your money in a bank account, only then considering how much to invest in something riskier that might offer a higher expected return. The logical step at this point is to consider other risky asset classes, such as stock, bonds, or real estate. This is an asset allocation decision. Second, in most cases the asset allocation choice is far more important xviii

than specific security-selection decisions in determining overall investment performance. Asset allocation is the primary determinant of the risk-return profile of the investment portfolio, and so it deserves primary attention in a study of investment policy. Our book also focuses on investment analysis, which allows us to present the practical applications of investment theory, and to convey insights of practical value. In this edition of the text, we have continued to expand a systematic collection of Excel spreadsheets that give you tools to explore concepts more deeply than was previously possible. These spreadsheets are available through the World Wide Web, and provide a taste of the sophisticated analytic tools available to professional investors. In our efforts to link theory to practice, we also have attempted to make our approach consistent with that of the Institute of Chartered Financial Analysts (ICFA). The ICFA administers an education and certification program to candidates for the title of Chartered Financial Analyst (CFA). The CFA curriculum represents the consensus of a committee of distinguished scholars and practitioners regarding the core of knowledge required by the investment professional. This text will introduce you to the major issues currently of concern to all investors. It can give you the skills to conduct a sophisticated assessment of current issues and debates covered by both the popular media as well as more specialized finance journals. Whether you plan to become an investment professional, or simply a sophisticated individual investor, you will find these skills essential. Zvi Bodie Alex Kane Alan J. Marcus

Bodie−Kane−Marcus: Essentials of Investments, Fifth Edition

I. Elements of Investments

© The McGraw−Hill Companies, 2003

Introduction

PA RT

ONE

ELEMENTS OF INVESTMENTS

ven a cursory glance at The Wall Street Journal reveals a bewildering collection of securities, markets, and financial institutions. Although it may appear so, the financial environment is not chaotic: There is a rhyme or reason behind the vast array of financial instruments and the markets in which they trade. These introductory chapters provide a bird’s-eye view of the investing environment. We will give you a tour of the major types of markets in which securities trade, the trading process, and the major players in these arenas. You will see that both markets and securities have evolved to meet the changing and complex needs of different participants in the financial system. Markets innovate and compete with each other for traders’ business just as vigorously as competitors in other industries. The competi-

E

>

tion between the National Association of Securities Dealers Automatic Quotation System (Nasdaq), the New York Stock Exchange (NYSE), and a number of non-U.S. exchanges is fierce and public. Trading practices can mean big money to investors. The explosive growth of online trading has saved them many millions of dollars in trading costs. Even more dramatically, new electronic communication networks will allow investors to trade directly without a broker. These advances promise to change the face of the investments industry, and Wall Street firms are scrambling to formulate strategies that respond to these changes. These chapters will give you a good foundation with which to understand the basic types of securities and financial markets as well as how trading in those markets is conducted.

1

Investments: Background and Issues

2

Global Financial Instruments

3

How Securities Are Traded

4

Mutual Funds and Other Investment Companies

www.mhhe.com/bkm

Bodie−Kane−Marcus: Essentials of Investments, Fifth Edition

I. Elements of Investments

1. Investments: Background and Issues

© The McGraw−Hill Companies, 2003

1 INVESTMENTS: BACKGROUND AND ISSUES

AFTER STUDYING THIS CHAPTER YOU SHOULD BE ABLE TO:

> > > > >

2

Define an investment. Distinguish between real assets and financial assets. Describe the major steps in the construction of an investment portfolio. Identify major participants in financial markets. Identify types of financial markets and recent trends in those markets.

Bodie−Kane−Marcus: Essentials of Investments, Fifth Edition

I. Elements of Investments

1. Investments: Background and Issues

Related Websites http://www.ceoexpress.com This site provides a list of links related to all aspects of business, including extensive sites related to finance and investment.

© The McGraw−Hill Companies, 2003

research from the various banks is available online. The Federal Reserve Economic Database, or FRED, is available through the St. Louis Federal Reserve Bank. A search engine for all of the Bank’s research articles is available at the San Francisco Federal Reserve Bank.

http://www.corpgov.net

http://www.cob.ohio-state.edu/fin/journal/ jofsites.htm

Dedicated to corporate governance issues, this site has extensive coverage and numerous links to other sites related to corporate governance.

This site contains a directory of finance journals and associations related to education in the financial area.

http://www.finpipe.com

http://finance.yahoo.com

This is an excellent general site that is dedicated to finance education. It contains information on debt securities, equities, and derivative instruments.

This investment site contains information on financial markets. Portfolios can be constructed and monitored at no charge. Limited historical return data is available for actively traded securities.

http://www.financewise.com

http://moneycentral.msn.com/home.asp

This is a thorough finance search engine for other financial sites.

Similar to Yahoo! Finance, this investment site contains comprehensive information on financial markets.

http://www.federalreserve.gov/otherfrb.htm This site contains a map that allows you to access all of the Federal Reserve Bank sites. Most of the economic

n investment is the current commitment of money or other resources in the expectation of reaping future benefits. For example, an individual might purchase shares of stock anticipating that the future proceeds from the shares will justify both the time that her money is tied up as well as the risk of the investment. The time you will spend studying this text (not to mention its cost) also is an investment. You are forgoing either current leisure or the income you could be earning at a job in the expectation that your future career will be sufficiently enhanced to justify this commitment of time and effort. While these two investments differ in many ways, they share one key attribute that is central to all investments: You sacrifice something of value now, expecting to benefit from that sacrifice later. This text can help you become an informed practitioner of investments. We will focus on investments in securities such as stocks, bonds, or options and futures contracts, but much of what we discuss will be useful in the analysis of any type of investment. The text will provide you with background in the organization of various securities markets, will survey the valuation and risk-management principles useful in particular markets, such as those for bonds or stocks, and will introduce you to the principles of portfolio construction. Broadly speaking, this chapter addresses three topics that will provide a useful perspective for the material that is to come later. First, before delving into the topic of “investments,” we consider the role of financial assets in the economy. We discuss the relationship between securities and the “real” assets that actually produce goods and services for consumers, and we consider why financial assets are important to the functioning of a developed economy. Given this background, we then take a first look at the types of decisions that confront investors as they assemble a portfolio of

A

Bodie−Kane−Marcus: Essentials of Investments, Fifth Edition

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4

Part ONE Elements of Investments

investment

assets. These investment decisions are made in an environment where higher returns usually can be obtained only at the price of greater risk, and in which it is rare to find assets that are so mispriced as to be obvious bargains. These themes—the risk-return trade-off and the efficient pricing of financial assets—are central to the investment process, so it is worth pausing for a brief discussion of their implications as we begin the text. These implications will be fleshed out in much greater detail in later chapters. Finally, we conclude the chapter with an introduction to the organization of security markets, the various players that participate in those markets, and a brief overview of some of the more important changes in those markets in recent years. Together, these various topics should give you a feel for who the major participants are in the securities markets as well as the setting in which they act. We close the chapter with an overview of the remainder of the text.

Commitment of current resources in the expectation of deriving greater resources in the future.

1.1 real assets Assets used to produce goods and services.

financial assets Claims on real assets or the income generated by them.

REAL ASSETS VERSUS FINANCIAL ASSETS

The material wealth of a society is ultimately determined by the productive capacity of its economy, that is, the goods and services its members can create. This capacity is a function of the real assets of the economy: the land, buildings, machines, and knowledge that can be used to produce goods and services. In contrast to such real assets are financial assets, such as stocks and bonds. Such securities are no more than sheets of paper or, more likely, computer entries and do not contribute directly to the productive capacity of the economy. Instead, these assets are the means by which individuals in well-developed economies hold their claims on real assets. Financial assets are claims to the income generated by real assets (or claims on income from the government). If we cannot own our own auto plant (a real asset), we can still buy shares in General Motors or Toyota (financial assets) and, thereby, share in the income derived from the production of automobiles. While real assets generate net income to the economy, financial assets simply define the allocation of income or wealth among investors. Individuals can choose between consuming their wealth today or investing for the future. If they choose to invest, they may place their wealth in financial assets by purchasing various securities. When investors buy these securities from companies, the firms use the money so raised to pay for real assets, such as plant, equipment, technology, or inventory. So investors’ returns on securities ultimately come from the income produced by the real assets that were financed by the issuance of those securities. The distinction between real and financial assets is apparent when we compare the balance sheet of U.S. households, shown in Table 1.1, with the composition of national wealth in the United States, shown in Table 1.2. Household wealth includes financial assets such as bank accounts, corporate stock, or bonds. However, these securities, which are financial assets of households, are liabilities of the issuers of the securities. For example, a bond that you treat as an asset because it gives you a claim on interest income and repayment of principal from General Motors is a liability of General Motors, which is obligated to make these payments to you. Your asset is GM’s liability. Therefore, when we aggregate over all balance sheets, these claims cancel out, leaving only real assets as the net wealth of the economy. National wealth consists of structures, equipment, inventories of goods, and land. We will focus almost exclusively on financial assets. But you shouldn’t lose sight of the fact that the successes or failures of the financial assets we choose to purchase ultimately depend on the performance of the underlying real assets.

Bodie−Kane−Marcus: Essentials of Investments, Fifth Edition

I. Elements of Investments

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1. Investments: Background and Issues

1

5

Investments: Background and Issues

TA B L E 1.1 Balance sheet of U.S. households

Assets

$ Billion

% Total

Real assets Real estate Durables Other

$12,567 2,820 117

26.7% 6.0 0.2

$15,504

32.9%

Total real assets Financial assets Deposits Live insurance reserves Pension reserves Corporate equity Equity in noncorp. business Mutual funds shares Personal trusts Debt securities Other

$ 4,698 817 8,590 5,917 5,056 2,780 949 2,075 746

Total financial assets

31,628

67.1

$47,132

100.0%

Total

Liabilities and Net Worth

$ Billion

% Total

Mortgages Consumer credit Bank & other loans Other

$ 5,210 1,558 316 498

11.1% 3.3 0.7 1.1

Total liabilities

$ 7,582

16.1%

10.0% 1.7 18.2 12.6 10.7 5.9 2.0 4.4 1.6 Net worth

39,550

83.9

$47,132

100.0%

Note: Column sums may differ from total because of rounding error. Source: Flow of Funds Accounts of the United States, Board of Governors of the Federal Reserve System, June 2001.

TA B L E 1.2

Assets

$ Billion

Domestic net worth

Real estate Plant and equipment Inventories

$17,438 18,643 1,350

Total

$37,431

Note: Column sums may differ from total because of rounding error. Sources: Flow of Funds Accounts of the United States, Board of Governors of the Federal Reserve System, June 2001; Statistical Abstract of the United States: 2000, US Census Bureau.

1. Are the following assets real or financial? a. Patents b. Lease obligations c. Customer goodwill d. A college education e. A $5 bill

1.2

A TAXONOMY OF FINANCIAL ASSETS

It is common to distinguish among three broad types of financial assets: fixed income, equity, and derivatives. Fixed-income securities promise either a fixed stream of income or a stream

24

Distinguish among the major assets that trade in money markets and in capital markets. Describe the construction of stock market indexes. Calculate the profit or loss on investments in options and futures contracts.

Bodie−Kane−Marcus: Essentials of Investments, Fifth Edition

I. Elements of Investments

2. Global Financial Instruments

Related Websites http://www.ceoexpress.com This site provides a list of links related to all aspects of business, including extensive sites related to finance and investment.

http://www.finpipe.com This is an excellent general site that is dedicated to finance education. It contains information on debt securities, equities, and derivative instruments.

http://www.nasdaq.com http://www.nyse.com http://www.bloomberg.com http://finance.yahoo.com These sites contain information on equity securities.

http://www.investinginbonds.com/ This site has extensive information on bonds and interest rates.

© The McGraw−Hill Companies, 2003

http://www.bondsonline.com/docs/bondprofessorglossary.html http://www.investorwords.com These two sites contain extensive glossaries of financial terms.

http://www.amex.com http://www.cboe.com/education http://www.cme.com http://www.commoditytrader.net http://www.erisk.com http://www.erivativesreview.com http://www.appliederivatives.com http://www.isda.org/index.html http://www.fiafii.org The above sites contain information on derivative securities

his chapter covers a range of financial securities and the markets in which they trade. Our goal is to introduce you to the features of various security types. This foundation will be necessary to understand the more analytic material that follows in later chapters. We first describe money market instruments. We then move on to debt and equity securities. We explain the structure of various stock market indexes in this chapter because market benchmark portfolios play an important role in portfolio construction and evaluation. Finally, we survey the derivative security markets for options and futures contracts. A summary of the markets, instruments, and indexes covered in this chapter appears in Table 2.1.

T

TA B L E 2.1 Financial markets and indexes

The money market Treasury bills Certificates of deposit Commercial paper Bankers’ acceptances Eurodollars Repos and reverses Federal funds Brokers’ calls Indexes Dow Jones averages Standard & Poor’s indexes Bond market indicators International indexes

The bond market Treasury bonds and notes Federal agency debt Municipal bonds Corporate bonds Mortgage-backed securities Equity markets Common stocks Preferred stocks Derivative markets Options Futures and forwards

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Part ONE Elements of Investments

2.1 money markets Include short-term, highly liquid, and relatively low-risk debt instruments.

capital markets Include longer-term, relatively riskier securities.

F I G U R E 2.1 Rates on money market securities Source: From The Wall Street Journal, October 19, 2001. Reprinted by permission of Dow Jones & Company, Inc. via Copyright Clearance Center, Inc. © 2001 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

THE MONEY MARKET

Financial markets are traditionally segmented into money markets and capital markets. Money market instruments include short-term, marketable, liquid, low-risk debt securities. Money market instruments sometimes are called cash equivalents, or just cash for short. Capital markets, in contrast, include longer-term and riskier securities. Securities in the capital market are much more diverse than those found within the money market. For this reason, we will subdivide the capital market into four segments: longer-term debt markets, equity markets, and the derivative markets for options and futures. The money market is a subsector of the debt market. It consists of very short-term debt securities that are highly marketable. Many of these securities trade in large denominations and so are out of the reach of individual investors. Money market mutual funds, however, are easily accessible to small investors. These mutual funds pool the resources of many investors and purchase a wide variety of money market securities on their behalf. Figure 2.1 is a reprint of a money rates listing from The Wall Street Journal. It includes the various instruments of the money market that we describe in detail below. Table 2.2 lists outstanding volume in 2000 of the major instruments of the money market.

Bodie−Kane−Marcus: Essentials of Investments, Fifth Edition

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2. Global Financial Instruments

Global Financial Instruments

27

U.S. Treasury bills (T-bills, or just bills, for short) are the most marketable of all money market instruments. T-bills represent the simplest form of borrowing. The government raises money by selling bills to the public. Investors buy the bills at a discount from the stated maturity value. At the bill’s maturity, the holder receives from the government a payment equal to the face value of the bill. The difference between the purchase price and the ultimate maturity value represents the investor’s earnings. T-bills with initial maturities of 28, 91, and 182 days are issued weekly. Sales are conducted by an auction where investors can submit competitive or noncompetitive bids. A competitive bid is an order for a given quantity of bills at a specific offered price. The order is filled only if the bid is high enough relative to other bids to be accepted. If the bid is high enough to be accepted, the bidder gets the order at the bid price. Thus, the bidder risks paying one of the highest prices for the same bill (bidding at the top), against the hope of bidding “at the tail,” that is, making the cutoff at the lowest price. A noncompetitive bid is an unconditional offer to purchase bills at the average price of the successful competitive bids. The Treasury ranks bids by offering price and accepts bids in order of descending price until the entire issue is absorbed by the competitive plus noncompetitive bids. Competitive bidders face two dangers: They may bid too high and overpay for the bills or bid too low and be shut out of the auction. Noncompetitive bidders, by contrast, pay the average price for the issue, and all noncompetitive bids are accepted up to a maximum of $1 million per bid. Individuals can purchase T-bills directly at the auction or on the secondary market from a government securities dealer. T-bills are highly liquid; that is, they are easily converted to cash and sold at low transaction cost and with little price risk. Unlike most other money market instruments, which sell in minimum denominations of $100,000, T-bills sell in minimum denominations of only $10,000. While the income earned on T-bills is taxable at the Federal level, it is exempt from all state and local taxes, another characteristic distinguishing T-bills from other money market instruments.

Treasury bills

2

Treasury Bills

Certificates of Deposit A certificate of deposit (CD) is a time deposit with a bank. Time deposits may not be withdrawn on demand. The bank pays interest and principal to the depositor only at the end of the $ Billion

TA B L E 2.2 Components of the money market

Repurchase agreements Small-denomination time deposits* Large-denomination time deposits† Bankers’ acceptances Eurodollars Treasury bills Commercial paper Savings deposits Money market mutual funds

354.3 1,037.8 766.0 7.8 196.1 682.1 1,539.0 1,852.6 1,657.1

*

Small denominations are less than $100,000.

†

Large denominations are greater than or equal to $100,000.

Source: Economic Report of the President, U.S. Government Printing Office, 2001; and Flow of Funds Accounts: Flows and Outstandings, Board of Governors of the Federal Reserve System, June 2000.

Short-term government securities issued at a discount from face value and returning the face amount at maturity.

certificate of deposit A bank time deposit.

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fixed term of the CD. CDs issued in denominations larger than $100,000 are usually negotiable, however; that is, they can be sold to another investor if the owner needs to cash in the certificate before its maturity date. Short-term CDs are highly marketable, although the market significantly thins out for maturities of three months or more. CDs are treated as bank deposits by the Federal Deposit Insurance Corporation, so they are insured for up to $100,000 in the event of a bank insolvency.

Commercial Paper

commercial paper Short-term unsecured debt issued by large corporations.

The typical corporation is a net borrower of both long-term funds (for capital investments) and short-term funds (for working capital). Large, well-known companies often issue their own short-term unsecured debt notes directly to the public, rather than borrowing from banks. These notes are called commercial paper (CP). Sometimes, CP is backed by a bank line of credit, which gives the borrower access to cash that can be used if needed to pay off the paper at maturity. CP maturities range up to 270 days; longer maturities require registration with the Securities and Exchange Commission and so are almost never issued. CP most commonly is issued with maturities of less than one or two months in denominations of multiples of $100,000. Therefore, small investors can invest in commercial paper only indirectly, through money market mutual funds. CP is considered to be a fairly safe asset, given that a firm’s condition presumably can be monitored and predicted over a term as short as one month. It is worth noting, though, that many firms issue commercial paper intending to roll it over at maturity, that is, issue new paper to obtain the funds necessary to retire the old paper. If lenders become complacent about monitoring a firm’s prospects and grant rollovers willy-nilly, they can suffer big losses. When Penn Central defaulted in 1970, it had $82 million of commercial paper outstanding—the only major default on commercial paper in the past 40 years. CP trades in secondary markets and so is quite liquid. Most issues are rated by at least one agency such as Standard & Poor’s. The yield on CP depends on the time to maturity and the credit rating.

Bankers’ Acceptances bankers’ acceptance An order to a bank by a customer to pay a sum of money at a future date.

A bankers’ acceptance starts as an order to a bank by a bank’s customer to pay a sum of money at a future date, typically within six months. At this stage, it is like a postdated check. When the bank endorses the order for payment as “accepted,” it assumes responsibility for ultimate payment to the holder of the acceptance. At this point, the acceptance may be traded in secondary markets much like any other claim on the bank. Bankers’ acceptances are considered very safe assets, as they allow traders to substitute the bank’s credit standing for their own. They are used widely in foreign trade where the creditworthiness of one trader is unknown to the trading partner. Acceptances sell at a discount from the face value of the payment order, just as T-bills sell at a discount from par value.

Eurodollars Eurodollars Dollar-denominated deposits at foreign banks or foreign branches of American banks.

Eurodollars are dollar-denominated deposits at foreign banks or foreign branches of American banks. By locating outside the United States, these banks escape regulation by the Federal Reserve Board. Despite the tag “Euro,” these accounts need not be in European banks, although that is where the practice of accepting dollar-denominated deposits outside the United States began.

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Most Eurodollar deposits are for large sums, and most are time deposits of less than six months’ maturity. A variation on the Eurodollar time deposit is the Eurodollar certificate of deposit. A Eurodollar CD resembles a domestic bank CD except it is the liability of a non-U.S. branch of a bank, typically a London branch. The advantage of Eurodollar CDs over Eurodollar time deposits is that the holder can sell the asset to realize its cash value before maturity. Eurodollar CDs are considered less liquid and riskier than domestic CDs, however, and so offer higher yields. Firms also issue Eurodollar bonds, that is, dollar-denominated bonds outside the U.S., although such bonds are not a money market investment by virtue of their long maturities.

Repos and Reverses Dealers in government securities use repurchase agreements, also called repos, or RPs, as a form of short-term, usually overnight, borrowing. The dealer sells securities to an investor on an overnight basis, with an agreement to buy back those securities the next day at a slightly higher price. The increase in the price is the overnight interest. The dealer thus takes out a oneday loan from the investor. The securities serve as collateral for the loan. A term repo is essentially an identical transaction, except the term of the implicit loan can be 30 days or more. Repos are considered very safe in terms of credit risk because the loans are backed by the government securities. A reverse repo is the mirror image of a repo. Here, the dealer finds an investor holding government securities and buys them with an agreement to resell them at a specified higher price on a future date.

repurchase agreements (repos) Short-term sales of government securities with an agreement to repurchase the securities at a higher price.

Brokers’ Calls Individuals who buy stocks on margin borrow part of the funds to pay for the stocks from their broker. The broker in turn may borrow the funds from a bank, agreeing to repay the bank immediately (on call) if the bank requests it. The rate paid on such loans is usually about one percentage point higher than the rate on short-term T-bills.

Federal Funds Just as most of us maintain deposits at banks, banks maintain deposits of their own at the Federal Reserve Bank, or the Fed. Each member bank of the Federal Reserve System is required to maintain a minimum balance in a reserve account with the Fed. The required balance depends on the total deposits of the bank’s customers. Funds in the bank’s reserve account are called Federal funds or Fed funds. At any time, some banks have more funds than required at the Fed. Other banks, primarily big New York and other financial center banks, tend to have a shortage of Federal funds. In the Federal funds market, banks with excess funds lend to those with a shortage. These loans, which are usually overnight transactions, are arranged at a rate of interest called the Federal funds rate. While the Fed funds rate is not directly relevant to investors, it is used as one of the barometers of the money market and so is widely watched by them.

Federal funds Funds in the accounts of commercial banks at the Federal Reserve Bank.

The LIBOR Market The London Interbank Offer Rate (LIBOR) is the rate at which large banks in London are willing to lend money among themselves. This rate has become the premier short-term interest rate quoted in the European money market and serves as a reference rate for a wide range of transactions. A corporation might borrow at a rate equal to LIBOR plus two percentage points, for example. Like the Fed funds rate, LIBOR is a statistic widely followed by investors.

LIBOR Lending rate among banks in the London market.

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5.0

OPEC I

4.5 4.0 Percentage points

3.5

OPEC II Penn Square

3.0 2.5

Market Crash

2.0

LTCM

1.5 1.0 0.5 0 1970

1975

1980

1985

1990

1995

2000

F I G U R E 2.2 Spread between three-month CD and T-bill rates

Yields on Money Market Instruments Although most money market securities are of low risk, they are not risk-free. As we noted earlier, the commercial paper market was rocked by the Penn Central bankruptcy, which precipitated a default on $82 million of commercial paper. Money market investments became more sensitive to creditworthiness after this episode, and the yield spread between low- and high-quality paper widened. The securities of the money market do promise yields greater than those on default-free T-bills, at least in part because of greater relative riskiness. Investors who require more liquidity also will accept lower yields on securities, such as T-bills, that can be more quickly and cheaply sold for cash. Figure 2.2 shows that bank CDs, for example, consistently have paid a risk premium over T-bills. Moreover, that risk premium increases with economic crises such as the energy price shocks associated with the Organization of Petroleum Exporting Countries (OPEC) disturbances, the failure of Penn Square Bank, the stock market crash in 1987, or the collapse of Long Term Capital Management in 1998.

2.2

THE BOND MARKET

The bond market is composed of longer-term borrowing or debt instruments than those that trade in the money market. This market includes Treasury notes and bonds, corporate bonds, municipal bonds, mortgage securities, and federal agency debt. These instruments are sometimes said to comprise the fixed-income capital market, because most of them promise either a fixed stream of income or stream of income that is determined according to a specified formula. In practice, these formulas can result in a flow of

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Global Financial Instruments

F I G U R E 2.3 Listing of Treasury issues Source: From The Wall Street Journal, October 19, 2001. Reprinted by permission of Dow Jones & Company, Inc. via Copyright Clearance Center, Inc. © 2001 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

income that is far from fixed. Therefore, the term “fixed income” is probably not fully appropriate. It is simpler and more straightforward to call these securities either debt instruments or bonds.

Treasury Notes and Bonds The U.S. government borrows funds in large part by selling Treasury notes and bonds. T-note maturities range up to 10 years, while T-bonds are issued with maturities ranging from 10 to 30 years. The Treasury announced in late 2001 that it would no longer issue bonds with maturities beyond 10 years. Nevertheless, investors often refer to all of these securities collectively as Treasury or T-bonds. They are issued in denominations of $1,000 or more. Both bonds and notes make semiannual interest payments called coupon payments, so named because in precomputer days, investors would literally clip a coupon attached to the bond and present it to an agent of the issuing firm to receive the interest payment. Aside from their differing maturities at issuance, the only major distinction between T-notes and T-bonds is that Tbonds may be callable during a given period, usually the last five years of the bond’s life. The call provision gives the Treasury the right to repurchase the bond at par value. While callable T-bonds still are outstanding, the Treasury no longer issues callable bonds. Figure 2.3 is an excerpt from a listing of Treasury issues in The Wall Street Journal. The highlighted bond matures in August 2009. The coupon income or interest paid by the bond is 6% of par value, meaning that for a $1,000 face value bond, $60 in annual interest payments will be made in two semiannual installments of $30 each. The numbers to the right of the colon in the bid and ask prices represent units of 1⁄32 of a point.

Treasury notes or bonds Debt obligations of the federal government with original maturities of one year or more.

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The bid price of the highlighted bond is 110 6⁄32, or 110.1875. The ask price is 110 9⁄32, or 110.28125. Although bonds are sold in denominations of $1,000 par value, the prices are quoted as a percentage of par value. Thus, the ask price of 110.28125 should be interpreted as 110.28125% of par or $1,102.8125 for the $1,000 par value bond. Similarly, the bond could be sold to a dealer for $1,101.875. The ⫺3 change means the closing price on this day fell 3⁄32 (as a percentage of par value) from the previous day’s closing price. Finally, the yield to maturity on the bond based on the ask price is 4.43%. The yield to maturity reported in the last column is a measure of the annualized rate of return to an investor who buys the bond and holds it until maturity. It is calculated by determining the semiannual yield and then doubling it, rather than compounding it for two half-year periods. This use of a simple interest technique to annualize means that the yield is quoted on an annual percentage rate (APR) basis rather than as an effective annual yield. The APR method in this context is also called the bond equivalent yield. We discuss the yield to maturity in detail in Chapter 9.

Federal Agency Debt Some government agencies issue their own securities to finance their activities. These agencies usually are formed for public policy reasons to channel credit to a particular sector of the economy that Congress believes is not receiving adequate credit through normal private sources. Figure 2.4 reproduces listings of some of these securities from The Wall Street Journal. The major mortgage-related agencies are the Federal Home Loan Bank (FHLB), the Federal National Mortgage Association (FNMA, or Fannie Mae), the Government National Mortgage Association (GNMA, or Ginnie Mae), and the Federal Home Loan Mortgage Corporation (FHLMC, or Freddie Mac). Freddie Mac, Fannie Mae, and Ginnie Mae were organized to provide liquidity to the mortgage market. Until establishment of the pass-through securities sponsored by these government agencies, the lack of a secondary market in mortgages hampered the flow of investment

F I G U R E 2.4 Listing of government agency securities Source: From The Wall Street Journal, October 19, 2001. Reprinted by permission of Dow Jones & Company, Inc. via Copyright Clearance Center, Inc. © 2001 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

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funds into mortgages and made mortgage markets dependent on local, rather than national, credit availability. The pass-through financing initiated by these agencies represents one of the most important financial innovations of the 1980s. Although the debt of federal agencies is not explicitly insured by the federal government, it is assumed the government will assist an agency nearing default. Thus, these securities are considered extremely safe assets, and their yield spread over Treasury securities is usually small. 1. Using Figures 2.3 and 2.4, compare the yield to maturity on one of the agency bonds with that of the T-bond with the nearest maturity date.

> > > >

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Describe the role of investment bankers in primary issues. Identify the various security markets. Compare trading practices in stock exchanges with those in dealer markets. Describe the role of brokers. Compare the mechanics and investment implications of buying on margin and short selling.

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Related Websites http://www.nasdaq.com www.nyse.com http://www.amex.com These sites contain information and listing requirements for each of the markets. They also provide substantial data on equities.

http://www.spglobal.com This site contains information on construction of Standard & Poor’s Indexes and has links to most major exchanges.

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http://www.ipo.com http://www.unlockdates.com http://www.123jump.com/ipomaven.htm http://moneycentral.msn.com/investor/market/ipo main.asp These sites contain information on initial public offerings.

http://www.sec.gov/index.htm http://www.nasdr.com These sites provide information on market regulation and trading.

he first time a security trades is when it is issued. Therefore, we begin our examination of trading with a look at how securities are first marketed to the public by investment bankers, the midwives of securities. Then, we turn to the various exchanges where already-issued securities can be traded among investors. We examine the competition among the New York Stock Exchange, regional exchanges, Nasdaq, and several foreign markets for the patronage of security traders. Next, we turn to the mechanics of trading in these various markets. We describe the role of the specialist in exchange markets and the dealer in over-the-counter markets. We also touch briefly on block trading and the SuperDot system of the NYSE for electronically routing orders to the floor of the exchange. We discuss the costs of trading and consider the ongoing debate between the NYSE and its competitors over which market provides the lowest-cost trading arena. Finally, we describe the essentials of specific transactions, such as buying on margin and selling stock short and discuss relevant regulations governing security trading. In the process, we will see that some regulations, such as those governing insider trading, can be difficult to interpret in practice.

T

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Market for new issues of securities.

secondary market Market for alreadyexisting securities.

initial public offering (IPO) First sale of stock by a formerly private company.

underwriters Underwriters purchase securities from the issuing company and resell them.

prospectus A description of the firm and the security it is issuing.

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3.1 primary market

I. Elements of Investments

HOW FIRMS ISSUE SECURITIES

When firms need to raise capital they may choose to sell or float securities. These new issues of stocks, bonds, or other securities typically are marketed to the public by investment bankers in what is called the primary market. Trading of already-issued securities among investors occurs in the secondary market. There are two types of primary market issues of common stock. Initial public offerings, or IPOs, are stocks issued by a formerly privately owned company that is going public, that is, selling stock to the public for the first time. Seasoned new issues are offered by companies that already have floated equity. For example, a sale by IBM of new shares of stock would constitute a seasoned new issue. In the case of bonds, we also distinguish between two types of primary market issues, a public offering and a private placement. The former refers to an issue of bonds sold to the general investing public that can then be traded on the secondary market. The latter refers to an issue that usually is sold to one or a few institutional investors and is generally held to maturity.

Investment Banking Public offerings of both stocks and bonds typically are marketed by investment bankers who in this role are called underwriters. More than one investment banker usually markets the securities. A lead firm forms an underwriting syndicate of other investment bankers to share the responsibility for the stock issue. Investment bankers advise the firm regarding the terms on which it should attempt to sell the securities. A preliminary registration statement must be filed with the Securities and Exchange Commission (SEC), describing the issue and the prospects of the company. This preliminary prospectus is known as a red herring because it includes a statement printed in red, stating that the company is not attempting to sell the security before the registration is approved. When the statement is in final form, and approved by the SEC, it is called the prospectus. At this point, the price at which the securities will be offered to the public is announced. In a typical underwriting arrangement, the investment bankers purchase the securities from the issuing company and then resell them to the public. The issuing firm sells the securities to the underwriting syndicate for the public offering price less a spread that serves as compensation to the underwriters. This procedure is called a firm commitment; the underwriters receive the issue and assume the risk that the shares cannot be sold to the public at the stipulated offering price. Figure 3.1 depicts the relationships among the firm issuing the security, the lead underwriter, the underwriting syndicate, and the public. An alternative to the firm commitment is the best-efforts agreement. In this case, the investment banker does not actually purchase the securities but agrees to help the firm sell the issue to the public. The banker simply acts as an intermediary between the public and the firm and does not bear the risk of not being able to resell purchased securities at the offering price. The best-efforts procedure is more common for initial public offerings of common stock, where the appropriate share price is less certain. Corporations engage investment bankers either by negotiation or competitive bidding, although negotiation is far more common. In addition to the compensation resulting from the spread between the purchase price and the public offering price, an investment banker may receive shares of common stock or other securities of the firm. As part of its marketing of the firm’s securities, the underwriting syndicate typically takes out advertisements in the financial press to announce the prospective sale. An example of

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F I G U R E 3.1

Issuing firm

Relationship among a firm issuing securities, the underwriters, and the public

Lead underwriter Underwriting syndicate Investment Banker A

Investment Banker B

Investment Banker C

Investment Banker D

Private investors

these so-called tombstone advertisements is given in Figure 3.2. The underwriters plan to sell 115 million shares of stock at a price of $18.50 each, to raise $2,127.5 million for the Principal Financial Group. The four lead underwriters are presented in larger type; the firms taking a smaller role in marketing the securities are presented below in smaller type. Most of the shares will be sold in the U.S., but 15% of the issue will be sold abroad. Notice that the underwriters for the non-U.S. portion of the issue have far greater international representation.

Shelf Registration An important innovation in the issuing of securities was introduced in 1982 when the SEC approved Rule 415, which allows firms to register securities and gradually sell them to the public for two years following the initial registration. Because the securities are already registered, they can be sold on short notice, with little additional paperwork. Moreover, they can be sold in small amounts without incurring substantial flotation costs. The securities are “on the shelf,” ready to be issued, which has given rise to the term shelf registration. 1. Why does it make sense for shelf registration to be limited in time?

Private Placements Primary offerings also can be sold in a private placement rather than a public offering. In this case, the firm (using an investment banker) sells shares directly to a small group of institutional or wealthy investors. Private placements can be far cheaper than public offerings. This is because Rule 144A of the SEC allows corporations to make these placements without preparing the extensive and costly registration statements required of a public offering. On the other hand, because private placements are not made available to the general public, they generally will be less suited for very large offerings. Moreover, private placements do not trade in secondary markets like stock exchanges. This greatly reduces their liquidity and presumably reduces the prices that investors will pay for the issue.

Initial Public Offerings Investment bankers manage the issuance of new securities to the public. Once the SEC has commented on the registration statement and a preliminary prospectus has been distributed to

The third market refers to trading of exchange-listed securities on the over-the-counter market. In the past, members of an exchange were required to execute all their trades of exchangelisted securities on the exchange and to charge commissions according to a fixed schedule. This procedure was disadvantageous to large traders when it prevented them from realizing economies of scale on large trades. Because of this restriction, brokerage firms that were not members of the NYSE and so not bound by its rules, established trading in the OTC market of large NYSE-listed stocks. These trades could be accomplished at lower commissions than would have been charged on the NYSE, and the third market grew dramatically until 1972, when the NYSE allowed negotiated commissions on orders exceeding $300,000. On May 1, 1975, frequently referred to as “May Day,” commissions on all NYSE orders became negotiable, and they have been ever since. 2. Look again at Table 3.1, which gives the history of seat prices on the NYSE. Interpret the data for 1975 in light of the changes instituted on May Day. The fourth market refers to direct trading between investors in exchange-listed securities without the benefit of a broker. The direct trading among investors that characterizes the fourth market has exploded in recent years due to the advent of electronic communication networks, or ECNs. ECNs are an alternative to either formal stock exchanges like the NYSE or dealer markets like Nasdaq for trading securities. These ECNs allow members to post buy or sell orders and to have those orders matched up or “crossed” with orders of other traders in

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the system. Both sides of the trade benefit because direct crossing eliminates the bid–ask spread that otherwise would be incurred. Early versions of ECNs were available exclusively to large institutional traders. In addition to cost savings, systems such as Instinet and Posit allowed these large traders greater anonymity than they could otherwise achieve. This was important to the traders since they did not want to publicly signal their desire to buy or sell large quantities of shares for fear of moving prices in advance of their trades. Posit also enabled trading in portfolios as well as individual stocks. ECNs have captured about 30% of the trading volume in Nasdaq-listed stocks. They must be certified by the SEC and registered with the National Association of Security Dealers to participate in the Nasdaq market. Table 3.5 is a list of registered ECNs at the start of 2001. While small investors today typically do not access an ECN directly, they can send orders through their brokers, including online brokers, who can then have the order executed on the ECN. Eventually, individuals will likely have direct access to most ECNs through the Internet. In fact, several financial firms (Goldman, Sachs; Merrill Lynch; Salomon Smith Barney; Morgan Stanley; and Bernard Madoff) have combined to build an electronic trading network called Primex, which is open to NASD broker/dealers, who in turn have the ability to offer public access to the market. Other ECNs, such as Instinet, which have traditionally served institutional investors, are considering opening up their services to retail brokerages. The advent of ECNs is putting increasing pressure on the NYSE to respond. In particular, big brokerage firms such as Goldman, Sachs and Merrill Lynch are calling for the NYSE to beef up its capabilities to automate orders without human intervention. Moreover, as they push the NYSE to change, these firms are hedging their bets by investing in ECNs on their own. The NYSE also has announced its intention to go public. In its current organization as a member-owned cooperative, it needs the approval of members to institute major changes. However, many of these members are precisely the floor brokers who will be most hurt by electronic trading. This has made it difficult for the NYSE to respond flexibly to the challenge of electronic trading. By converting to a publicly held for-profit corporate organization, it hopes to be able to compete more vigorously in the marketplace of stock markets.

fourth market

3

TA B L E 3.5 Registered Electronic Communication Networks (ECNs)

Archipelago Attain B-Trade Services The BRASS Utility Instinet Corporation The Island ECN Market XT NexTrade REDIbook

Source: Nasdaq in Black & White, Nasdaq, 2001.

The National Market System The Securities Act Amendments of 1975 directed the Securities and Exchange Commission to implement a national competitive securities market. Such a market would entail centralized reporting of transactions and a centralized quotation system, with the aim of enhanced competition among market makers. In 1975, Consolidated Tape began reporting trades on the NYSE, Amex, and major regional exchanges, as well as trades of Nasdaq-listed stocks. In 1977, the Consolidated Quotations Service began providing online bid and ask quotes for NYSE securities also traded on various other exchanges. This has enhanced competition by allowing market participants, including

Direct trading in exchange-listed securities between one investor and another without the benefit of a broker.

electronic communication networks (ECNs) Computer networks that allow direct trading without the need for market makers.

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brokers or dealers who are at different locations, to interact and for orders to be directed to the market in which the best price can be obtained. In 1978, the Intermarket Trading System (ITS) was implemented. ITS currently links nine exchanges by computer (NYSE, Amex, Boston, Cincinnati, Pacific, Philadelphia, Chicago, Nasdaq, and the Chicago Board Options Exchange). Nearly 5,000 issues are eligible for trading on the ITS; these account for most of the securities that are traded on more than one exchange. The system allows brokers and market makers to display and view quotes for all markets and to execute cross-market trades when the Consolidated Quotation System shows better prices in other markets. For example, suppose a specialist firm on the Boston Exchange is currently offering to buy a security for $20, but a broker in Boston who is attempting to sell shares for a client observes a superior bid price on the NYSE, say $20.12. The broker should route the order to the specialist’s post on the NYSE, where it can be executed at the higher price. The transaction is then reported on the Consolidated Tape. Moreover, a specialist who observes a better price on another exchange is also expected either to match that price or route the trade to that market. While the ITS does much to unify markets, it has some important shortcomings. First, it does not provide for automatic execution in the market with the best price. The trade must be directed there by a market participant, who might find it inconvenient (or unprofitable) to do so. Moreover, some feel that the ITS is too slow to integrate prices off the NYSE. A logical extension of the ITS as a means to integrate securities markets would be the establishment of a central limit order book. Such an electronic “book” would contain all orders conditional on both prices and dates. All markets would be linked and all traders could compete for all orders. While market integration seems like a desirable goal, the recent growth of ECNs has led to some concern that markets are in fact becoming more fragmented. This is because participants in one ECN do not necessarily know what prices are being quoted on other networks. ECNs do display their best-priced offers on the Nasdaq system, but other limit orders are not available. Only stock exchanges may participate in the Intermarket Trading System, which means that ECNs are excluded. Moreover, during the after-hours trading enabled by ECNs, trades take place on these private networks while other larger markets are closed, and current prices for securities are harder to access. In the wake of growing concern about market fragmentation, some big Wall Street brokerage houses have called for an electronically driven central limit order book. But full market integration has proven to be elusive.

Bond Trading The New York Stock Exchange also operates a bond exchange where U.S. government, corporate, municipal, and foreign bonds may be traded. The centerpiece of the NYSE bond market is the Automated Bond System (ABS), which is an automated trading system that allows trading firms to obtain market information, to enter and execute trades over a computer network, and to receive immediate confirmations of trade execution. However, the vast majority of bond trading occurs in the OTC market among bond dealers, even for bonds that are actually listed on the NYSE. This market is a network of bond dealers such as Merrill Lynch, Salomon Smith Barney, or Goldman, Sachs that is linked by a computer quotation system. However, because these dealers do not carry extensive inventories of the wide range of bonds that have been issued to the public, they cannot necessarily offer to sell bonds from their inventory to clients or even buy bonds for their own inventory. They may instead work to locate an investor who wishes to take the opposite side of a trade. In practice, however, the corporate bond market often is quite “thin,” in that there may be few investors interested in trading a bond at any particular time. As a result, the bond market is subject to a type of liquidity risk, for it can be difficult to sell one’s holdings quickly if the need arises.

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WEBMA STER Electronic Communication Networks Go to the New York Federal Reserve’s website, http://www.ny.frb.org/rmaghome/ curr_iss/ci6-12. html, to read “The Emergence of Electronic Communication Networks (ECNs) in the U.S. Equity Markets,” by James McAndrews and Chris Stefanadis, researchers at the Federal Reserve Bank of New York. After reading this article, answer the following questions: 1.

What is an ECN and how does it differ from a traditional market such as the NYSE?

2.

List and briefly describe the four potential advantages of an ECN as identified by the authors.

3.

What risk is related to the fragmentation that may accompany the development of the ECNs?

Listing Requirements Go to www.nasdaq.com/sitemap/sitemap.stm. On the sitemap there is an item labeled listing information. Select that item and identify the following items in Initial Listing Standards for the National Market System 1, 2, and 3 and the Nasdaq SmallCap Market for domestic companies: 1.

Public float in millions of shares.

2.

Market value of public float.

3.

Shareholders of round lots.

Go to www.nyse.com and select the listed company item or information bullet. Under the bullet select the listing standards tab. Identify the same items for NYSE (U.S. Standards) initial listing requirements. 4.

3.3

In what two categories are the listing requirements most significantly different?

TRADING ON EXCHANGES

Most of the information in this section applies to all securities traded on exchanges. Some of it, however, applies just to stocks, and in such cases we use the specific words, stocks or shares.

The Participants We begin our discussion of the mechanics of exchange trading with a brief description of the potential parties to a trade. When an investor instructs a broker to buy or sell securities, a number of players must act to consummate the deal. The investor places an order with a broker. The brokerage firm for which the broker works, and which owns a seat on the exchange, contacts its commission broker, who is on the floor of the exchange, to execute the order. When the firm’s commission brokers are overloaded and have too many orders to handle, they will use the services of floor brokers, who are independent members of the exchange (and own seats), to execute orders. The specialist is central to the trading process. All trading in a given stock takes place at one location on the floor of the exchange called the specialist’s post. At the specialist’s post is a monitor called the Display Book that presents all the current offers from interested traders to buy or sell shares at various prices as well as the number of shares these quotes are good for.

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The specialist manages the trading in the stock. The market making responsibility for each stock is assigned by the NYSE to one specialist firm. There is only one specialist firm per stock but most firms will have responsibility for trading in several stocks. The specialist firm also may act as a dealer in the stock, trading for its own account. We will examine the role of the specialist in more detail shortly.

Types of Orders Market orders Market orders are simply buy or sell orders that are to be executed immediately at current market prices. For example, an investor might call his broker and ask for the market price of IBM. The retail broker will wire this request to the commission broker on the floor of the exchange, who will approach the specialist’s post and ask the specialist for best current quotes. Finding that the current quotes are $98 per share bid, and $98.10 asked, the investor might direct the broker to buy 100 shares “at market,” meaning that he is willing to pay $98.10 per share for an immediate transaction. Similarly, an order to “sell at market” will result in stock sales at $98 per share. (Until 2001, when U.S. markets adopted decimal pricing, the minimum possible bid–ask spread was “one tick,” which on the NYSE was $ 1⁄8 until 1997 and $ 1⁄16 thereafter. With decimal pricing, the spread can be far lower.) When a trade is executed, the specialist’s clerk will fill out an order card that reports the time, price, and quantity of shares traded and the transaction will be reported on the exchange’s ticker tape. There are two potential complications to this simple scenario, however. First, as noted earlier, the posted quotes of $98 and $98.10 actually represent commitments to trade up to a specified number of shares. If the market order is for more than this number of shares, the order may be filled at multiple prices. For example, if the asked price is good for orders up to 600 shares and the investor wishes to purchase 1,000 shares, it may be necessary to pay a slightly higher price for the last 400 shares than the quoted asked price. The second complication arises from the possibility of trading “inside the quoted spread.” If the broker who has received a market buy order for IBM meets another broker who has received a market sell order for IBM, they can agree to trade with each other at a price of $98.05 per share. By meeting in the middle of the quoted spread, both the buyer and the seller obtain “price improvements,” that is, transaction prices better than the best quoted prices. Such “meetings” of brokers are more than accidental. Because all trading takes place at the specialist’s post, floor brokers know where to look for counterparties to take the other side of a trade.

Limit orders Investors also may choose to place a limit order, where they specify prices at which they are willing to buy or sell a security. If IBM is selling at $98 bid, $98.10 asked, for example, a limit buy order may instruct the broker to buy the stock if and when the share price falls below $97. Correspondingly, a limit sell order instructs the broker to sell as soon as the stock price goes above the specified limit. Figure 3.5 is a portion of the limit order book for shares in Intel on the Island exchange on one day in 2001. Notice that the best orders are at the top of the list: the offers to buy at the highest price and to sell at the lowest price. The buy and sell orders at the top of the list— $27.88 and $27.93—are called the inside quotes; they are the buy and sell orders with the closest prices. For Intel, the inside spread is only 5 cents per share. What happens if a limit order is placed in between the quoted bid and ask prices? For example, suppose you have instructed your broker to buy IBM at a price of $98.05 or better. The order may not be executed immediately, since the quoted asked price for the shares is $98.10, which is more than you are willing to pay. However, your willingness to buy at $98.05 is better than the quoted bid price of $98 per share. Therefore, you may find that there are traders who were unwilling to sell their shares at the currently quoted $98 bid price but are happy to sell shares to you at your higher bid price of $98.05.

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refresh

island home

disclamer

help GET STOCK INTC go

INTC LAST MATCH Price 27.8900 Time 14:24:45

TODAY’S ACTIVITY Orders 16,774 Volume 4,631,778

BUY ORDERS Shares Price 100 27.8800 500 27.8500 200 27.8500 1,000 27.8200 3,300 27.8100 300 27.8000 75 27.7500 101 27.7300 5,000 27.7200 1,000 27.72 (416 more)

SELL ORDERS Shares Price 1,000 27.9300 1,000 27.9690 1,000 27.9800 1,000 27.9900 1,000 28.0000 1,800 28.0600 1,000 28.0800 1,000 28.1000 2,000 28.1100 1,000 28,1800 (395 more)

Condition Price below Price above the limit the limit

Limit buy order

Stop-buy order

Sell

Stop-loss order

Limit sell order

Action

Buy

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How Securities Are Traded

Stop-loss orders are similar to limit orders in that the trade is not to be executed unless the stock hits a price limit. Here, however, the stock is to be sold if its price falls below a stipulated level. As the name suggests, the order lets the stock be sold to stop further losses from accumulating. Similarly, stop-buy orders specify that a stock should be bought when its price rises above a limit. These trades often accompany short sales (sales of securities you don’t own but have borrowed from your broker) and are used to limit potential losses from the short position. Short sales are discussed in greater detail later in this chapter. Figure 3.6 organizes these types of trades in a convenient matrix. Orders also can be limited by a time period. Day orders, for example, expire at the close of the trading day. If it is not executed on that day, the order is canceled. Open or good-tillcanceled orders, in contrast, remain in force for up to six months, unless canceled by the customer.

F I G U R E 3.5 The limit order book for Intel on the Island exchange, November 9, 2001.

F I G U R E 3.6 Limit orders

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Specialists and the Execution of Trades specialist A trader who makes a market in the shares of one or more firms and who maintains a “fair and orderly market” by dealing personally in the market.

A specialist “makes a market” in the shares of one or more firms. This task may require the specialist to act as either a broker or a dealer. The specialist’s role as a broker is simply to execute the orders of other brokers. Specialists also may buy or sell shares of stock for their own portfolios. When no other broker can be found to take the other side of a trade, specialists will do so even if it means they must buy for or sell from their own accounts. The NYSE commissions these companies to perform this service and monitors their performance. Part of the specialist’s job as a broker is simply clerical. The specialist maintains a “book” listing all outstanding unexecuted limit orders entered by brokers on behalf of clients. Actually, the book is now a computer console. When limit orders can be executed at market prices, the specialist executes, or “crosses,” the trade. The specialist is required to use the highest outstanding offered purchase price and the lowest outstanding offered selling price when matching trades. Therefore, the specialist system results in an auction market, meaning all buy and all sell orders come to one location, and the best orders “win” the trades. In this role, the specialist acts merely as a facilitator. The more interesting function of the specialist is to maintain a “fair and orderly market” by acting as a dealer in the stock. In return for the exclusive right to make the market in a specific stock on the exchange, the specialist is required by the exchange to maintain an orderly market by buying and selling shares from inventory. Specialists maintain their own portfolios of stock and quoted bid and ask prices at which they are obligated to meet at least a limited amount of market orders. If market buy orders come in, specialists must sell shares from their own accounts at the ask price; if sell orders come in, they must stand willing to buy at the listed bid price.4 Ordinarily, however, in an active market, specialists can match buy and sell orders without using their own accounts. That is, the specialist’s own inventory of securities need not be the primary means of order execution. Sometimes, the specialist’s bid and ask prices are better than those offered by any other market participant. Therefore, at any point, the effective ask price in the market is the lower of either the specialist’s ask price or the lowest of the unfilled limit-sell orders. Similarly, the effective bid price is the highest of the unfilled limit buy orders or the specialist’s bid. These procedures ensure that the specialist provides liquidity to the market. In practice, specialists participate in approximately one-quarter of the transactions on the NYSE. By standing ready to trade at quoted bid and ask prices, the specialist is exposed to exploitation by other traders. Larger traders with ready access to superior information will trade with specialists when the specialist’s quotes are temporarily out of line with assessments of value based on that information. Specialists who cannot match the information resources of large traders will be at a disadvantage when their quoted prices offer profit opportunities to more advantaged traders. You might wonder why specialists do not protect their interests by setting a low bid price and a high ask price. Specialists using that strategy would protect themselves from losses in a period of dramatic movements in the stock price. In contrast, specialists who offer a narrow spread between the bid and ask price have little leeway for error and must constantly monitor market conditions to avoid offering other investors advantageous terms. Large bid–ask spreads are not viable options for the specialist for two reasons. First, one source of the specialist’s income is frequent trading at the bid and ask prices, with the spread as a trading profit. A too-large spread would make the specialist’s quotes uncompetitive with the limit orders placed by other traders. If the specialist’s bid and asked quotes are consistently 4

The specialist’s published quotes are valid only for a given number of shares. If a buy or sell order is placed for more shares than the quotation size, the specialist has the right to revise the quote.

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worse than those of public traders, the specialist will not participate in any trades and will lose the ability to profit from the bid–ask spread. An equally important reason that specialists cannot use large bid–ask spreads to protect their interests is that they are obligated to provide price continuity to the market. To illustrate the principle of price continuity, suppose the highest limit buy order for a stock is $30, while the lowest limit sell order is $32. When a market buy order comes in, it is matched to the best limit sell at $32. A market sell order would be matched to the best limit buy at $30. As market buys and sells come to the floor randomly, the stock price would fluctuate between $30 and $32. The exchange authorities would consider this excessive volatility, and the specialist would be expected to step in with bid and/or ask prices between these values to reduce the bid–ask spread to an acceptable level, typically less than $.15 for large firms. When a firm is newly listed on an exchange, specialist firms vigorously compete to be awarded the rights by the exchange to maintain the market in those shares. Since specialists are evaluated on their past performance in maintaining price continuity, they have considerable incentive to maintain tight spreads. Specialists earn income both from commissions for acting as brokers for orders and from the spreads at which they buy and sell securities. Some believe specialists’ access to their “books” of limit orders gives them unique knowledge about the probable direction of price movement over short periods of time. However, these days, interested floor traders also have access to the Display Books of outstanding limit orders. For example, suppose the specialist sees that a stock now selling for $45 has limit buy orders for over 100,000 shares at prices ranging from $44.50 to $44.75. This latent buying demand provides a cushion of support, in that it is unlikely that enough sell pressure will come in during the next few hours to cause the price to drop below $44.50. If there are very few limit sell orders above $45, in contrast, some transient buying demand could raise the price substantially. The specialist in such circumstances realizes that a position in the stock offers little downside risk and substantial upside potential. Such access to the trading intentions of other market participants seems to allow a specialist and agile floor traders to earn profits on personal transactions and for selected clients. One can easily overestimate such advantages, however, because ever more of the large orders are negotiated “upstairs,” that is, as fourth-market deals.

Block Sales Institutional investors frequently trade blocks of tens of thousands of shares of stock. Table 3.6 shows that block transactions of over 10,000 shares now account for about half of all trading. The larger block transactions are often too large for specialists to handle, as they do not wish to hold such large blocks of stock in their inventory. For example, the largest block transaction in the first half of 2001 was for 34 million shares of USX-Marathon stock.

TA B L E 3.6 Block transactions on the New York Stock Exchange

block transactions Large transactions in which at least 10,000 shares of stock are bought or sold.

Year

Shares (millions)

% Reported Volume

Average Number of Block Transactions per Day

1965 1970 1975 1980 1985 1990 1995 2000

48 451 779 3,311 14,222 19,682 49,737 135,772

3.1% 15.4 16.6 29.2 51.7 49.6 57.0 51.7

9 68 136 528 2,139 3,333 7,793 21,941

Source: Data from the New York Stock Exchange Fact Book, 2001.

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“Block houses” have evolved to aid in the placement of larger block trades. Block houses are brokerage firms that specialize in matching block buyers and sellers. Once a buyer and a seller have been matched, the block is sent to the exchange floor where specialists execute the trade. If a buyer cannot be found, the block house might purchase all or part of a block sale for its own account. The block house then can resell the shares to the public.

The SuperDot System

program trade Coordinated sale or purchase of a portfolio of stocks.

SuperDot enables exchange members to send orders directly to the specialist’s Display Book over computer lines. The largest market order that can be handled is 30,099 shares. In 2000, SuperDot processed an average of 1.5 million orders per day; the average time to execute market orders submitted through SuperDot was 15 seconds. SuperDot is especially useful to program traders. A program trade is a coordinated purchase or sale of an entire portfolio of stocks. Many trading strategies (such as index arbitrage, a topic we will study in Chapter 16) require that an entire portfolio of stocks be purchased or sold simultaneously in a coordinated program. SuperDot is the tool that enables many trading orders to be sent out at once and executed almost simultaneously. The vast majority of all orders are submitted through SuperDot. However, these tend to be smaller orders and account for only a bit more than half of total share volume.

Settlement Since June 1995, an order executed on the exchange must be settled within three working days. This requirement is often called T ⫹ 3, for trade date plus three days. The purchaser must deliver the cash, and the seller must deliver the stock to the broker, who in turn delivers it to the buyer’s broker. Frequently, a firm’s clients keep their securities in street name, which means the broker holds the shares registered in the firm’s own name on behalf of the client. This convention can speed security transfer. T ⫹ 3 settlement has made such arrangements more important: It can be quite difficult for a seller of a security to complete delivery to the purchaser within the three-day period if the stock is kept in a safe deposit box. Settlement is simplified further by the existence of a clearinghouse. The trades of all exchange members are recorded each day, with members’ transactions netted out, so that each member need transfer or receive only the net number of shares sold or bought that day. An exchange member then settles with the clearinghouse instead of individually with every firm with which it made trades.

3.4

TRADING ON THE OTC MARKET

On the exchanges, all trading occurs through a specialist. On the over-the-counter (OTC) market, however, trades are negotiated directly through dealers who maintain an inventory of selected securities. Dealers sell from their inventories at ask prices and buy for them at bid prices. An investor who wishes to purchase or sell shares engages a broker who tries to locate the dealer offering the best deal on the security. This is in contrast to exchange trading, where all buy or sell orders are negotiated through the specialist, who arranges for the best bids to get the trade. In the OTC market, brokers must search the offers of dealers directly to find the best trading opportunity. In this sense, Nasdaq is a price quotation system, not a trading system. While bid and ask prices can be obtained from the Nasdaq computer network, the actual trade still requires direct negotiation (often over the phone) between the broker and the dealer in the security. However, in the wake of the stock market crash of 1987, Nasdaq instituted a Small Order Execution System (SOES), which is in effect a trading system. Under SOES, market makers

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in a security who post bid or ask prices on the Nasdaq network may be contacted over the network by other traders and are required to trade at the prices they currently quote. Dealers must accept SOES orders at their posted prices up to a limit which may be 1,000 shares, but usually is smaller, depending on factors such as trading volume in the stock. Because the Nasdaq system does not use a specialist, OTC trades do not require a centralized trading floor as do exchange-listed stocks. Dealers can be located anywhere they can communicate effectively with other buyers and sellers. One disadvantage of the decentralized dealer market is that the investing public is vulnerable to trading through, which refers to the possibility that dealers can trade with the public at their quoted bid or asked prices even if other customers have offered to trade at better prices. A dealer who posts $20 bid and $20.15 asked prices for a stock may continue to fill market buy orders at the ask price and fill market sell orders at the bid price—even if there are limit orders by public customers “inside the spread,” for example, limit orders to buy at $20.05 or limit orders to sell at $20.10. This practice harms the investor whose limit order is not filled (is “traded through”) as well as the investor whose market buy or sell order is not filled at the best available price. Trading through on Nasdaq sometimes results from imperfect coordination among dealers. A limit order placed with one broker may not be seen by brokers for other traders because computer systems are not linked and only the broker’s own bid and asked prices are posted on the Nasdaq system. In contrast, trading through is strictly forbidden on the NYSE or Amex, where “price priority” requires that the specialist fill the best-priced order first. Moreover, because all traders in an exchange market must trade through the specialist, the exchange provides true price discovery, meaning that market prices reflect the prices at which all participants at that moment are willing to trade. This is the advantage of a centralized auction market. In October 1994, the Justice Department announced an investigation of the Nasdaq Stock Market regarding possible collusion among market makers to maintain spreads at artificially high levels. In 1996, the Justice Department settled with the Nasdaq dealers. The dealers agreed to refrain from pressuring any other market maker to maintain wide spreads and from refusing to deal with other traders who try to undercut an existing spread. Also in 1996, the SEC settled with the National Association of Securities Dealers (NASD) as well as with the Nasdaq stock market. The settlement called for NASD to take steps to prohibit market makers from colluding on spreads. In addition, the SEC mandated the following three rules on Nasdaq dealers: 1. Publicly display all limit orders. Limit orders from all investors that exceed 100 shares must now be displayed. Therefore, the quoted bid or ask price for a stock must now be the best price quoted by any investor, not simply the best dealer quote. This shrinks the effective spread on the stock. 2. Make best dealer quotes public. Nasdaq dealers must now disclose whether they have posted better quotes in private trading systems or ECNs such as Instinet than they are quoting in the Nasdaq market. 3. Reveal the size of best customer limit orders. For example, if a dealer quotes an offer to buy 1,000 shares of stock at a quoted bid price and a customer places a limit buy order for 500 shares at the same price, the dealer must advertise the bid price as good for 1,500 shares.

Market Structure in Other Countries The structure of security markets varies considerably from one country to another. A full cross-country comparison is far beyond the scope of this text. Therefore, we will instead

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briefly review three of the biggest non-U.S. stock markets: the London, Euronext, and Tokyo exchanges. Figure 3.7 shows the volume of trading in major world markets.

London Until 1997, trading arrangements in London were similar to those on Nasdaq. Competing dealers who wished to make a market in a stock would enter bid and ask prices into the Stock Exchange Automated Quotations (SEAQ) system. As in the U.S., London security firms acted as both dealers and as brokerage firms, that is, both making a market in securities and executing trades for their clients. In 1997, the London Stock Exchange introduced an electronic trading system dubbed SETS (Stock Exchange Electronic Trading Service). This is an electronic clearing system similar to ECNs in which buy and sell orders are submitted via computer networks and any buy and sell orders that can be crossed are executed automatically. Most trading in London equities is now conducted using SETS, particularly for shares in larger firms. However, SEAQ continues to operate and may be more likely to be used for the “upstairs market” in large block transactions or other less liquid transactions.

Euronext Euronext was formed in 2000 by a merger of the Paris, Amsterdam, and Brussels exchanges. Euronext, like most European exchanges, uses an electronic trading system. Its system, called NSC (for Nouveau Système de Cotation, or New Quotation System), has fully automated order routing and execution. In fact, investors can enter their orders directly without contacting their brokers. An order submitted to the system is executed immediately if it can be crossed against an order in the public limit order book; if it cannot be executed, it is entered into the limit order book. Euronext is in the process of establishing cross-trading agreements with several other European exchanges such as Helsinki or Luxembourg. In 2001, it also purchased LIFFE, the London International Financial Futures and Options Exchange.

22,500

Dollar volume of equity trading in major world markets, 2000

20,000

12,500 10,000 7,500 5,000

Toronto

Switzerland

Amsterdam*

Amex

Madrid

Taiwan

Italy

Germany

Tokyo

0

Paris*

2,500 London

The Paris and Amsterdam exchanges have (together with the Brussels exchange) merged to form the Euronext exchange. Although the exchanges have been integrated, trading continues to be conducted in each of these cities.

15,000

New York

*

17,500

Nasdaq

Source: International Federation of Stock Exchanges, www.fibv.com.

Annual trading volume ($ billion)

F I G U R E 3.7

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Tokyo The Tokyo Stock Exchange (TSE) is the largest stock exchange in Japan, accounting for about 80% of total trading. There is no specialist system on the TSE. Instead, a saitori maintains a public limit order book, matches market and limit orders, and is obliged to follow certain actions to slow down price movements when simple matching of orders would result in price changes greater than exchange-prescribed minimums. In their clerical role of matching orders, saitoris are somewhat similar to specialists on the NYSE. However, saitoris do not trade for their own accounts, and therefore they are quite different from either dealers or specialists in the United States. Because the saitori performs an essentially clerical role, there are no market making services or liquidity provided to the market by dealers or specialists. The limit order book is the primary provider of liquidity. In this regard, the TSE bears some resemblance to the fourth market in the United States, in which buyers and sellers trade directly via networks such as Instinet or Posit. On the TSE, however, if order imbalances result in price movements across sequential trades that are considered too extreme by the exchange, the saitori may temporarily halt trading and advertise the imbalance in the hope of attracting additional trading interest to the “weak” side of the market. The TSE organizes stocks into two categories. The First Section consists of about 1,200 of the most actively traded stocks. The Second Section is for about 400 of the less actively traded stocks. Trading in the larger First Section stocks occurs on the floor of the exchange. The remaining securities in the First Section and the Second Section trade electronically.

Globalization of Stock Markets All stock markets have come under increasing pressure in recent years to make international alliances or mergers. Much of this pressure is due to the impact of electronic trading. To a growing extent, traders view stock markets as computer networks that link them to other traders, and there are increasingly fewer limits on the securities around the world that they can trade. Against this background, it becomes more important for exchanges to provide the cheapest and most efficient mechanism by which trades can be executed and cleared. This argues for global alliances that can facilitate the nuts and bolts of cross-border trading and can benefit from economies of scale. Moreover, in the face of competition from electronic networks, established exchanges feel that they eventually need to offer 24-hour global markets. Finally, companies want to be able to go beyond national borders when they wish to raise capital. Merger talks and international strategic alliances blossomed in the late 1990s. We have noted the Euronext merger as well as its alliance with other European exchanges. The Stockholm, Copenhagen, and Oslo exchanges formed a “Nordic Country Alliance” in 1999. In the last few years, Nasdaq has instituted a pilot program to co-list shares on the Stock Exchange of Hong Kong; has launched Nasdaq Europe, Nasdaq Japan, and Nasdaq Canada markets; and has entered negotiations on joint ventures with both the London and Frankfurt exchanges. The NYSE and Tokyo Stock Exchange are exploring the possibility of common listing standards. The NYSE also is exploring the possibility of an alliance with Euronext, in which the shares of commonly listed large multinational firms could be traded on both exchanges. In the wake of the stock market decline of 2001–2002, however, globalization initiatives have faltered. With less investor interest in markets and a dearth of initial public offerings, both Nasdaq Europe and Nasdaq Japan have been less successful, and Nasdaq reportedly was considering pulling out of its Japanese venture. Meanwhile, many markets are increasing their international focus. For example, Nasdaq and the NYSE each list over 400 non-U.S. firms, and foreign firms account for about 10% of trading volume on the NYSE.

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3.5

TRADING COSTS

Part of the cost of trading a security is obvious and explicit. Your broker must be paid a commission. Individuals may choose from two kinds of brokers: full-service or discount brokers. Full-service brokers who provide a variety of services often are referred to as account executives or financial consultants. Besides carrying out the basic services of executing orders, holding securities for safekeeping, extending margin loans, and facilitating short sales, brokers routinely provide information and advice relating to investment alternatives. Full-service brokers usually depend on a research staff that prepares analyses and forecasts of general economic as well as industry and company conditions and often makes specific buy or sell recommendations. Some customers take the ultimate leap of faith and allow a fullservice broker to make buy and sell decisions for them by establishing a discretionary account. In this account, the broker can buy and sell prespecified securities whenever deemed fit. (The broker cannot withdraw any funds, though.) This action requires an unusual degree of trust on the part of the customer, for an unscrupulous broker can “churn” an account, that is, trade securities excessively with the sole purpose of generating commissions. Discount brokers, on the other hand, provide “no-frills” services. They buy and sell securities, hold them for safekeeping, offer margin loans, and facilitate short sales, and that is all. The only information they provide about the securities they handle is price quotations. Discount brokerage services have become increasingly available in recent years. Many banks, thrift institutions, and mutual fund management companies now offer such services to the investing public as part of a general trend toward the creation of one-stop “financial supermarkets.” The commission schedule for trades in common stocks for one prominent discount broker is as follows:

bid–ask spread The difference between a dealer’s bid and asked price.

Transaction Method

Commission

Online trading Automated telephone trading Orders desk (through an associate)

$20 or $0.02 per share, whichever is greater $40 or $0.02 per share, whichever is greater $45 ⫹ $0.03 per share

Notice that there is a minimum charge regardless of trade size and cost as a fraction of the value of traded shares falls as trade size increases. Note also that these prices (and most advertised prices) are for the cheapest market orders. Limit orders are more expensive. In addition to the explicit part of trading costs—the broker’s commission—there is an implicit part—the dealer’s bid–ask spread. Sometimes the broker is a dealer in the security being traded and charges no commission but instead collects the fee entirely in the form of the bid–ask spread. Another implicit cost of trading that some observers would distinguish is the price concession an investor may be forced to make for trading in any quantity that exceeds the quantity the dealer is willing to trade at the posted bid or asked price. One continuing trend is toward online trading either through the Internet or through software that connects a customer directly to a brokerage firm. In 1994, there were no online brokerage accounts; only five years later, there were around 7 million such accounts at “e brokers” such as Ameritrade, Charles Schwab, Fidelity, and E*Trade, and roughly one in five trades was initiated over the Internet. While there is little conceptual difference between placing your order using a phone call versus through a computer link, online brokerage firms can process trades more cheaply since they do not have to pay as many brokers. The average commission for an online trade is now less than $20, compared to perhaps $100–$300 at full-service brokers.

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SEC Prepares for a New World of Stock Trading What should our securities markets look like to serve today’s investor best? Congress addressed this very question a generation ago, when markets were threatened with fragmentation from an increasing number of competing dealers and exchanges. This led the SEC to establish the national market system, which enabled investors to obtain the best quotes on stocks from any of the major exchanges. Today it is the proliferation of electronic exchanges and after-hours trading venues that threatens to fragment the market. But the solution is simple, and would take the intermarket trading system devised by the SEC a quarter century ago to its next logical step. The highest bid and the lowest offer for every stock, no matter where they originate, should be displayed on a screen that would be available to all investors, 24 hours a day, seven days a week. If the SEC mandated this centralization of order flow, competition would significantly enhance investor choice and the quality of the trading environment. Would brokerage houses or even exchanges exist, as we now know them? I believe so, but electronic communication networks would provide the crucial links between buyers and sellers. ECNs would compete by providing far more sophisticated services to the investor than are currently available—not only the entering and execution of standard limit and market orders, but the execution of contingent orders, buys and sells dependent on the levels of other stocks, bonds, commodities, even indexes. The services of brokerage houses would still be in much demand, but their transformation from commission-based to flat-fee or asset-based pricing would be accelerated. Although ECNs will offer almost

costless processing of the basic investor transactions, brokerages would aid investors in placing more sophisticated orders. More importantly, brokers would provide investment advice. Although today’s investor has access to more and more information, this does not mean that he has more understanding of the forces that rule the market or the principles of constructing the best portfolio. As the spread between the best bid and offer price has collapsed, some traditional concerns of regulators are less pressing than they once were. Whether to allow dealers to step in front of customers to buy or sell, or allow brokerages to cross their orders internally at the best price, regardless of other orders at the price on the book, have traditionally been burning regulatory issues. But with spreads so small and getting smaller, these issues are of virtually no consequence to the average investor as long as the integrity of the order flow information is maintained. None of this means that the SEC can disappear once it establishes the central order-flow system. A regulatory authority is needed to monitor the functioning of the new systems and ensure that participants live up to their promises. The rise of technology threatens many established power centers and has prompted some to call for more controls and a go-slow approach. By making clear that the commission’s role is to encourage competition to best serve investors, not to impose or dictate the ultimate structure of the markets, the SEC is poised to take stock trading into the new millennium. SOURCE: Abridged from Jeremy J. Siegel, “The SEC Prepares for a New World of Stock Trading,” The Wall Street Journal, September 27, 1999. Reprinted by permission of Dow Jones & Company, Inc. via Copyright Clearance Center, Inc. © 1999 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

Moreover, these e-brokers are beginning to provide some of the same services offered by full-service brokers such as online company research and, to a lesser extent, the opportunity to participate in IPOs. The traditional full-service brokerage firms have responded to this competitive challenge by introducing online trading for their own customers. Some of these firms are charging by the trade; others charge for such trading through fee-based accounts, in which the customer pays a percentage of assets in the account for the right to trade online. An ongoing controversy between the NYSE and its competitors is the extent to which better execution on the NYSE offsets the generally lower explicit costs of trading in other markets. Execution refers to the size of the effective bid–ask spread and the amount of price impact in a market. The NYSE believes that many investors focus too intently on the costs they can see, despite the fact that quality of execution can be a far more important determinant of total costs. Many NYSE trades are executed at a price inside the quoted spread. This can happen because floor brokers at the specialist’s post can bid above or sell below the specialist’s quote. In this way, two public orders can cross without incurring the specialist’s spread. In contrast, in a dealer market, all trades go through the dealer, and all trades, therefore, are subject to a bid–ask spread. The client never sees the spread as an explicit cost, however. The

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price at which the trade is executed incorporates the dealer’s spread, but this part of the price is never reported to the investor. Similarly, regional markets are disadvantaged in terms of execution because their lower trading volume means that fewer brokers congregate at a specialist’s post, resulting in a lower probability of two public orders crossing. A controversial practice related to the bid–ask spread and the quality of trade execution is “paying for order flow.” This entails paying a broker a rebate for directing the trade to a particular dealer rather than to the NYSE. By bringing the trade to a dealer instead of to the exchange, however, the broker eliminates the possibility that the trade could have been executed without incurring a spread. In fact, the opportunity to profit from the bid–ask spread is the major reason that the dealer is willing to pay the broker for the order flow. Moreover, a broker that is paid for order flow might direct a trade to a dealer that does not even offer the most competitive price. (Indeed, the fact that dealers can afford to pay for order flow suggests that they are able to lay off the trade at better prices elsewhere and, possibly, that the broker also could have found a better price with some additional effort.) Many of the online brokerage firms rely heavily on payment for order flow, since their explicit commissions are so minimal. They typically do not actually execute orders, instead sending an order either to a market maker or to a stock exchange for listed stocks. Such practices raise serious ethical questions, because the broker’s primary obligation is to obtain the best deal for the client. Payment for order flow might be justified if the rebate is passed along to the client either directly or through lower commissions, but it is not clear that such rebates are passed through. Online trading and electronic communications networks have already changed the landscape of the financial markets, and this trend can only be expected to continue. The nearby box considers some of the implications of these new technologies for the future structure of financial markets.

3.6

margin Describes securities purchased with money borrowed in part from a broker. The margin is the net worth of the investor’s account.

BUYING ON MARGIN

When purchasing securities, investors have easy access to a source of debt financing called broker’s call loans. The act of taking advantage of broker’s call loans is called buying on margin. Purchasing stocks on margin means the investor borrows part of the purchase price of the stock from a broker. The margin in the account is the portion of the purchase price contributed by the investor; the remainder is borrowed from the broker. The brokers in turn borrow money from banks at the call money rate to finance these purchases; they then charge their clients that rate (defined in Chapter 2), plus a service charge for the loan. All securities purchased on margin must be maintained with the brokerage firm in street name, for the securities are collateral for the loan. The Board of Governors of the Federal Reserve System limits the extent to which stock purchases can be financed using margin loans. The current initial margin requirement is 50%, meaning that at least 50% of the purchase price must be paid for in cash, with the rest borrowed. The percentage margin is defined as the ratio of the net worth, or the “equity value,” of the account to the market value of the securities. To demonstrate, suppose an investor initially pays $6,000 toward the purchase of $10,000 worth of stock (100 shares at $100 per share), borrowing the remaining $4,000 from a broker. The initial balance sheet looks like this: Assets Value of stock

Liabilities and Owners’ Equity $10,000

Loan from broker Equity

$4,000 $6,000

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The initial percentage margin is Margin ⫽

Equity in account $6,000 ⫽ ⫽ .60, or 60% Value of stock $10,000

If the stock’s price declines to $70 per share, the account balance becomes: Assets Value of stock

Liabilities and Owners’ Equity $7,000

Loan from broker Equity

$4,000 $3,000

The assets in the account fall by the full decrease in the stock value, as does the equity. The percentage margin is now Margin ⫽

Equity in account $3,000 ⫽ ⫽ .43, or 43% Value of stock $7,000

If the stock value were to fall below $4,000, owners’ equity would become negative, meaning the value of the stock is no longer sufficient collateral to cover the loan from the broker. To guard against this possibility, the broker sets a maintenance margin. If the percentage margin falls below the maintenance level, the broker will issue a margin call, which requires the investor to add new cash or securities to the margin account. If the investor does not act, the broker may sell securities from the account to pay off enough of the loan to restore the percent age margin to an acceptable level. Margin calls can occur with little warning. For example, on April 14, 2000, when the Nasdaq index fell by a record 355 points, or 9.7%, the accounts of many investors who had purchased stock with borrowed funds ran afoul of their maintenance margin requirements. Some brokerage houses, concerned about the incredible volatility in the market and the possibility that stock prices would fall below the point that remaining shares could cover the amount of the loan, gave their customers only a few hours or less to meet a margin call rather than the more typical notice of a few days. If customers could not come up with the cash, or were not at a phone to receive the notification of the margin call until later in the day, their accounts were sold out. In other cases, brokerage houses sold out accounts without notifying their customers. The nearby box discussed this episode. An example will show how maintenance margin works. Suppose the maintenance margin is 30%. How far could the stock price fall before the investor would get a margin call? Answering this question requires some algebra. Let P be the price of the stock. The value of the investor’s 100 shares is then 100P, and the equity in the account is 100P ⫺ $4,000. The percentage margin is (100P ⫺ $4,000)/100P. The price at which the percentage margin equals the maintenance margin of .3 is found by solving the equation 100P ⫺ 4,000 ⫽ .3 100P which implies that P ⫽ $57.14. If the price of the stock were to fall below $57.14 per share, the investor would get a margin call. 3. Suppose the maintenance margin is 40%. How far can the stock price fall before the investor gets a margin call?

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Buying on Margin

The Excel spreadsheet model below is built using the text example for IBM. The model makes it easy to analyze the impacts of different margin levels and the volatility of stock prices. It also allows you to compare return on investment for a margin trade with a trade using no borrowed funds. The original price ranges for the text example are highlighted for your reference. You can learn more about this spreadsheet model using the interactive version available on our website at www.mhhe.com/bkm.

A 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

B

Buying on Margin Initial Equity Investment Amount Borrowed Initial Stock Price Shares Purchased Ending Stock Price Cash Dividends During Hold Per. Initial Margin Percentage Maintenance Margin Percentage

C

D

E

Ending St Price 10,000.00 10,000.00 100.00 200 130.00 0.00 50.00% 30.00%

Rate on Margin Loan Holding Period in Months

9.00% 12

Return on Investment Capital Gain on Stock Dividends Interest on Margin Loan Net Income Initial Investment Return on Investment

6000.00 0.00 900.00 5100.00 10000.00 51.00%

Margin Call: Margin Based on Ending Price Price When Margin Call Occurs

61.54% $71.43

Return on Stock without Margin

30.00%

30 40 50 60 70 80 90 100 110 120 130 140 150

F

Return on Investment 51.00% -149.00% -129.00% -109.00% -89.00% -69.00% -49.00% -29.00% -9.00% 11.00% 31.00% 51.00% 71.00% 91.00%

G

H

Ending St Price

Return with No Margin 30.00% -70.00% -60.00% -50.00% -40.00% -30.00% -20.00% -10.00% 0.00% 10.00% 20.00% 30.00% 40.00% 50.00%

30 40 50 60 70 80 90 100 110 120 130 140 150

The 200 shares will be worth $26,000. Paying off $10,900 of principal and interest on the margin loan leaves $15,100 (i.e., $26,000 ⫺ $10,900). The rate of return in this case will be $15,100 ⫺ $10,000 ⫽ 51% $10,000 The investor has parlayed a 30% rise in the stock’s price into a 51% rate of return on the $10,000 investment. Doing so, however, magnifies the downside risk. Suppose that, instead of going up by 30%, the price of IBM stock goes down by 30% to $70 per share. In that case, the 200 shares will be worth $14,000, and the investor is left with $3,100 after paying off the $10,900 of principal and interest on the loan. The result is a disastrous return of 3,100 ⫺ 10,000 10,000

⫽ ⫺69% 85

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Table 3.7 summarizes the possible results of these hypothetical transactions. If there is no change in IBM’s stock price, the investor loses 9%, the cost of the loan.

Concept CHECK

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4. Suppose that in the previous example, the investor borrows only $5,000 at the same interest rate of 9% per year. What will the rate of return be if the price of IBM goes up by 30%? If it goes down by 30%? If it remains unchanged?

3.7

short sale The sale of shares not owned by the investor but borrowed through a broker and later purchased to replace the loan.

TA B L E 3.7 Illustration of buying stock on margin

SHORT SALES

Normally, an investor would first buy a stock and later sell it. With a short sale, the order is reversed. First, you sell and then you buy the shares. In both cases, you begin and end with no shares. A short sale allows investors to profit from a decline in a security’s price. An investor borrows a share of stock from a broker and sells it. Later, the short-seller must purchase a share of the same stock in the market in order to replace the share that was borrowed. This is called covering the short position. Table 3.8 compares stock purchases to short sales. The short-seller anticipates the stock price will fall, so that the share can be purchased later at a lower price than it initially sold for; if so, the short-seller will reap a profit. Short-sellers must not only replace the shares but also pay the lender of the security any dividends paid during the short sale. In practice, the shares loaned out for a short sale are typically provided by the short-seller’s brokerage firm, which holds a wide variety of securities of its other investors in street name. Change in Stock Price

End-of-Year Value of Shares

Repayment of Principal and Interest*

Investor’s Rate of Return

30% increase No change 30% decrease

$26,000 20,000 14,000

$10,900 10,900 10,900

51% ⫺9 ⫺69

*Assuming the investor buys $20,000 worth of stock by borrowing $10,000 as an interest rate of 9% per year.

Purchase of Stock

TA B L E 3.8 Cash flows from purchasing versus short-selling shares of stock

Cash Flow*

Time

Action

0 1

Buy share Receive dividend, sell share

⫺ Initial price Ending price ⫹ Dividend

Profit ⫽ (Ending price ⫹ Dividend) ⫺ Initial price

Short Sale of Stock Time

Action

0 1

Borrow share: sell it Repay dividend and buy share to replace the share originally borrowed

Cash Flow ⫹ Initial price ⫺ (Ending price ⫹ Dividend)

Profit ⫽ Initial price ⫺ (Ending price ⫹ Dividend) *Note: A negative cash flow implies a cash outflow.

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The owner of the shares need not know that the shares have been lent to the short-seller. If the owner wishes to sell the shares, the brokerage firm will simply borrow shares from another investor. Therefore, the short sale may have an indefinite term. However, if the brokerage firm cannot locate new shares to replace the ones sold, the short-seller will need to repay the loan immediately by purchasing shares in the market and turning them over to the brokerage house to close out the loan. Exchange rules permit short sales only when the last recorded change in the stock price is positive. This rule apparently is meant to prevent waves of speculation against the stock. In essence, the votes of “no confidence” in the stock that short sales represent may be entered only after a price increase. Finally, exchange rules require that proceeds from a short sale must be kept on account with the broker. The short-seller cannot invest these funds to generate income, although large or institutional investors typically will receive some income from the proceeds of a short sale being held with the broker. Short-sellers also are required to post margin (cash or collateral) with the broker to cover losses should the stock price rise during the short sale. To illustrate the mechanics of short-selling, suppose you are bearish (pessimistic) on Dot Bomb stock, and its market price is $100 per share. You tell your broker to sell short 1,000 shares. The broker borrows 1,000 shares either from another customer’s account or from another broker. The $100,000 cash proceeds from the short sale are credited to your account. Suppose the broker has a 50% margin requirement on short sales. This means you must have other cash or securities in your account worth at least $50,000 that can serve as margin on the short sale. Let’s say that you have $50,000 in Treasury bills. Your account with the broker after the short sale will then be: Assets Cash T-bills

Liabilities and Owners’ Equity

$100,000 50,000

Short position in Dot Bomb stock (1,000 shares owed) Equity

$100,000 50,000

Your initial percentage margin is the ratio of the equity in the account, $50,000, to the current value of the shares you have borrowed and eventually must return, $100,000: Percentage margin ⫽

Equity $50,000 ⫽ ⫽ .50 Value of stock owed $100,000

Suppose you are right and Dot Bomb falls to $70 per share. You can now close out your position at a profit. To cover the short sale, you buy 1,000 shares to replace the ones you borrowed. Because the shares now sell for $70, the purchase costs only $70,000.5 Because your account was credited for $100,000 when the shares were borrowed and sold, your profit is $30,000: The profit equals the decline in the share price times the number of shares sold short. On the other hand, if the price of Dot Bomb goes up unexpectedly while you are short, you may get a margin call from your broker. Suppose the broker has a maintenance margin of 30% on short sales. This means the equity in your account must be at least 30% of the value of your short position at all times. How much can the price of Dot Bomb stock rise before you get a margin call? 5

Notice that when buying on margin, you borrow a given amount of dollars from your broker, so the amount of the loan is independent of the share price. In contrast, when short-selling you borrow a given number of shares, which must be returned. Therefore, when the price of the shares changes, the value of the loan also changes.

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E XCEL Applications

>

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Short Sale

This Excel spreadsheet model was built using the text example for Dot Bomb. The model allows you to analyze the effects of returns, margin calls, and different levels of initial and maintenance margins. The model also includes a sensitivity analysis for ending stock price and return on investment. The original price for the text example is highlighted for your reference. You can learn more about this spreadsheet model using the interactive version available on our website at www.mhhe.com/bkm. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

A Chapter 3 Short Sale Dot Bomb Short Sale

B

Initial Investment Beginning Share Price Number of Shares Sold Short Ending Share Price Dividends Per Share Initial Margin Percentage Maintenance Margin Percentage

50000.00 100.00 1000.00 70.00 0.00 50.00% 30.00%

Return on Short Sale Gain or Loss on Price Dividends Paid Net Income Return on Investment

30000.00 0.00 30000.00 60.00%

Margin Positions Margin Based on Ending Price

114.29%

Price for Margin Call

C

D

E

F

Ending Return on St Price Investment 60.00% 40 120.00% 50 100.00% 60 80.00% 70 60.00% 80 40.00% 90 20.00% 100 0.00% 110 -20.00% 120 -40.00% 130 -60.00%

115.38

Let P be the price of Dot Bomb stock. Then the value of the shares you must pay back is 1,000P, and the equity in your account is $150,000 ⫺ 1,000P. Your short position margin ratio is equity/value of stock ⫽ (150,000 ⫺ 1,000P)/1,000P. The critical value of P is thus Equity 150,000 ⫺1,000P ⫽ ⫽ .3 Value of shares owed 1,000P which implies that P ⫽ $115.38 per share. If Dot Bomb stock should rise above $115.38 per share, you will get a margin call, and you will either have to put up additional cash or cover your short position by buying shares to replace the ones borrowed.

Concept CHECK

88

>

5. a. Construct the balance sheet if Dot Bomb goes up to $110. b. If the short position maintenance margin in the Dot Bomb example is 40%, how far can the stock price rise before the investor gets a margin call? You can see now why stop-buy orders often accompany short sales. Imagine that you short sell Dot Bomb when it is selling at $100 per share. If the share price falls, you will profit from the short sale. On the other hand, if the share price rises, let’s say to $130, you will lose $30 per share. But suppose that when you initiate the short sale, you also enter a stop-buy order at $120. The stop-buy will be executed if the share price surpasses $120, thereby limiting your losses to $20 per share. (If the stock price drops, the stop-buy will never be executed.) The stop-buy order thus provides protection to the short-seller if the share price moves up.

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3.8

How Securities Are Traded

REGUL ATION OF SECURITIES MARKETS

Trading in securities markets in the United States is regulated by a myriad of laws. The major governing legislation includes the Securities Act of 1933 and the Securities Exchange Act of 1934. The 1933 Act requires full disclosure of relevant information relating to the issue of new securities. This is the act that requires registration of new securities and issuance of a prospectus that details the financial prospects of the firm. SEC approval of a prospectus or financial report is not an endorsement of the security as a good investment. The SEC cares only that the relevant facts are disclosed; investors must make their own evaluation of the security’s value. The 1934 Act established the Securities and Exchange Commission to administer the provisions of the 1933 Act. It also extended the disclosure principle of the 1933 Act by requiring periodic disclosure of relevant financial information by firms with already-issued securities on secondary exchanges. Of course, disclosure is valuable only if the information disclosed faithfully represents the condition of the firm; in the wake of the corporate reporting scandals of 2001 and 2002, confidence in such reports justifiably waned. Under legislation passed in 2002, CEOs and chief financial officers of public firms will be required to swear to the accuracy and completeness of the major financial statements filed by their firms. The 1934 Act also empowers the SEC to register and regulate securities exchanges, OTC trading, brokers, and dealers. While the SEC is the administrative agency responsible for broad oversight of the securities markets, it shares responsibility with other regulatory agencies. The Commodity Futures Trading Commission (CFTC) regulates trading in futures markets, while the Federal Reserve has broad responsibility for the health of the U.S. financial system. In this role, the Fed sets margin requirements on stocks and stock options and regulates bank lending to securities markets participants. The Securities Investor Protection Act of 1970 established the Securities Investor Protection Corporation (SIPC) to protect investors from losses if their brokerage firms fail. Just as the Federal Deposit Insurance Corporation provides depositors with federal protection against bank failure, the SIPC ensures that investors will receive securities held for their account in street name by a failed brokerage firm up to a limit of $500,000 per customer. The SIPC is financed by levying an “insurance premium” on its participating, or member, brokerage firms. It also may borrow money from the SEC if its own funds are insufficient to meet its obligations. In addition to federal regulations, security trading is subject to state laws, known generally as blue sky laws because they are intended to give investors a clearer view of investment prospects. State laws to outlaw fraud in security sales existed before the Securities Act of 1933. Varying state laws were somewhat unified when many states adopted portions of the Uniform Securities Act, which was enacted in 1956.

Self-Regulation and Circuit Breakers Much of the securities industry relies on self-regulation. The SEC delegates to secondary exchanges such as the NYSE much of the responsibility for day-to-day oversight of trading. Similarly, the National Association of Securities Dealers oversees trading of OTC securities. The Institute of Chartered Financial Analysts’ Code of Ethics and Professional Conduct sets out principles that govern the behavior of CFAs. The nearby box presents a brief outline of those principles. The market collapse of October 19, 1987, prompted several suggestions for regulatory change. Among these was a call for “circuit breakers” to slow or stop trading during periods of extreme volatility. Some of the current circuit breakers being used are as follows: • Trading halts. If the Dow Jones Industrial Average falls by 10%, trading will be halted for one hour if the drop occurs before 2:00 P.M. (Eastern Standard Time), for one-half hour if

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AIMR Standards of Professional Conduct STANDARD I: FUNDAMENTAL RESPONSIBILITIES Members shall maintain knowledge of and comply with all applicable laws, rules, and regulations including AIMR’s Code of Ethics and Standards of Professional Conduct.

STANDARD II: RESPONSIBILITIES TO THE PROFESSION • Professional misconduct. Members shall not engage in any professional conduct involving dishonesty, fraud, deceit, or misrepresentation, • Prohibition against plagiarism.

STANDARD III: RESPONSIBILITIES TO THE EMPLOYER • Obligation to inform employer of code and standards. Members shall inform their employer that they are obligated to comply with these Code and Standards. • Disclosure of additional compensation arrangements. Members shall disclose to their employer all benefits that they receive in addition to compensation from that employer.

STANDARD IV: RESPONSIBILITIES TO CLIENTS AND PROSPECTS • Investment process and research reports. Members shall exercise diligence and thoroughness in making investment recommendations . . . distinguish

between facts and opinions in research reports . . . and use reasonable care to maintain objectivity. • Interactions with clients and prospects. Members must place their clients’ interests before their own. • Portfolio investment recommendations. Members shall make a reasonable inquiry into a client’s financial situation, investment experience, and investment objectives prior to making appropriate investment recommendations . . . • Priority of transactions. Transactions for clients and employers shall have priority over transactions for the benefit of a member. • Disclosure of conflicts to clients and prospects. Members shall disclose to their clients and prospects all matters, including ownership of securities or other investments, that reasonably could be expected to impair the member’s ability to make objective recommendations.

STANDARD V: RESPONSIBILITIES TO THE PUBLIC • Prohibition against use of material nonpublic [inside] information. Members who possess material nonpublic information related to the value of a security shall not trade in that security. • Performance presentation. Members shall not make any statements that misrepresent the investment performance that they have accomplished or can reasonably be expected to achieve. SOURCE: Abridged from The Standards of Professional Conduct of the AIMR.

the drop occurs between 2:00 and 2:30, but not at all if the drop occurs after 2:30. If the Dow falls by 20%, trading will be halted for two hours if the drop occurs before 1:00 P.M., for one hour if the drop occurs between 1:00 and 2:00, and for the rest of the day if the drop occurs after 2:00. A 30% drop in the Dow would close the market for the rest of the day, regardless of the time. • Collars. When the Dow moves about two percentage points6 in either direction from the previous day’s close, Rule 80A of the NYSE requires that index arbitrage orders pass a “tick test.” In a falling market, sell orders may be executed only at a plus tick or zero-plus tick, meaning that the trade may be done at a higher price than the last trade (a plus tick) or at the last price if the last recorded change in the stock price is positive (a zero-plus tick). The rule remains in effect for the rest of the day unless the Dow returns to within one percentage point of the previous day’s close. 6

The exact threshold is computed as 2% of the value of the Dow, updated quarterly, rounded to the nearest 10 points.

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The idea behind circuit breakers is that a temporary halt in trading during periods of very high volatility can help mitigate informational problems that might contribute to excessive price swings. For example, even if a trader is unaware of any specific adverse economic news, if he sees the market plummeting, he will suspect that there might be a good reason for the price drop and will become unwilling to buy shares. In fact, he might decide to sell shares to avoid losses. Thus, feedback from price swings to trading behavior can exacerbate market movements. Circuit breakers give participants a chance to assess market fundamentals while prices are temporarily frozen. In this way, they have a chance to decide whether price movements are warranted while the market is closed. Of course, circuit breakers have no bearing on trading in non-U.S. markets. It is quite possible that they simply have induced those who engage in program trading to move their operations into foreign exchanges.

Insider Trading Regulations also prohibit insider trading. It is illegal for anyone to transact in securities to profit from inside information, that is, private information held by officers, directors, or major stockholders that has not yet been divulged to the public. But the definition of insiders can be ambiguous. While it is obvious that the chief financial officer of a firm is an insider, it is less clear whether the firm’s biggest supplier can be considered an insider. Yet a supplier may deduce the firm’s near-term prospects from significant changes in orders. This gives the supplier a unique form of private information, yet the supplier is not technically an insider. These ambiguities plague security analysts, whose job is to uncover as much information as possible concerning the firm’s expected prospects. The distinction between legal private information and illegal inside information can be fuzzy. An important Supreme Court decision in 1997, however, ruled on the side of an expansive view of what constitutes illegal insider trading. The decision upheld the so-called misappropriation theory of insider trading, which holds that traders may not trade on nonpublic information even if they are not company insiders. The SEC requires officers, directors, and major stockholders to report all transactions in their firm’s stock. A compendium of insider trades is published monthly in the SEC’s Official Summary of Securities Transactions and Holdings. The idea is to inform the public of any implicit vote of confidence or no confidence made by insiders. Insiders do exploit their knowledge. Three forms of evidence support this conclusion. First, there have been well-publicized convictions of principals in insider trading schemes. Second, there is considerable evidence of “leakage” of useful information to some traders before any public announcement of that information. For example, share prices of firms announcing dividend increases (which the market interprets as good news concerning the firm’s prospects) commonly increase in value a few days before the public announcement of the increase. Clearly, some investors are acting on the good news before it is released to the public. Similarly, share prices tend to increase a few days before the public announcement of abovetrend earnings growth. Share prices still rise substantially on the day of the public release of good news, however, indicating that insiders, or their associates, have not fully bid up the price of the stock to the level commensurate with the news. A third form of evidence on insider trading has to do with returns earned on trades by insiders. Researchers have examined the SEC’s summary of insider trading to measure the performance of insiders. In one of the best known of these studies, Jaffee (1974) examined the abnormal return of stocks over the months following purchases or sales by insiders. For months in which insider purchasers of a stock exceeded insider sellers of the stock by three or more, the stock had an abnormal return in the following eight months of about 5%. Moreover, when insider sellers exceeded insider buyers, the stock tended to perform poorly.

inside information Nonpublic knowledge about a corporation possessed by corporate officers, major owners, or other individuals with privileged access to information about the firm.

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Restriction of the use of inside information is not universal. Japan has no such prohibition. An argument in favor of free use of inside information is that investors are not misled to believe that the financial market is a level playing field for all. At the same time, free use of inside information means that such information will more quickly be reflected in stock prices. Most Americans believe, however, that it is valuable as well as virtuous to outlaw such advantage, even if less-than-perfect enforcement may leave the door open for some profitable violations of the law.

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SUMMARY

• Firms issue securities to raise the capital necessary to finance their investments. Investment bankers market these securities to the public on the primary market. Investment bankers generally act as underwriters who purchase the securities from the firm and resell them to the public at a markup. Before the securities may be sold to the public, the firm must publish an SEC-approved prospectus that provides information on the firm’s prospects. • Already-issued securities are traded on the secondary market, that is, on organized stock exchanges; the over-the-counter market; and for large trades, through direct negotiation. Only members of exchanges may trade on the exchange. Brokerage firms holding seats on the exchange sell their services to individuals, charging commissions for executing trades on their behalf. The NYSE maintains strict listing requirements. Regional exchanges provide listing opportunities for local firms that do not meet the requirements of the national exchanges. • Trading of common stocks on exchanges occurs through specialists. The specialist acts to maintain an orderly market in the shares of one or more firms. The specialist maintains “books” of limit buy and sell orders and matches trades at mutually acceptable prices. Specialists also accept market orders by selling from or buying for their own inventory of stocks when there is an imbalance of buy and sell orders. • The over-the-counter market is not a formal exchange but a network of brokers and dealers who negotiate sales of securities. The Nasdaq system provides online computer quotes offered by dealers in the stock. When an individual wishes to purchase or sell a share, the broker can search the listing of bid and ask prices, contact the dealer with the best quote, and execute the trade. • Block transactions are a fast-growing segment of the securities market that currently accounts for about half of trading volume. These trades often are too large to be handled readily by specialists and so have given rise to block houses that specialize in identifying potential trading partners for their clients. • Buying on margin means borrowing money from a broker in order to buy more securities than can be purchased with one’s own money alone. By buying securities on a margin, an investor magnifies both the upside potential and the downside risk. If the equity in a margin account falls below the required maintenance level, the investor will get a margin call from the broker. • Short-selling is the practice of selling securities that the seller does not own. The shortseller borrows the securities sold through a broker and may be required to cover the short position at any time on demand. The cash proceeds of a short sale are kept in escrow by the broker, and the broker usually requires that the short-seller deposit additional cash or securities to serve as margin (collateral) for the short sale. • Securities trading is regulated by the Securities and Exchange Commission, other government agencies, and self-regulation of the exchanges. Many of the important

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regulations have to do with full disclosure of relevant information concerning the securities in question. Insider trading rules also prohibit traders from attempting to profit from inside information. • In addition to providing the basic services of executing buy and sell orders, holding securities for safekeeping, making margin loans, and facilitating short sales, full-service brokers offer investors information, advice, and even investment decisions. Discount brokers offer only the basic brokerage services but usually charge less. Total trading costs consist of commissions, the dealer’s bid–ask spread, and price concessions.

inside information, 91 margin, 82 Nasdaq, 67 over-the-counter (OTC) market, 67 primary market, 60 private placement, 61 program trade, 76 prospectus, 60

secondary market, 60 short sale, 86 specialist, 74 stock exchanges, 65 third market, 68 underwriters, 60

1. FBN, Inc., has just sold 100,000 shares in an initial public offering. The underwriter’s explicit fees were $70,000. The offering price for the shares was $50, but immediately upon issue, the share price jumped to $53. a. What is your best guess as to the total cost to FBN of the equity issue? b. Is the entire cost of the underwriting a source of profit to the underwriters? 2. Suppose you short sell 100 shares of IBM, now selling at $120 per share. a. What is your maximum possible loss? b. What happens to the maximum loss if you simultaneously place a stop-buy order at $128? 3. Dée Trader opens a brokerage account, and purchases 300 shares of Internet Dreams at $40 per share. She borrows $4,000 from her broker to help pay for the purchase. The interest rate on the loan is 8%. a. What is the margin in Dée ’s account when she first purchases the stock? b. If the share price falls to $30 per share by the end of the year, what is the remaining margin in her account? If the maintenance margin requirement is 30%, will she receive a margin call? c. What is the rate of return on her investment? 4. Old Economy Traders opened an account to short sell 1,000 shares of Internet Dreams from the previous question. The initial margin requirement was 50%. (The margin account pays no interest.) A year later, the price of Internet Dreams has risen from $40 to $50, and the stock has paid a dividend of $2 per share. a. What is the remaining margin in the account? b. If the maintenance margin requirement is 30%, will Old Economy receive a margin call? c. What is the rate of return on the investment? 5. Do you think it is possible to replace market-making specialists with a fully automated, computerized trade-matching system? 6. Consider the following limit order book of a specialist. The last trade in the stock occurred at a price of $50.

KEY TERMS

PROBLEM SETS

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ask price, 67 bid–ask spread 80 bid price, 67 block transactions, 75 electronic communication networks (ECNs), 68 fourth market, 68 initial public offerings (IPOs), 60

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Limit Buy Orders

7.

8.

9.

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10.

Limit Sell Orders

Price

Shares

Price

Shares

$49.75 49.50 49.25 49.00 48.50

500 800 500 200 600

$50.25 51.50 54.75 58.25

100 100 300 100

a. If a market buy order for 100 shares comes in, at what price will it be filled? b. At what price would the next market buy order be filled? c. If you were the specialist, would you want to increase or decrease your inventory of this stock? You are bullish on Telecom stock. The current market price is $50 per share, and you have $5,000 of your own to invest. You borrow an additional $5,000 from your broker at an interest rate of 8% per year and invest $10,000 in the stock. a. What will be your rate of return if the price of Telecom stock goes up by 10% during the next year? (Ignore the expected dividend.) b. How far does the price of Telecom stock have to fall for you to get a margin call if the maintenance margin is 30%? Assume the price fall happens immediately. You are bearish on Telecom and decide to sell short 100 shares at the current market price of $50 per share. a. How much in cash or securities must you put into your brokerage account if the broker’s initial margin requirement is 50% of the value of the short position? b. How high can the price of the stock go before you get a margin call if the maintenance margin is 30% of the value of the short position? Suppose that Intel currently is selling at $40 per share. You buy 500 shares using $15,000 of your own money and borrowing the remainder of the purchase price from your broker. The rate on the margin loan is 8%. a. What is the percentage increase in the net worth of your brokerage account if the price of Intel immediately changes to: (i) $44; (ii) $40; (iii) $36? What is the relationship between your percentage return and the percentage change in the price of Intel? b. If the maintenance margin is 25%, how low can Intel’s price fall before you get a margin call? c. How would your answer to (b) change if you had financed the initial purchase with only $10,000 of your own money? d. What is the rate of return on your margined position (assuming again that you invest $15,000 of your own money) if Intel is selling after one year at: (i) $44; (ii) $40; (iii) $36? What is the relationship between your percentage return and the percentage change in the price of Intel? Assume that Intel pays no dividends. e. Continue to assume that a year has passed. How low can Intel’s price fall before you get a margin call? Suppose that you sell short 500 shares of Intel, currently selling for $40 per share, and give your broker $15,000 to establish your margin account. a. If you earn no interest on the funds in your margin account, what will be your rate of return after one year if Intel stock is selling at: (i) $44; (ii) $40; (iii) $36? Assume that Intel pays no dividends. b. If the maintenance margin is 25%, how high can Intel’s price rise before you get a margin call?

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c. Redo parts (a) and (b), but now assume that Intel also has paid a year-end dividend of $1 per share. The prices in part (a) should be interpreted as ex-dividend, that is, prices after the dividend has been paid. 11. Call one full-service broker and one discount broker and find out the transaction costs of implementing the following strategies: a. Buying 100 shares of IBM now and selling them six months from now. b. Investing an equivalent amount in six-month at-the-money call options on IBM stock now and selling them six months from now. 12. Here is some price information on Marriott:

Marriott

Bid

Asked

37.25

38.12

You have placed a stop-loss order to sell at $38. What are you telling your broker? Given market prices, will your order be executed? 13. Here is some price information on Fincorp stock. Suppose first that Fincorp trades in a dealer market such as Nasdaq.

15. 16. 17.

Asked

55.25

55.50

a. Suppose you have submitted an order to your broker to buy at market. At what price will your trade be executed? b. Suppose you have submitted an order to sell at market. At what price will your trade be executed? c. Suppose you have submitted a limit order to sell at $55.62. What will happen? d. Suppose you have submitted a limit order to buy at $55.37. What will happen? Now reconsider problem 13 assuming that Fincorp sells in an exchange market like the NYSE. a. Is there any chance for price improvement in the market orders considered in parts (a) and (b)? b. Is there any chance of an immediate trade at $55.37 for the limit buy order in part (d)? What purpose does the SuperDot system serve on the New York Stock Exchange? Who sets the bid and asked price for a stock traded over the counter? Would you expect the spread to be higher on actively or inactively traded stocks? Consider the following data concerning the NYSE: Year

Average Daily Trading Volume (thousands of shares)

Annual High Price of an Exchange Membership

1985 1987 1989 1991 1993 1995 1997

109,169 188,938 165,470 178,917 264,519 346,101 526,925

$ 480,000 1,150,000 675,000 440,000 775,000 1,050,000 1,750,000

a. What do you conclude about the short-run relationship between trading activity and the value of a seat?

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Bid

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b. Based on these data, what do you think has happened to the average commission charged to traders in the last decade? 18. On January 1, you sold short one round lot (that is, 100 shares) of Zenith stock at $14 per share. On March 1, a dividend of $2 per share was paid. On April 1, you covered the short sale by buying the stock at a price of $9 per share. You paid 50 cents per share in commissions for each transaction. What is the value of your account on April 1? The following questions are from past CFA examinations. 19. If you place a stop-loss order to sell 100 shares of stock at $55 when the current price is $62, how much will you receive for each share if the price drops to $50? a. $50. b. $55. c. $54.87. d. Cannot tell from the information given. 20. You wish to sell short 100 shares of XYZ Corporation stock. If the last two transactions were at $34.12 followed by $34.25, you can sell short on the next transaction only at a price of a. 34.12 or higher b. 34.25 or higher c. 34.25 or lower d. 34.12 or lower 21. Specialists on the New York Stock Exchange do all of the following except: a. Act as dealers for their own accounts. b. Execute limit orders. c. Help provide liquidity to the marketplace. d. Act as odd-lot dealers.

WEBMA STER Short Sales Go to the website for Nasdaq at http://www.nasdaq.com. When you enter the site, a dialog box appears that allows you to get quotes for up to 10 stocks. Request quotes for the following companies as identified by their ticker: Noble Drilling (NE), Diamond Offshore (DO), and Haliburton (HAL). Once you have entered the tickers for each company, click the item called info quotes that appears directly below the dialog box for quotes.

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1.

On which market or exchange do these stocks trade? Identify the high and low price based on the current day’s trading.

Below each of the info quotes another dialog box is present. Click the item labeled fundamentals for the first stock. Some basic information on the company will appear along with an additional submenu. One of the items is labeled short interest. When you select that item a 12-month history of short interest will appear. You will need to complete the above process for each of the stocks. 2.

Describe the trend, if any, for short sales over the last year.

3.

What is meant by the term Days to Cover that appears on the history for each company?

4.

Which of the companies has the largest relative number of shares that have been sold short?

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1. Limited time shelf registration was introduced because of its favorable trade-off of saving issue cost against mandated disclosure. Allowing unlimited shelf registration would circumvent “blue sky” laws that ensure proper disclosure as the financial circumstances of the firm change over time.

SOLUTIONS TO

3

2. The advent of negotiated commissions reduced the prices that brokers charged to execute trades on the NYSE. This reduced the profitability of a seat on the exchange, which in turn resulted in the lower seat prices in 1975 that is evident in Table 3.1. Eventually, however, trading volume increased dramatically, which more than made up for lower commissions per trade, and the value of a seat on the exchange rapidly increased after 1975.

> > > >

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AFTER STUDYING THIS CHAPTER YOU SHOULD BE ABLE TO: Cite advantages and disadvantages of investing with an investment company rather than buying securities directly. Contrast open-end mutual funds with closed-end funds and unit investment trusts. Define net asset value and measure the rate of return on a mutual fund. Classify mutual funds according to investment style. Demonstrate the impact of expenses and turnover on mutual fund investment performance.

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Related Websites http://www.brill.com http://www.mfea.com http://www.morningstar.com http://biz.yahoo.com/funds http://moneycentral.msn.com/investor/research/ fundwelcome.asp?Funds=1 http://www.bloomberg.com/money/mutual/index. html The above sites have general and specific information on mutual funds. The Morningstar site has a section dedicated to exchange-traded funds.

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http://www.IndexFunds.com http://www.amex.com http://www.cboe.com/OptiProd/ETFProdSpecs.asp http://www.nyse.com/marketinfo/marketinfo.html These sites give information on exchange-traded funds (ETFs). IndexFunds.com has an excellent screening program that allows you to compare index funds with ETFs in terms of expense ratios.

http://www.vanguard.com http://www100.fidelity.com:80 These sites are examples of specific mutual fund organization websites.

he previous chapter provided an introduction to the mechanics of trading securities and the structure of the markets in which securities trade. Increasingly, however, individual investors are choosing not to trade securities directly for their own accounts. Instead, they direct their funds to investment companies that purchase securities on their behalf. The most important of these financial intermediaries are mutual funds, which are currently owned by about one-half of U.S. households. Other types of investment companies, such as unit investment trusts and closed-end funds, also merit distinctions. We begin the chapter by describing and comparing the various types of investment companies available to investors—unit investment trusts, closed-end investment companies, and open-end investment companies, more commonly known as mutual funds. We devote most of our attention to mutual funds, examining the functions of such funds, their investment styles and policies, and the costs of investing in these funds. Next, we take a first look at the investment performance of these funds. We consider the impact of expenses and turnover on net performance and examine the extent to which performance is consistent from one period to the next. In other words, will the mutual funds that were the best past performers be the best future performers? Finally, we discuss sources of information on mutual funds and consider in detail the information provided in the most comprehensive guide, Morningstar’s Mutual Fund Sourcebook.

T

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4.1

INVESTMENT COMPANIES

Investment companies are financial intermediaries that collect funds from individual investors and invest those funds in a potentially wide range of securities or other assets. Pooling of assets is the key idea behind investment companies. Each investor has a claim to the portfolio established by the investment company in proportion to the amount invested. These companies thus provide a mechanism for small investors to “team up” to obtain the benefits of large-scale investing. Investment companies perform several important functions for their investors:

investment companies Financial intermediaries that invest the funds of individual investors in securities or other assets.

1. Record keeping and administration. Investment companies issue periodic status reports, keeping track of capital gains distributions, dividends, investments, and redemptions, and they may reinvest dividend and interest income for shareholders. 2. Diversification and divisibility. By pooling their money, investment companies enable investors to hold fractional shares of many different securities. They can act as large investors even if any individual shareholder cannot. 3. Professional management. Most, but not all, investment companies have full-time staffs of security analysts and portfolio managers who attempt to achieve superior investment results for their investors. 4. Lower transaction costs. Because they trade large blocks of securities, investment companies can achieve substantial savings on brokerage fees and commissions. While all investment companies pool the assets of individual investors, they also need to divide claims to those assets among those investors. Investors buy shares in investment companies, and ownership is proportional to the number of shares purchased. The value of each share is called the net asset value, or NAV. Net asset value equals assets minus liabilities expressed on a per-share basis:

net asset value (NAV) Assets minus liabilities expressed on a per-share basis.

Net asset value ⫽

Market value of assets minus liabilities Shares outstanding

Consider a mutual fund that manages a portfolio of securities worth $120 million. Suppose the fund owes $4 million to its investment advisers and owes another $1 million for rent, wages due, and miscellaneous expenses. The fund has 5 million shareholders. Then Net asset value ⫽

Concept CHECK

>

$120 million ⫺ $5 million ⫽ $23 per share 5 million shares

1. Consider these data from the December 2000 balance sheet of the Growth Index mutual fund sponsored by the Vanguard Group. (All values are in millions.) What was the net asset value of the portfolio? Assets: Liabilities: Shares:

4.2

$14,754 $ 1,934 419.4

TYPES OF INVESTMENT COMPANIES

In the United States, investment companies are classified by the Investment Company Act of 1940 as either unit investment trusts or managed investment companies. The portfolios of unit investment trusts are essentially fixed and thus are called “unmanaged.” In contrast, managed

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companies are so named because securities in their investment portfolios continually are bought and sold: The portfolios are managed. Managed companies are further classified as either closed-end or open-end. Open-end companies are what we commonly call mutual funds.

Unit Investment Trusts Unit investment trusts are pools of money invested in a portfolio that is fixed for the life of the fund. To form a unit investment trust, a sponsor, typically a brokerage firm, buys a portfolio of securities which are deposited into a trust. It then sells to the public shares, or “units,” in the trust, called redeemable trust certificates. All income and payments of principal from the portfolio are paid out by the fund’s trustees (a bank or trust company) to the shareholders. There is little active management of a unit investment trust because once established, the portfolio composition is fixed; hence these trusts are referred to as unmanaged. Trusts tend to invest in relatively uniform types of assets; for example, one trust may invest in municipal bonds, another in corporate bonds. The uniformity of the portfolio is consistent with the lack of active management. The trusts provide investors a vehicle to purchase a pool of one particular type of asset, which can be included in an overall portfolio as desired. The lack of active management of the portfolio implies that management fees can be lower than those of managed funds. Sponsors of unit investment trusts earn their profit by selling shares in the trust at a premium to the cost of acquiring the underlying assets. For example, a trust that has purchased $5 million of assets may sell 5,000 shares to the public at a price of $1,030 per share, which (assuming the trust has no liabilities) represents a 3% premium over the net asset value of the securities held by the trust. The 3% premium is the trustee’s fee for establishing the trust. Investors who wish to liquidate their holdings of a unit investment trust may sell the shares back to the trustee for net asset value. The trustees can either sell enough securities from the asset portfolio to obtain the cash necessary to pay the investor, or they may instead sell the shares to a new investor (again at a slight premium to net asset value).

unit investment trusts Money pooled from many investors that is invested in a portfolio fixed for the life of the fund.

Managed Investment Companies There are two types of managed companies: closed-end and open-end. In both cases, the fund’s board of directors, which is elected by shareholders, hires a management company to manage the portfolio for an annual fee that typically ranges from .2% to 1.5% of assets. In many cases the management company is the firm that organized the fund. For example, Fidelity Management and Research Corporation sponsors many Fidelity mutual funds and is responsible for managing the portfolios. It assesses a management fee on each Fidelity fund. In other cases, a mutual fund will hire an outside portfolio manager. For example, Vanguard has hired Wellington Management as the investment adviser for its Wellington Fund. Most management companies have contracts to manage several funds. Open-end funds stand ready to redeem or issue shares at their net asset value (although both purchases and redemptions may involve sales charges). When investors in open-end funds wish to “cash out” their shares, they sell them back to the fund at NAV. In contrast, closed-end funds do not redeem or issue shares. Investors in closed-end funds who wish to cash out must sell their shares to other investors. Shares of closed-end funds are traded on organized exchanges and can be purchased through brokers just like other common stock; their prices therefore can differ from NAV. Figure 4.1 is a listing of closed-end funds from The Wall Street Journal. The first column after the name of the fund indicates the exchange on which the shares trade (A: Amex; C: Chicago; N: NYSE; O: Nasdaq; T: Toronto; z: does not trade on an exchange). The next four

open-end funds A fund that issues or redeems its shares at net asset value.

closed-end funds A fund whose shares are traded at prices that can differ from net asset value. Shares may not be redeemed at NAV.

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F I G U R E 4.1 Closed-end mutual funds Source: The Wall Street Journal, November 19, 2001. Reprinted by permission of Dow Jones & Company, Inc., via Copyright Clearance Center, Inc. © 2001 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

columns give the fund’s most recent net asset value, the closing share price, the change in the closing price from the previous day, and trading volume in round lots of 100 shares. The premium or discount is the percentage difference between price and NAV: (Price ⫺ NAV)/NAV. Notice that there are more funds selling at discounts to NAV (indicated by negative differences) than premiums. Finally, the annual dividend and the 52-week return based on the percentage change in share price plus dividend income is presented in the last two columns. The common divergence of price from net asset value, often by wide margins, is a puzzle that has yet to be fully explained. To see why this is a puzzle, consider a closed-end fund that is selling at a discount from net asset value. If the fund were to sell all the assets in the portfolio, it would realize proceeds equal to net asset value. The difference between the market price of the fund and the fund’s NAV would represent the per-share increase in the wealth of the fund’s investors. Despite this apparent profit opportunity, sizable discounts seem to persist for long periods of time. Interestingly, while many closed-end funds sell at a discount from net asset value, the prices of these funds when originally issued are often above NAV. This is a further puzzle, as it is hard to explain why investors would purchase these newly issued funds at a premium to NAV when the shares tend to fall to a discount shortly after issue. Many investors consider closed-end funds selling at a discount to NAV to be a bargain. Even if the market price never rises to the level of NAV, the dividend yield on an investment in the fund at this price would exceed the dividend yield on the same securities held outside the fund. To see this, imagine a fund with an NAV of $10 per share holding a portfolio that pays an annual dividend of $1 per share; that is, the dividend yield to investors that hold this portfolio directly is 10%. Now suppose that the market price of a share of this closed-end fund is $9. If management pays out dividends received from the shares as they come in, then the dividend yield to those that hold the same portfolio through the closed-end fund will be $1/$9, or 11.1%. Variations on closed-end funds are interval closed-end funds and discretionary closed-end funds. Interval closed-end funds may purchase from 5 to 25% of outstanding shares from

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investors at intervals of 3, 6, or 12 months. Discretionary closed-end funds may purchase any or all of outstanding shares from investors, but no more frequently than once every two years. The repurchase of shares for either of these funds takes place at net asset value plus a repurchase fee that may not exceed 2%. In contrast to closed-end funds, the price of open-end funds cannot fall below NAV, because these funds stand ready to redeem shares at NAV. The offering price will exceed NAV, however, if the fund carries a load. A load is, in effect, a sales charge, which is paid to the seller. Load funds are sold by securities brokers and directly by mutual fund groups. Unlike closed-end funds, open-end mutual funds do not trade on organized exchanges. Instead, investors simply buy shares from and liquidate through the investment company at net asset value. Thus, the number of outstanding shares of these funds changes daily.

103

load A sales commission charged on a mutual fund.

Other Investment Organizations There are intermediaries not formally organized or regulated as investment companies that nevertheless serve functions similar to investment companies. Among the more important are commingled funds, real estate investment trusts, and hedge funds.

Commingled funds Commingled funds are partnerships of investors that pool their funds. The management firm that organizes the partnership, for example, a bank or insurance company, manages the funds for a fee. Typical partners in a commingled fund might be trust or retirement accounts which have portfolios that are much larger than those of most individual investors but are still too small to warrant managing on a separate basis. Commingled funds are similar in form to open-end mutual funds. Instead of shares, though, the fund offers units, which are bought and sold at net asset value. A bank or insurance company may offer an array of different commingled funds from which trust or retirement accounts can choose. Examples are a money market fund, a bond fund, and a common stock fund.

Real Estate Investment Trusts (REITs) A REIT is similar to a closed-end fund. REITs invest in real estate or loans secured by real estate. Besides issuing shares, they raise capital by borrowing from banks and issuing bonds or mortgages. Most of them are highly leveraged, with a typical debt ratio of 70%. There are two principal kinds of REITs. Equity trusts invest in real estate directly, whereas mortgage trusts invest primarily in mortgage and construction loans. REITs generally are established by banks, insurance companies, or mortgage companies, which then serve as investment managers to earn a fee. REITs are exempt from taxes as long as at least 95% of their taxable income is distributed to shareholders. For shareholders, however, the dividends are taxable as personal income. Hedge funds Like mutual funds, hedge funds are vehicles that allow private investors to pool assets to be invested by a fund manager. However, hedge funds are not registered as mutual funds and are not subject to SEC regulation. They typically are open only to wealthy or institutional investors. As hedge funds are only lightly regulated, their managers can pursue investment strategies that are not open to mutual fund managers, for example, heavy use of derivatives, short sales, and leverage. Hedge funds typically attempt to exploit temporary misalignments in security valuations. For example, if the yield on mortgage-backed securities seems abnormally high compared to that on Treasury bonds, the hedge fund would buy mortgage-backed and short sell Treasury securities. Notice that the fund is not betting on broad movement in the entire bond market; it

hedge fund A private investment pool, open to wealthy or institutional investors, that is exempt from SEC regulation and can therefore pursue more speculative policies than mutual funds.

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buys one type of bond and sells another. By taking a long mortgage/short Treasury position, the fund “hedges” its interest rate exposure, while making a bet on the relative valuation across the two sectors. The idea is that when yield spreads converge back to their “normal” relationship, the fund will profit from the realignment regardless of the general trend in the level of interest rates. In this respect, it strives to be “market neutral,” which gives rise to the term “hedge fund.” Of course even if the fund’s position is market neutral, this does not mean that it is low risk. The fund still is speculating on valuation differences across the two sectors, often taking a very large position, and this decision can turn out to be right or wrong. Because the funds often operate with considerable leverage, returns can be quite volatile. One of the major financial stories of 1998 was the collapse of Long-Term Capital Management (LTCM), probably the best-known hedge fund at the time. Among its many investments were several “convergence bets,” such as the mortgage-backed/Treasury spread we have described. When Russia defaulted on some of its debts in August 1998, risk and liquidity premiums increased, so that instead of converging, the yield spread between safe Treasuries and almost all other bonds widened. LTCM lost billions of dollars in August and September of 1998; the fear was that given its extreme leverage, continued losses might more than wipe out the firm’s capital and force it to default on its positions. Eventually, several Wall Street firms contributed a total of about $3.5 billion to bail out the fund, in return receiving a 90% ownership stake in the firm.

4.3

MUTUAL FUNDS

Mutual fund is the common name for an open-end investment company. This is the dominant investment company today, accounting for roughly 90% of investment company assets. Assets under management in the mutual fund industry reached $7 trillion by year-end 2001.

Investment Policies Each mutual fund has a specified investment policy, which is described in the fund’s prospectus. For example, money market mutual funds hold the short-term, low-risk instruments of the money market (see Chapter 2 for a review of these securities), while bond funds hold fixed-income securities. Some funds have even more narrowly defined mandates. For example, some bond funds will hold primarily Treasury bonds, others primarily mortgage-backed securities. Management companies manage a family, or “complex,” of mutual funds. They organize an entire collection of funds and then collect a management fee for operating them. By managing a collection of funds under one umbrella, these companies make it easy for investors to allocate assets across market sectors and to switch assets across funds while still benefiting from centralized record keeping. Some of the most well-known management companies are Fidelity, Vanguard, Putnam, and Dreyfus. Each offers an array of open-end mutual funds with different investment policies. There were over 8,000 mutual funds at the end of 2000, which were offered by fewer than 500 fund complexes. Some of the more important fund types, classified by investment policy, are discussed next.

Money market funds These funds invest in money market securities. They usually offer check-writing features, and net asset value is fixed at $1 per share, so that there are no tax implications such as capital gains or losses associated with redemption of shares.

Equity funds Equity funds invest primarily in stock, although they may, at the portfolio manager’s discretion, also hold fixed-income or other types of securities. Funds commonly

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will hold about 5% of total assets in money market securities to provide the liquidity necessary to meet potential redemption of shares. It is traditional to classify stock funds according to their emphasis on capital appreciation versus current income. Thus income funds tend to hold shares of firms with high dividend yields that provide high current income. Growth funds are willing to forgo current income, focusing instead on prospects for capital gains. While the classification of these funds is couched in terms of income versus capital gains, it is worth noting that in practice the more relevant distinction concerns the level of risk these funds assume. Growth stocks—and therefore growth funds—are typically riskier and respond far more dramatically to changes in economic conditions than do income funds.

Bond funds As the name suggests, these funds specialize in the fixed-income sector. Within that sector, however, there is considerable room for specialization. For example, various funds will concentrate on corporate bonds, Treasury bonds, mortgage-backed securities, or municipal (tax-free) bonds. Indeed, some of the municipal bond funds will invest only in bonds of a particular state (or even city!) in order to satisfy the investment desires of residents of that state who wish to avoid local as well as federal taxes on the interest paid on the bonds. Many funds also will specialize by the maturity of the securities, ranging from short-term to intermediate to long-term, or by the credit risk of the issuer, ranging from very safe to highyield or “junk” bonds. Balanced and income funds Some funds are designed to be candidates for an individual’s entire investment portfolio. Therefore, they hold both equities and fixed-income securities in relatively stable proportions. According to Wiesenberger, such funds are classified as income or balanced funds. Income funds strive to maintain safety of principal consistent with “as liberal a current income from investments as possible,” while balanced funds “minimize investment risks so far as this is possible without unduly sacrificing possibilities for long-term growth and current income.”

Asset allocation funds These funds are similar to balanced funds in that they hold both stocks and bonds. However, asset allocation funds may dramatically vary the proportions allocated to each market in accord with the portfolio manager’s forecast of the relative performance of each sector. Hence, these funds are engaged in market timing and are not designed to be low-risk investment vehicles.

Index funds An index fund tries to match the performance of a broad market index. The fund buys shares in securities included in a particular index in proportion to the security’s representation in that index. For example, the Vanguard 500 Index Fund is a mutual fund that replicates the composition of the Standard & Poor’s 500 stock price index. Because the S&P 500 is a value-weighted index, the fund buys shares in each S&P 500 company in proportion to the market value of that company’s outstanding equity. Investment in an index fund is a low-cost way for small investors to pursue a passive investment strategy—that is, to invest without engaging in security analysis. Of course, index funds can be tied to nonequity indexes as well. For example, Vanguard offers a bond index fund and a real estate index fund.

Specialized sector funds Some funds concentrate on a particular industry. For example, Fidelity markets dozens of “select funds,” each of which invests in specific industry such as biotechnology, utilities, precious metals, or telecommunications. Other funds specialize in securities of particular countries. Table 4.1 breaks down the number of mutual funds by investment orientation as of the end of 2001. Figure 4.2 is part of the listings for mutual funds from The Wall Street Journal.

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Assets ($ billion)

% of Total

$ 576.2 1,047.5 1,066.6 125.4 415.1 13.7 173.6

8.3% 15.0 15.3 1.8 6.0 0.2 2.5

Total equity funds Bond Funds Corporate, investment grade Corporate, high yield Government & agency Mortgage-backed Global bond funds Strategic income Municipal single state Municipal general

$3,418.1

49.0%

$ 161.0 94.3 90.9 73.4 19.0 191.6 141.0 154.0

2.3% 1.4 1.3 1.1 0.3 2.7 2.0 2.2

Total bond funds Mixed (hybrid) Asset Classes Balanced Asset allocation & flexible

$ 925.2

13.3%

$ 231.1 115.3

3.3% 1.7

$ 346.3

5.0%

$2,012.9 272.4

28.9% 3.9

$2,285.3

32.8%

$6,974.9

100.0%

TA B L E 4.1 Classification of mutual funds, December 2001

Common Stock Aggressive growth Growth Growth & income Equity income International Emerging markets Sector funds

Total hybrid funds Money Market Taxable Tax-free Total money market funds Total Note: Column sums subject to rounding error. Source: Mutual Fund Fact Book, Investment Company Institute, 2002.

Notice that the funds are organized by the fund family. For example, funds sponsored by the Vanguard Group comprise most of the figure. The first two columns after the name of each fund present the net asset value of the fund and the change in NAV from the previous day. The last column is the year-to-date return on the fund. Often the fund name describes its investment policy. For example, Vanguard’s GNMA fund invests in mortgage-backed securities, the municipal intermediate fund (MuInt) invests in intermediate-term municipal bonds, and the high-yield corporate bond fund (HYCor) invests in large part in speculative grade, or “junk,” bonds with high yields. You can see that Vanguard offers about 20 index funds, including portfolios indexed to the bond market (TotBd), the Wilshire 5000 Index (TotSt), the Russell 2000 Index of small firms (SmCap), as well as European- and Pacific Basin-indexed portfolios (Europe and Pacific). However, names of common stock funds frequently reflect little or nothing about their investment policies. Examples are Vanguard’s Windsor and Wellington funds.

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F I G U R E 4.2 Listing of mutual fund quotations Source: The Wall Street Journal, November 15, 2001. Reprinted by permission of Dow Jones & Company, Inc., via Copyright Clearance Center, Inc. © 2001 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

How Funds Are Sold Most mutual funds have an underwriter that has exclusive rights to distribute shares to investors. Mutual funds are generally marketed to the public either directly by the fund underwriter or indirectly through brokers acting on behalf of the underwriter. Direct-marketed funds are sold through the mail, various offices of the fund, over the phone, and increasingly, over the Internet. Investors contact the fund directly to purchase shares. For example, if you look at the financial pages of your local newspaper, you will see several advertisements for funds, along with toll-free phone numbers that you can call to receive a fund’s prospectus and an application to open an account with the fund. A bit less than half of fund sales today are distributed through a sales force. Brokers or financial advisers receive a commission for selling shares to investors. (Ultimately, the commission is paid by the investor. More on this shortly.) In some cases, funds use a “captive” sales force that sells only shares in funds of the mutual fund group they represent. The trend today, however, is toward “financial supermarkets” that can sell shares in funds of many complexes. This approach was made popular by the OneSource program of Charles Schwab & Co. Schwab allows customers of the OneSource program to buy funds from many different fund groups. Instead of charging customers a sales commission, Schwab splits management fees with the mutual fund company. The supermarket approach has proven to be popular. For example, Fidelity now sells non-Fidelity mutual funds through its FundsNetwork even though many of those funds compete with Fidelity products. Like Schwab, Fidelity shares a portion of the management fee from the non-Fidelity funds it sells.

4.4

COSTS OF INVESTING IN MUTUAL FUNDS

Fee Structure An individual investor choosing a mutual fund should consider not only the fund’s stated investment policy and past performance, but also its management fees and other expenses.

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Comparative data on virtually all important aspects of mutual funds are available in the annual reports prepared by Wiesenberger Investment Companies Services or in Morningstar’s Mutual Fund Sourcebook, which can be found in many academic and public libraries. You should be aware of four general classes of fees.

Front-end load A front-end load is a commission or sales charge paid when you purchase the shares. These charges, which are used primarily to pay the brokers who sell the funds, may not exceed 8.5%, but in practice they are rarely higher than 6%. Low-load funds have loads that range up to 3% of invested funds. No-load funds have no front-end sales charges. Loads effectively reduce the amount of money invested. For example, each $1,000 paid for a fund with an 8.5% load results in a sales charge of $85 and fund investment of only $915. You need cumulative returns of 9.3% of your net investment (85/915 ⫽ .093) just to break even.

Back-end load A back-end load is a redemption, or “exit,” fee incurred when you sell your shares. Typically, funds that impose back-end loads start them at 5% or 6% and reduce them by one percentage point for every year the funds are left invested. Thus, an exit fee that starts at 6% would fall to 4% by the start of your third year. These charges are known more formally as “contingent deferred sales charges.”

Operating expenses

Operating expenses are the costs incurred by the mutual fund in operating the portfolio, including administrative expenses and advisory fees paid to the investment manager. These expenses, usually expressed as a percentage of total assets under management, may range from 0.2% to 2%. Shareholders do not receive an explicit bill for these operating expenses; however, the expenses periodically are deducted from the assets of the fund. Shareholders pay for these expenses through the reduced value of the portfolio.

12b-1 charges The Securities and Exchange Commission allows the managers of so12b-1 fees Annual fees charged by a mutual fund to pay for marketing and distribution costs.

called 12b-1 funds to use fund assets to pay for distribution costs such as advertising, promotional literature including annual reports and prospectuses, and, most important, commissions paid to brokers who sell the fund to investors. These 12b-1 fees are named after the SEC rule that permits use of these plans. Funds may use 12b-1 charges instead of, or in addition to, front-end loads to generate the fees with which to pay brokers. As with operating expenses, investors are not explicitly billed for 12b-1 charges. Instead, the fees are deducted from the assets of the fund. Therefore, 12b-1 fees (if any) must be added to operating expenses to obtain the true annual expense ratio of the fund. The SEC now requires that all funds include in the prospectus a consolidated expense table that summarizes all relevant fees. The 12b-1 fees are limited to 1% of a fund’s average net assets per year.1 A relatively recent innovation in the fee structure of mutual funds is the creation of different “classes”; they represent ownership in the same portfolio of securities but impose different combinations of fees. For example, Class A shares typically are sold with front-end loads of between 4% to 5%. Class B shares impose 12b-1 charges and back-end loads. Because Class B shares pay 12b-1 fees while Class A shares do not, the reported rate of return on the B

1

The maximum 12b-1 charge for the sale of the fund is .75%. However, an additional service fee of .25% of the fund’s assets also is allowed for personal service and/or maintenance of shareholder accounts.

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shares will be less than that of the A shares despite the fact that they represent holdings in the same portfolio. (The reported return on the shares does not reflect the impact of loads paid by the investor.) Class C shares do not impose back-end redemption fees, but they impose 12b-1 fees higher than those in Class B, often as high as 1% annually. Other classes and combinations of fees are also marketed by mutual fund companies. For example, Merrill Lynch has introduced Class D shares of some of its funds, which include front-end loads and 12b-1 charges of .25%. Each investor must choose the best combination of fees. Obviously, pure no-load no-fee funds distributed directly by the mutual fund group are the cheapest alternative, and these will often make the most sense for knowledgeable investors. However, many investors are willing to pay for financial advice, and the commissions paid to advisers who sell these funds are the most common form of payment. Alternatively, investors may choose to hire a fee-only financial manager who charges directly for services and does not accept commissions. These advisers can help investors select portfolios of low- or no-load funds (as well as provide other financial advice). Independent financial planners have become increasingly important distribution channels for funds in recent years. If you do buy a fund through a broker, the choice between paying a load and paying 12b-1 fees will depend primarily on your expected time horizon. Loads are paid only once for each purchase, whereas 12b-1 fees are paid annually. Thus, if you plan to hold your fund for a long time, a one-time load may be preferable to recurring 12b-1 charges. You can identify funds with various charges by the following letters placed after the fund name in the listing of mutual funds in the financial pages: r denotes redemption or exit fees; p denotes 12b-1 fees; and t denotes both redemption and 12b-1 fees. The listings do not allow you to identify funds that involve front-end loads, however; while NAV for each fund is presented, the offering price at which the fund can be purchased, which may include a load, is not.

Fees and Mutual Fund Returns The rate of return on an investment in a mutual fund is measured as the increase or decrease in net asset value plus income distributions such as dividends or distributions of capital gains expressed as a fraction of net asset value at the beginning of the investment period. If we denote the net asset value at the start and end of the period as NAV0 and NAV1, respectively, then Rate of return ⫽

NAV1 ⫺ NAV0 ⫹ Income and capital gain distributions NAV0

For example, if a fund has an initial NAV of $20 at the start of the month, makes income distributions of $.15 and capital gain distributions of $.05, and ends the month with NAV of $20.10, the monthly rate of return is computed as Rate of return ⫽

$20.10 ⫺ $20.00 ⫹ $.15 ⫹ $.05 ⫽ .015, or 1.5% $20.00

Notice that this measure of the rate of return ignores any commissions such as front-end loads paid to purchase the fund. On the other hand, the rate of return is affected by the fund’s expenses and 12b-1 fees. This is because such charges are periodically deducted from the portfolio, which reduces net asset value. Thus the rate of return on the fund equals the gross return on the underlying portfolio minus the total expense ratio.

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Cumulative Proceeds (all dividends reinvested)

TA B L E 4.2 Impact of costs on investment performance

Initial investment* 5 years 10 years 15 years 20 years

Fund A

Fund B

Fund C

$10,000 17,234 29,699 51,183 88,206

$10,000 16,474 27,141 44,713 73,662

$ 9,200 15,502 26,123 44,018 74,173

*

After front-end load, if any.

Notes: 1. Fund A is no-load with .5% expense ratio. 2. Fund B is no-load with 1.5% expense ratio. 3. Fund C has an 8% load on purchases and a 1% expense ratio. 4. Gross return on all funds is 12% per year before expenses.

4.1 EXAMPLE Expenses and Rates of Return

soft dollars The value of research services brokerage houses provide “free of charge” in exchange for the investment manager’s business.

To see how expenses can affect rate of return, consider a fund with $100 million in assets at the start of the year and with 10 million shares outstanding. The fund invests in a portfolio of stocks that provides no income but increases in value by 10%. The expense ratio, including 12b-1 fees, is 1%. What is the rate of return for an investor in the fund? The initial NAV equals $100 million/10 million shares ⫽ $10 per share. In the absence of expenses, fund assets would grow to $110 million and NAV would grow to $11 per share, for a 10% rate of return. However, the expense ratio of the fund is 1%. Therefore, $1 million will be deducted from the fund to pay these fees, leaving the portfolio worth only $109 million, and NAV equal to $10.90. The rate of return on the fund is only 9%, which equals the gross return on the underlying portfolio minus the total expense ratio.

Fees can have a big effect on performance. Table 4.2 considers an investor who starts with $10,000 and can choose between three funds that all earn an annual 12% return on investment before fees but have different fee structures. The table shows the cumulative amount in each fund after several investment horizons. Fund A has total operating expenses of .5%, no load, and no 12b-1 charges. This might represent a low-cost producer like Vanguard. Fund B has no load but has 1% management expenses and .5% in 12b-1 fees. This level of charges is fairly typical of actively managed equity funds. Finally, Fund C has 1% in management expenses, no 12b-1 charges, but assesses an 8% front-end load on purchases. Note the substantial return advantage of low-cost Fund A. Moreover, that differential is greater for longer investment horizons. Although expenses can have a big impact on net investment performance, it is sometimes difficult for the investor in a mutual fund to measure true expenses accurately. This is because of the common practice of paying for some expenses in soft dollars. A portfolio manager earns soft-dollar credits with a stockbroker by directing the fund’s trades to that broker. Based on those credits, the broker will pay for some of the mutual fund’s expenses, such as databases, computer hardware, or stock-quotation systems. The soft-dollar arrangement means that the stockbroker effectively returns part of the trading commission to the fund. The advantage to the mutual fund is that purchases made with soft dollars are not included in the fund’s expenses, so the fund can advertise an unrealistically low expense ratio to the public.

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Although the fund may have paid the broker needlessly high commissions to obtain the softdollar “rebate,” trading costs are not included in the fund’s expenses. The impact of the higher trading commission shows up instead in net investment performance. Soft-dollar arrangements make it difficult for investors to compare fund expenses, and periodically these arrangements come under attack. 2. The Equity Fund sells Class A shares with a front-end load of 4% and Class B shares with 12b-1 fees of .5% annually as well as back-end load fees that start at 5% and fall by 1% for each full year the investor holds the portfolio (until the fifth year). Assume the rate of return on the fund portfolio net of operating expenses is 10% annually. What will be the value of a $10,000 investment in Class A and Class B shares if the shares are sold after (a) 1 year, (b) 4 years, (c) 10 years? Which fee structure provides higher net proceeds at the end of each investment horizon?

4.5

Concept CHECK

TAXATION OF MUTUAL FUND INCOME

Investment returns of mutual funds are granted “pass-through status” under the U.S. tax code, meaning that taxes are paid only by the investor in the mutual fund, not by the fund itself. The income is treated as passed through to the investor as long as the fund meets several requirements, most notably that at least 90% of all income is distributed to shareholders. In addition, the fund must receive less than 30% of its gross income from the sale of securities held for less than three months, and the fund must satisfy some diversification criteria. Actually, the earnings pass-through requirements can be even more stringent than 90%, since to avoid a separate excise tax, a fund must distribute at least 98% of income in the calendar year that it is earned. A fund’s short-term capital gains, long-term capital gains, and dividends are passed through to investors as though the investor earned the income directly. The investor will pay taxes at the appropriate rate depending upon the type of income as well as the investor’s own tax bracket.2 The pass through of investment income has one important disadvantage for individual investors. If you manage your own portfolio, you decide when to realize capital gains and losses on any security; therefore, you can time those realizations to efficiently manage your tax liabilities. When you invest through a mutual fund, however, the timing of the sale of securities from the portfolio is out of your control, which reduces your ability to engage in tax management. Of course, if the mutual fund is held in a tax-deferred retirement account such as an IRA or 401(k) account, these tax management issues are irrelevant. A fund with a high portfolio turnover rate can be particularly “tax inefficient.” Turnover is the ratio of the trading activity of a portfolio to the assets of the portfolio. It measures the fraction of the portfolio that is “replaced” each year. For example, a $100 million portfolio with $50 million in sales of some securities with purchases of other securities would have a turnover rate of 50%. High turnover means that capital gains or losses are being realized constantly, and therefore that the investor cannot time the realizations to manage his or her overall tax obligation.

2

3. An investor’s portfolio currently is worth $1 million. During the year, the investor sells 1,000 shares of Microsoft at a price of $80 per share and 2,000 shares of Ford at a price of $40 per share. The proceeds are used to buy 1,600 shares of IBM at $100 per share. a. What was the portfolio turnover rate? b. If the shares in Microsoft originally were purchased for $70 each and those in Ford were purchased for $35, and if the investor’s tax rate on capital gains income is 20%, how much extra will the investor owe on this year’s taxes as a result of these transactions?

4.6 exchange-traded funds Offshoots of mutual funds that allow investors to trade index portfolios.

EXCHANGE-TRADED FUNDS

Exchange-traded funds (ETFs) are offshoots of mutual funds that allow investors to trade index portfolios just as they do shares of stock. The first ETF was the “Spider,” a nickname for SPDR or Standard & Poor’s Depository Receipt, which is a unit investment trust holding a portfolio matching the S&P 500 index. Unlike mutual funds, which can be bought or sold only at the end of the day when NAV is calculated, investors could trade Spiders throughout the day, just like any other share of stock. Spiders gave rise to many similar products such as “Diamonds” (based on the Dow Jones Industrial Average, ticker DIA), Cubes (based on the Nasdaq 100 Index, ticker QQQ), and WEBS (World Equity Benchmark Shares, which are shares in portfolios of foreign stock market indexes). By 2000, there were dozens of ETFs in three general classes: broad U.S. market indexes, narrow industry or “sector” portfolios, and international indexes, marketed as WEBS. Table 4.3, Panel A, presents some of the sponsors of ETFs; Panel B is a sample of ETFs. ETFs offer several advantages over conventional mutual funds. First, as we just noted, a mutual fund’s net asset value is quoted—and therefore, investors can buy or sell their shares in the fund—only once a day. In contrast, ETFs trade continuously. Moreover, like other shares, but unlike mutual funds, ETFs can be sold short or purchased on margin. ETFs also offer a potential tax advantage over mutual funds. When large numbers of mutual fund investors redeem their shares, the fund must sell securities to meet the redemptions. This can trigger capital gains taxes, which are passed through to and must be paid by the remaining shareholders. In contrast, when small investors wish to redeem their position in an ETF they simply sell their shares to other traders, with no need for the fund to sell any of the underlying portfolio. Moreover, when large traders wish to redeem their position in the ETF, redemptions are satisfied with shares of stock in the underlying portfolio. Again, a redemption does not trigger a stock sale by the fund sponsor. The ability of large investors to redeem ETFs for a portfolio of stocks comprising the index, or to exchange a portfolio of stocks for shares in the corresponding ETF, ensures that the price of an ETF cannot depart significantly from the NAV of that portfolio. Any meaningful discrepancy would offer arbitrage trading opportunities for these large traders, which would quickly eliminate the disparity. ETFs are also cheaper than mutual funds. Investors who buy ETFs do so through brokers, rather than buying directly from the fund. Therefore, the fund saves the cost of marketing

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A. ETF Sponsors

TA B L E 4.3 ETF sponsors and products

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Sponsor

Product Name

Barclays Global Investors Merrill Lynch StateStreet/Merrill Lynch Vanguard

i-Shares HOLDRS (Holding Company Depository Receipts: “Holders”) Select Sector SPDRs (S&P Depository Receipts: “Spiders”) VIPER (Vanguard Index Participation Equity Receipts: “VIPERS”)

B. Sample of ETF Products Name Broad U.S. Indexes Spiders Diamonds Cubes iShares Russell 2000 VIPER Industry Indexes Energy Select Spider iShares Energy Sector Financial Sector Spider iShares Financial Sector International Indexes WEBS United Kingdom WEBS France WEBS Japan

Ticker

Index Tracked

SPY DIA QQQ IWM VTI

S&P 500 Dow Jones Industrials Nasdaq 100 Russell 2000 Wilshire 5000

XLE IYE XLF IYF

S&P 500 energy companies Dow Jones energy companies S&P 500 financial companies Dow Jones financial companies

EWU EWQ EWJ

MCSI U.K. Index MCSI France Index MCSI Japan Index

itself directly to small investors. This reduction in expenses translates into lower management fees. For example, Barclays charges annual expenses of just over 9 basis points (i.e., .09%) of NAV per year on its S&P 500 ETF, whereas Vanguard charges 18 basis points on its S&P 500 index mutual fund. There are some disadvantages to ETFs, however. Because they trade as securities, there is the possibility that their prices can depart by small amounts from NAV. As noted, this discrepancy cannot be too large without giving rise to arbitrage opportunities for large traders, but even small discrepancies can easily swamp the cost advantage of ETFs over mutual funds. Second, while mutual funds can be bought for NAV with no expense from no-load funds, ETFs must be purchased from brokers for a fee. Investors also incur a bid–ask spread when purchasing an ETF. ETFs have to date been a huge success. Most trade on the Amex and currently account for about half of Amex trading volume. So far, ETFs have been limited to index portfolios. A variant on large exchange-traded funds in a “built-to-order” fund, marketed by sponsors to retail investors as folios, e-baskets, or personal funds. The sponsor establishes several model portfolios that investors can purchase as a basket. These baskets may be sector or broader-based portfolios. Alternatively, investors can custom-design their own portfolios. In either case, investors can trade these portfolios with the sponsor just as though it were a personalized mutual fund. The advantage of this arrangement is that, as is true of ETFs, the individual investor is fully in charge of the timing of purchases and sales of securities. In contrast to mutual funds, the investor’s tax liability is unaffected by the redemption activity of other

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investors. (Remember that in the case of mutual funds, redemptions can trigger the realization of capital gains that are passed through to all shareholders.) Of course, investors would similarly control their tax position using a typical brokerage account, but these basket accounts allow one to trade ready-made diversified portfolios. Investors typically pay an annual fee to participate in these plans.

WEBMA STER Exchange Traded Funds Go to William J. Bernstein’s website, http://www.efficientfrontier.com/ef/901/shootout. htm, for a discussion of potential advantages and disadvantages of ETFs versus index mutual funds. After reading the discussion, address the following questions: 1.

What did Mr. Bernstein conclude about tracking error on ETFs compared to index funds?

2.

What four reasons did he give for possibly favoring ETFs over index funds?

3.

What did the author mean by the statement that the ETF is only as good as its underlying index?

4.7

MUTUAL FUND INVESTMENT PERFORMANCE: A FIRST LOOK

We noted earlier that one of the benefits of mutual funds for the individual investor is the ability to delegate management of the portfolio to investment professionals. The investor retains control over the broad features of the overall portfolio through the asset allocation decision: Each individual chooses the percentages of the portfolio to invest in bond funds versus equity funds versus money market funds, and so forth, but can leave the specific security selection decisions within each investment class to the managers of each fund. Shareholders hope that these portfolio managers can achieve better investment performance than they could obtain on their own. What is the investment record of the mutual fund industry? This seemingly straightforward question is deceptively difficult to answer because we need a standard against which to evaluate performance. For example, we clearly would not want to compare the investment performance of an equity fund to the rate of return available in the money market. The vast differences in the risk of these two markets dictate that year-by-year as well as average performance will differ considerably. We would expect to find that equity funds outperform money market funds (on average) as compensation to investors for the extra risk incurred in equity markets. How can we determine whether mutual fund portfolio managers are performing up to par given the level of risk they incur? In other words, what is the proper benchmark against which investment performance ought to be evaluated? Measuring portfolio risk properly and using such measures to choose an appropriate benchmark is an extremely difficult task. We devote all of Parts II and III of the text to issues surrounding the proper measurement of portfolio risk and the trade-off between risk and return. In this chapter, therefore, we will satisfy ourselves with a first look at the question of fund performance by using only very simple performance benchmarks and ignoring the more subtle issues of risk differences across funds. However, we will return to this topic in Chapter 11,

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where we take a closer look at mutual fund performance after adjusting for differences in the exposure of portfolios to various sources of risk. Here, we will use as a benchmark for the performance of equity fund managers the rate of return on the Wilshire 5000 Index. Recall from Chapter 2 that this is a value-weighted index of about 7,000 stocks that trade on the NYSE, Nasdaq, and Amex stock markets. It is the most inclusive index of the performance of U.S. equities. The performance of the Wilshire 5000 is a useful benchmark with which to evaluate professional managers because it corresponds to a simple passive investment strategy: Buy all the shares in the index in proportion to their outstanding market value. Moreover, this is a feasible strategy for even small investors, because the Vanguard Group offers an index fund (its Total Stock Market Portfolio) designed to replicate the performance of the Wilshire 5000 Index. The expense ratio of the fund is extremely small by the standards of other equity funds, only .20% per year. Using the Wilshire 5000 Index as a benchmark, we may pose the problem of evaluating the performance of mutual fund portfolio managers this way: How does the typical performance of actively managed equity mutual funds compare to the performance of a passively managed portfolio that simply replicates the composition of a broad index of the stock market? By using the Wilshire 5000 as a benchmark, we use a well-diversified equity index to evaluate the performance of managers of diversified equity funds. Nevertheless, as noted earlier, this is only an imperfect comparison, as the risk of the Wilshire 5000 portfolio may not be comparable to that of any particular fund. Casual comparisons of the performance of the Wilshire 5000 Index versus that of professionally managed mutual fund portfolios show disappointing results for most fund managers. Figure 4.3 shows the percent of mutual fund managers whose performance was inferior in each year to the Wilshire 5000. In more years than not, the Index has outperformed the median manager. Figure 4.4 shows the cumulative return since 1970 of the Wilshire 5000 compared to the Lipper General Equity Fund Average. The annualized compound return of the Wilshire 5000 was 12.20% versus 11.11% for the average fund. The 1.09% margin is substantial. To some extent, however, this comparison is unfair. Real funds incur expenses that reduce the rate of return of the portfolio, as well as trading costs such as commissions and bid–ask

F I G U R E 4.3

90%

Percent of equity mutual funds outperformed by Wilshire 5000 Index, 1972–2001

80% 70% 60%

Source: The Vanguard Group.

50% 40% 30% 20%

2000

1998

1996

1994

1992

1990

1988

1986

1984

1982

1980

1978

1976

1974

0

1972

10%

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F I G U R E 4.4

50

Growth of $1 invested in Wilshire 5000 Index versus average general equity fund

Compound growth rate (% / year) Wilshire 5000 12.20 Average Fund 11.11

40 Portfolio Value

Source: The Vanguard Group.

30

20

2000

1998

1996

1994

1992

1990

1988

1986

1984

1982

1980

1978

1976

1974

0

1972

10

1970

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spreads that also reduce returns. John Bogle, former chairman of the Vanguard Group, has estimated that operating expenses reduce the return of typical managed portfolios by about 1% and that transaction fees associated with trading reduce returns by an additional .7%. In contrast, the return to the Wilshire index is calculated as though investors can buy or sell the index with reinvested dividends without incurring any expenses. These considerations suggest that a better benchmark for the performance of actively managed funds is the performance of index funds, rather than the performance of the indexes themselves. Vanguard’s Wilshire 5000 fund was established in 1992, and so has a relatively short track record. However, because it is passively managed, its expense ratio is only about 0.20%; moreover because index funds need to engage in very little trading, its turnover rate is about 3% per year, also extremely low. If we reduce the rate of return on the index by about 0.30%, we ought to obtain a good estimate of the rate of return achievable by a low-cost indexed portfolio. This procedure reduces the average margin of superiority of the index strategy over the average mutual fund from 1.09% to 0.79%, still suggesting that over the past two decades, passively managed (indexed) equity funds would have outperformed the typical actively managed fund. This result may seem surprising to you. After all, it would not seem unreasonable to expect that professional money managers should be able to outperform a very simple rule such as “hold an indexed portfolio.” As it turns out, however, there may be good reasons to expect such a result. We will explore them in detail in Chapter 8, where we discuss the efficient market hypothesis. Of course, one might argue that there are good managers and bad managers, and that the good managers can, in fact, consistently outperform the index. To test this notion, we examine whether managers with good performance in one year are likely to repeat that performance in a following year. In other words, is superior performance in any particular year due to luck, and therefore random, or due to skill, and therefore consistent from year to year? To answer this question, Goetzmann and Ibbotson3 examined the performance of a large sample of equity mutual fund portfolios over the 1976–1985 period. Dividing the funds into 3

William N. Goetzmann and Roger G. Ibbotson, “Do Winners Repeat?” Journal of Portfolio Management (Winter 1994), pp. 9–18.

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TA B L E 4.4 Consistency of investment results

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Initial Period Performance A. Goetzmann and Ibbotson study Top half Bottom half B. Malkiel study, 1970s Top half Bottom half C. Malkiel study, 1980s Top half Bottom half

Top Half

Bottom Half

62.0% 36.6%

38.0% 63.4%

65.1% 35.5%

34.9% 64.5%

51.7% 47.5%

48.3% 52.5%

Sources: Panel A: From “Do Winners Repeat?” by William N. Goetzmann and Roger G. Ibbotson, Journal of Portfolio Management, Winter 1994, pp. 9–18. Reprinted by permission of Institutional Investor. Panels B and C: From “Returns from Investing in Equity Mutual Funds 1971–1991,” by Burton G. Malkiel, Journal of Finance 50 (June 1995), pp. 549–572. Reprinted by permission of Blackwell Science, UK.

two groups based on total investment return for different subperiods, they posed the question: “Do funds with investment returns in the top half of the sample in one two-year period continue to perform well in the subsequent two-year period?” Panel A of Table 4.4 presents a summary of their results. The table shows the fraction of “winners” (i.e., top-half performers) in the initial period that turn out to be winners or losers in the following two-year period. If performance were purely random from one period to the next, there would be entries of 50% in each cell of the table, as top- or bottom-half performers would be equally likely to perform in either the top or bottom half of the sample in the following period. On the other hand, if performance were due entirely to skill, with no randomness, we would expect to see entries of 100% on the diagonals and entries of 0% on the off-diagonals: Top-half performers would all remain in the top half while all bottom-half performers similarly would all remain in the bottom half. In fact, the table shows that 62.0% of initial top-half performers fall in the top half of the sample in the following period, while 63.4% of initial bottom-half performers fall in the bottom half in the following period. This evidence is consistent with the notion that at least part of a fund’s performance is a function of skill as opposed to luck, so that relative performance tends to persist from one period to the next.4 On the other hand, this relationship does not seem stable across different sample periods. Malkiel5 uses a larger sample, but a similar methodology (except that he uses one-year instead of two-year investment returns) to examine performance consistency. He finds that while initial-year performance predicts subsequent-year performance in the 1970s (see Table 4.4, Panel B), the pattern of persistence in performance virtually disappears in the 1980s (Panel C). To summarize, the evidence that performance is consistent from one period to the next is suggestive, but it is inconclusive. In the 1970s, top-half funds in one year were twice as likely in the following year to be in the top half rather as the bottom half of funds. In the 1980s, the odds that a top-half fund would fall in the top half in the following year were essentially equivalent to those of a coin flip. Other studies suggest that bad performance is more likely to persist than good performance. This makes some sense: It is easy to identify fund characteristics that will predictably lead to consistently poor investment performance, notably high expense ratios, and high turnover 4

Another possibility is that performance consistency is due to variation in fee structure across funds. We return to this possibility in Chapter 11. 5 Burton G. Malkiel, “Returns from Investing in Equity Mutual Funds 1971–1991,” Journal of Finance 50 (June 1995), pp. 549–72.

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ratios with associated trading costs. It is far harder to identify the secrets of successful stock picking. (If it were easy, we would all be rich!) Thus the consistency we do observe in fund performance may be due in large part to the poor performers. This suggests that the real value of past performance data is to avoid truly poor funds, even if identifying the future top performers is still a daunting task.

Concept CHECK

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4. Suppose you observe the investment performance of 400 portfolio managers and rank them by investment returns during the year. Twenty percent of all managers are truly skilled, and therefore always fall in the top half, but the others fall in the top half purely because of good luck. What fraction of these top-half managers would you expect to be top-half performers next year? Assume skilled managers always are top-half performers.

4.8

INFORMATION ON MUTUAL FUNDS

The first place to find information on a mutual fund is in its prospectus. The Securities and Exchange Commission requires that the prospectus describe the fund’s investment objectives and policies in a concise “Statement of Investment Objectives” as well as in lengthy discussions of investment policies and risks. The fund’s investment adviser and its portfolio manager also are described. The prospectus also presents the costs associated with purchasing shares in the fund in a fee table. Sales charges such as front-end and back-end loads as well as annual operating expenses such as management fees and 12b-1 fees are detailed in the fee table. Despite this useful information, there is widespread agreement that until recently most prospectuses were difficult to read and laden with legalese. In 1999, however, the SEC required firms to prepare more easily understood prospectuses using less jargon, simpler sentences, and more charts. The nearby box contains some illustrative changes from two prospectuses that illustrate the scope of the problem the SEC was attempting to address. Still, even with these improvements, there remains a question as to whether these plain-English prospectuses contain the information an investor should know when selecting a fund. The answer, unfortunately, is that they still do not. The box also contains a discussion of the information one should look for, as well as what tends to be missing, from the usual prospectus. Funds provide information about themselves in two other sources. The Statement of Additional Information, also known as Part B of the prospectus, includes a list of the securities in the portfolio at the end of the fiscal year, audited financial statements, and a list of the directors and officers of the fund. The fund’s annual report, which generally is issued semiannually, also includes portfolio composition and financial statements, as well as a discussion of the factors that influenced fund performance over the last reporting period. With more than 8,000 mutual funds to choose from, it can be difficult to find and select the fund that is best suited for a particular need. Several publications now offer “encyclopedias” of mutual fund information to help in the search process. Two prominent sources are Wiesenberger’s Investment Companies and Morningstar’s Mutual Fund Sourcebook. The Investment Company Institute—the national association of mutual funds, closed-end funds, and unit investment trusts—publishes an annual Directory of Mutual Funds that includes information on fees as well as phone numbers to contact funds. To illustrate the range of information available about funds, we consider Morningstar’s report on Fidelity’s Magellan fund, reproduced in Figure 4.5. Some of Morningstar’s analysis is qualitative. The top box on the left-hand side of the page provides a short description of fund strategy, in particular the types of securities in which the fund manager tends to invest. The bottom box on the left (“Analysis”) is a more detailed discussion of the fund’s income strategy. The short statement of the fund’s investment policy is in the top right-hand corner: Magellan is a “large blend” fund, meaning that it tends to

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F I G U R E 4.5 Morningstar report Source: Morningstar Mutual Funds. © 2002 Morningstar, Inc. All rights reserved. 225 W. Wacker Dr., Chicago, IL . Although data are gathered from reliable sources, Morningstar cannot guarantee completeness and accuracy.

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Shorter, Clearer Mutual-Fund Disclosure May Omit Vital Investment Information Mutual-fund investors will receive shorter and clearer disclosure documents, under new rules adopted by the Securities and Exchange Commission. But despite all the hoopla surrounding the improvements—including a new “profile” prospectus and an easier-to-read full prospectus—there’s still a slew of vital information fund investors don’t get from any disclosure documents, long or short. Of course, more information isn’t necessarily better. As it is, investors rarely read fund disclosure documents, such as the prospectus (which funds must provide to prospective investors), the semiannual reports (provided to all fund investors) or the statement of additional information (made available upon request). Buried in each are a few nuggets of useful data; but for the most part, they’re full of legalese and technical terms. So what should funds be required to disclose that they currently don’t—and won’t have to even under the SEC’s new rules? Here’s a partial list: Tax-adjusted returns: Under the new rules, both the full prospectus and the fund profile must contain a bar chart of annual returns over the past 10 years, and the fund’s best and worst quarterly returns during that period. That’s a huge improvement over not long ago when a fund’s raw returns were sometimes nowhere to be found in the prospectus. But that doesn’t go far enough, according to some investment advisers. Many would like to see funds report returns after taxes—using assumptions about an investor’s tax bracket that would be disclosed in footnotes. The reason: Many funds make big payouts of dividends and capital gains, forcing investors to fork over a big chunk of their gains to the Internal Revenue Service.

What’s in the fund: If you’re about to put your retirement nest egg in a fund, shouldn’t you get to see what’s in it first? The zippy new profile prospectus describes a fund’s investment strategy, as did the old-style prospectus. But neither gives investors a look at what the fund actually owns. To get the fund’s holdings, you have to have its latest semiannual or annual report. Most people don’t get those documents until after they invest, and even then it can be as much as six months old. Many investment advisers think funds should begin reporting their holdings monthly, but so far funds have resisted doing so. A manager’s stake in a fund: Funds should be required to tell investors whether the fund manager owns any of its shares so investors can see just how confident a manager is in his or her own ability to pick stocks, some investment advisers say. As it stands now, many fund groups don’t even disclose the names and backgrounds of the men and women calling the shots, and instead report that their funds are managed by a “team” of individuals whose identities they don’t disclose. A breakdown of fees: Investors will see in the profile prospectus a clearer outline of the expenses incurred by the fund company that manages the portfolio. But there’s no way to tell whether you are picking up the tab for another guy’s lunch. The problem is, some no-load funds impose a socalled 12b-1 marketing fee on all shareholders. But they use the money gathered from the fee to cover the cost of participating in mutual-fund supermarket distribution programs. Only some fund shareholders buy the fund shares through these programs, but all shareholders bear the expense—including those who purchased shares directly from the fund.

invest in large firms, and not to specialize in either value versus growth stocks—it holds a blend of these. The table on the left labeled “Performance” reports on the fund’s returns over the last few years and over longer periods up to 15 years. Comparisons of returns to relevant indexes, in this case, the S&P 500 and the Wilshire top 750 indexes, are provided to serve as benchmarks in evaluating the performance of the fund. The values under these columns give the performance of the fund relative to the index. For example, Magellan’s return was 1.87% below the S&P 500 over the last three months, but 0.55% per year above the S&P over the past 5 years. The returns reported for the fund are calculated net of expenses, 12b-1 fees, and any other fees automatically deducted from fund assets, but they do not account for any sales charges such as front-end loads or back-end charges. Next appear the percentile ranks of the fund compared to all other funds (see column headed by All) and to all funds with the same investment objective (see column headed by Cat). A rank of 1 means the fund is a top performer. A rank of 80 would mean that it was beaten by 80% of funds in the comparison group. You can see 120

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Nice, Light Read: the Prospectus Old Language Dreyfus The Transfer Agent has adopted example standards and procedures pursuant to which signature-guarantees in proper form generally will be accepted from domestic banks, brokers, dealers, credit unions, national securities exchanges, registered securities associations, clearing agencies and savings associations, as well as from participants in the New York Stock Exchange Medallion Signature Program, the Securities Transfer Agents Medallion Program (“STAMP”) and the Stock Exchange Medallion Program. T. Rowe Price example

Total Return. The Fund may advertise total return figures on both a cumulative and compound average annual basis. Cumulative total return compares the amount invested at the beginning of a period with the amount redeemed at the end of the period, assuming the reinvestment of all dividends and capital gain distributions. The compound average annual total return, derived from the cumulative total return figure, indicates a yearly average of the Fund’s performance. The annual compound rate of return for the Fund may vary from any average.

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Plain English A signature guarantee helps protect against fraud. You can obtain one from most banks or securities dealers, but not from a notary public.

Total Return. This tells you how much an investment in a fund has changed in value over a given time period. It reflects any net increase or decrease in the share price and assumes that all dividends and capital gains (if any) paid during the period were reinvested in additional shares. Therefore, total return numbers include the effect of compounding. Advertisements for a fund may include cumulative or average annual total return figures, which may be compared with various indices, other performance measures, or other mutual funds.

Sources: Adapted from Vanessa O’Connell, “Shorter, Clearer, Mutual-Fund Disclosure May Omit Vital Investment Information,” The Wall Street Journal, March 12, 1999. Reprinted by permission of Dow Jones & Company, Inc., via Copyright Clearance Center, Inc. © 1999 Dow Jones & Company, Inc. All Rights Reserved Worldwide. “A Little Light Reading? Try a Fund Prospectus,” The Wall Street Journal, May 3, 1999. p. R1. Reprinted by permission of Dow Jones & Company, Inc., via Copyright Clearance Center, Inc. © 1999 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

from the table that Magellan has had below-par recent (three month to three year) performance compared to other growth and income funds, but excellent longer-term performance. For example, over the past 15 years, its average return was higher than all but 13% of the funds in its category. Finally, growth of $10,000 invested in the fund over various periods ranging from the past three months to the past 15 years is given in the last column. More data on the performance of the fund are provided in the graph at the top right of the figure. The bar charts give the fund’s rate of return for each quarter of the last 10 years. Below the graph is a box for each year that depicts the relative performance of the fund for that year. The shaded area on the box shows the quartile in which the fund’s performance falls relative to other funds with the same objective. If the shaded band is at the top of the box, the firm was a top quartile performer in that period, and so on. 121

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The table below the bar charts presents historical data on characteristics of the fund. These data include return, return relative to appropriate benchmark indexes such as the S&P 500, the component of returns due to income (dividends) or capital gains, the percentile rank of the fund compared to all funds and funds in its objective class (where, again, 1% is the best performer and 99% would mean that the fund was outperformed by 99% of its comparison group), the expense ratio, and the turnover rate of the portfolio. The table on the right entitled Portfolio Analysis presents the 25 largest holdings of the portfolio, showing the price–earnings ratio and year-to-date return of each of those securities. Investors can thus get a quick look at the manager’s biggest bets. Below the portfolio analysis table is a box labeled Current Investment Style. In this box, Morningstar evaluates style along two dimensions: One dimension is the size of the firms held in the portfolio as measured by the market value of outstanding equity; the other dimension is a value/growth continuum. Morningstar defines value stocks as those with low ratios of market price per share to various measures of value. It puts stocks on a growth-value continuum based on the ratios of stock price to the firm’s earnings, book value, sales, cash flow, and dividends. Value stocks are those with a low price relative to these measures of value. In contrast, growth stocks have high ratios, suggesting that investors in these firms must believe that the firm will experience rapid growth to justify the prices at which the stocks sell. The shaded box for Magellan shows that the portfolio tends to hold larger firms (top row) and blend stocks (middle column). A year-by-year history of Magellan’s investment style is presented in the sequence of such boxes at the top of the figure. The center of the figure, labeled Risk Analysis, is one of the more complicated but interesting facets of Morningstar’s analysis. The column labeled Load-Adj Return rates a fund’s return compared to other funds with the same investment policy. Returns for periods ranging from 1 to 10 years are calculated with all loads and back-end fees applicable to that investment period subtracted from total income. The return is then divided by the average return for the comparison group of funds to obtain the Morningstar Return; therefore, a value of 1.0 in the Return column would indicate average performance while a value of 1.10 would indicate returns 10% above the average for the comparison group (e.g., 11% return for the fund versus 10% for the comparison group). The risk measure indicates the portfolio’s exposure to poor performance, that is, the “downside risk” of the fund. Morningstar bases its risk measure in part on the overall volatility of returns. However, it focuses more intently on episodes of underperformance relative to Treasury bills. The total underperformance compared to T-bills in those months with poor portfolio performance divided by total months sampled is part of the measure of downside risk. The risk measure also is scaled by dividing by the average risk measure for all firms with the same investment objective. Therefore, the average value in the Risk column is 1.0. The two columns to the left of the Morningstar Risk and Return columns are the percentile scores of risk and return for each fund. The risk-adjusted rating, ranging from one to five stars, is based on the Morningstar return score minus the risk score. The stars each fund earns are based on risk-adjusted performance relative to other funds in the same style group. To allow funds to be compared to other funds with similar investment styles, Morningstar recently increased the number of categories; there are now 18 separate stock fund groups and 20 fixed income categories. The tax analysis box on the left provides some evidence on the tax efficiency of the fund by comparing pretax and after-tax returns. The after-tax return, given in the first column, is computed based on the dividends paid to the portfolio as well as realized capital gains, assuming the investor is in the maximum tax bracket at the time of the distribution. State and local taxes are ignored. The “tax efficiency” of the fund is defined as the ratio of after-tax to pretax returns; it is presented in the second column, labeled % Pretax Return. Tax efficiency will be lower when turnover is higher because capital gains are taxed as they are realized.

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The bottom of the page provides information on the expenses and loads associated with investments in the fund, as well as information on the fund’s investment adviser. Thus, Morningstar provides a considerable amount of the information you would need to decide among several competing funds.

closed-end fund, 101 exchange-traded funds, 112 hedge fund, 103

investment company, 100 load, 103 net asset value (NAV), 100 open-end fund, 101

soft dollars, 110 12b-1 fees, 108 turnover, 111 unit investment trust, 101

SUMMARY

KEY TERMS

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• Unit investment trusts, closed-end management companies, and open-end management companies are all classified and regulated as investment companies. Unit investment trusts are essentially unmanaged in the sense that the portfolio, once established, is fixed. Managed investment companies, in contrast, may change the composition of the portfolio as deemed fit by the portfolio manager. Closed-end funds are traded like other securities; they do not redeem shares for their investors. Open-end funds will redeem shares for net asset value at the request of the investor. • Net asset value equals the market value of assets held by a fund minus the liabilities of the fund divided by the shares outstanding. • Mutual funds free the individual from many of the administrative burdens of owning individual securities and offer professional management of the portfolio. They also offer advantages that are available only to large-scale investors, such as lower trading costs. On the other hand, funds are assessed management fees and incur other expenses, which reduce the investor’s rate of return. Funds also eliminate some of the individual’s control over the timing of capital gains realizations. • Mutual funds often are categorized by investment policy. Major policy groups include money market funds; equity funds, which are further grouped according to emphasis on income versus growth; fixed-income funds; balanced and income funds; asset allocation funds; index funds; and specialized sector funds. • Costs of investing in mutual funds include front-end loads, which are sales charges; backend loads, which are redemption fees or, more formally, contingent-deferred sales charges; fund operating expenses; and 12b-1 charges, which are recurring fees used to pay for the expenses of marketing the fund to the public. • Income earned on mutual fund portfolios is not taxed at the level of the fund. Instead, as long as the fund meets certain requirements for pass-through status, the income is treated as being earned by the investors in the fund. • The average rate of return of the average equity mutual fund in the last 25 years has been below that of a passive index fund holding a portfolio to replicate a broad-based index like the S&P 500 or Wilshire 5000. Some of the reasons for this disappointing record are the costs incurred by actively managed funds, such as the expense of conducting the research to guide stock-picking activities, and trading costs due to higher portfolio turnover. The record on the consistency of fund performance is mixed. In some sample periods, the better-performing funds continue to perform well in the following periods; in other sample periods they do not.

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1. Would you expect a typical open-end fixed-income mutual fund to have higher or lower operating expenses than a fixed-income unit investment trust? Why? 2. An open-end fund has a net asset value of $10.70 per share. It is sold with a front-end load of 6%. What is the offering price? 3. If the offering price of an open-end fund is $12.30 per share and the fund is sold with a front-end load of 5%, what is its net asset value? 4. The composition of the Fingroup Fund portfolio is as follows: Stock

Shares

Price

A B C D

200,000 300,000 400,000 600,000

$35 40 20 25

The fund has not borrowed any funds, but its accrued management fee with the portfolio manager currently totals $30,000. There are 4 million shares outstanding. What is the net asset value of the fund? 5. Reconsider the Fingroup Fund in the previous problem. If during the year the portfolio manager sells all of the holdings of stock D and replaces it with 200,000 shares of stock E at $50 per share and 200,000 shares of stock F at $25 per share, what is the portfolio turnover rate? 6. The Closed Fund is a closed-end investment company with a portfolio currently worth $200 million. It has liabilities of $3 million and 5 million shares outstanding. a. What is the NAV of the fund? b. If the fund sells for $36 per share, what is its premium or discount as a percent of NAV? 7. Corporate Fund started the year with a net asset value of $12.50. By year-end, its NAV equaled $12.10. The fund paid year-end distributions of income and capital gains of $1.50. What was the rate of return to an investor in the fund? 8. A closed-end fund starts the year with a net asset value of $12.00. By year-end, NAV equals $12.10. At the beginning of the year, the fund is selling at a 2% premium to NAV. By the end of the year, the fund is selling at a 7% discount to NAV. The fund paid year-end distributions of income and capital gains of $1.50. a. What is the rate of return to an investor in the fund during the year? b. What would have been the rate of return to an investor who held the same securities as the fund manager during the year? 9. What are some comparative advantages of investing your assets in the following: a. Unit investment trusts. b. Open-end mutual funds. c. Individual stocks and bonds that you choose for yourself. 10. Open-end equity mutual funds find it necessary to keep a significant percentage of total investments, typically around 5% of the portfolio, in very liquid money market assets. Closed-end funds do not have to maintain such a position in “cash-equivalent” securities. What difference between open-end and closed-end funds might account for their differing policies? 11. Balanced funds and asset allocation funds invest in both the stock and bond markets. What is the difference between these types of funds?

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12. a. Impressive Fund had excellent investment performance last year, with portfolio returns that placed it in the top 10% of all funds with the same investment policy. Do you expect it to be a top performer next year? Why or why not? b. Suppose instead that the fund was among the poorest performers in its comparison group. Would you be more or less likely to believe its relative performance will persist into the following year? Why? 13. Consider a mutual fund with $200 million in assets at the start of the year and with 10 million shares outstanding. The fund invests in a portfolio of stocks that provides dividend income at the end of the year of $2 million. The stocks included in the fund’s portfolio increase in price by 8%, but no securities are sold, and there are no capital gains distributions. The fund charges 12b-1 fees of 1%, which are deducted from portfolio assets at year-end. What is net asset value at the start and end of the year? What is the rate of return for an investor in the fund? 14. The New Fund had average daily assets of $2.2 billion in the past year. The fund sold $400 million and purchased $500 million worth of stock during the year. What was its turnover ratio? 15. If New Fund’s expense ratio was 1.1% and the management fee was .7%, what were the total fees paid to the fund’s investment managers during the year? What were the other administrative expenses? 16. You purchased 1,000 shares of the New Fund at a price of $20 per share at the beginning of the year. You paid a front-end load of 4%. The securities in which the fund invests increase in value by 12% during the year. The fund’s expense ratio is 1.2%. What is your rate of return on the fund if you sell your shares at the end of the year? 17. The Investments Fund sells Class A shares with a front-end load of 6% and Class B shares with 12b-1 fees of .5% annually as well as back-end load fees that start at 5% and fall by 1% for each full year the investor holds the portfolio (until the fifth year). Assume the portfolio rate of return net of operating expenses is 10% annually. If you plan to sell the fund after four years, are Class A or Class B shares the better choice for you? What if you plan to sell after 15 years? 18. Suppose you observe the investment performance of 350 portfolio managers for five years, and rank them by investment returns during each year. After five years, you find that 11 of the funds have investment returns that place the fund in the top half of the sample in each and every year of your sample. Such consistency of performance indicates to you that these must be the funds whose managers are in fact skilled, and you invest your money in these funds. Is your conclusion warranted? 19. You are considering an investment in a mutual fund with a 4% load and an expense ratio of .5%. You can invest instead in a bank CD paying 6% interest. a. If you plan to invest for two years, what annual rate of return must the fund portfolio earn for you to be better off in the fund than in the CD? Assume annual compounding of returns. b. How does your answer change if you plan to invest for six years? Why does your answer change? c. Now suppose that instead of a front-end load the fund assesses a 12b-1 fee of .75% per year. What annual rate of return must the fund portfolio earn for you to be better off in the fund than in the CD? Does your answer in this case depend on your time horizon? 20. Suppose that every time a fund manager trades stock, transaction costs such as commissions and bid–ask spreads amount to .4% of the value of the trade. If the portfolio turnover rate is 50%, by how much is the total return of the portfolio reduced by trading costs?

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21. You expect a tax-free municipal bond portfolio to provide a rate of return of 4%. Management fees of the fund are .6%. What fraction of portfolio income is given up to fees? If the management fees for an equity fund also are .6%, but you expect a portfolio return of 12%, what fraction of portfolio income is given up to fees? Why might management fees be a bigger factor in your investment decision for bond funds than for stock funds? Can your conclusion help explain why unmanaged unit investment trusts tend to focus on the fixed-income market?

WEBMA STER Mutual Fund Report Go to http://morningstar.com. From the home page select the Funds tab. From this location you can request information on an individual fund. In the dialog box enter the ticker JANSX, for the Janus Fund, and enter Go. This contains the report information on the fund. On the left-hand side of the screen are tabs that allow you to view the various components of the report. Using the components specified, answer the following questions on the Janus Fund:

SOLUTIONS TO

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1.

Morningstar analysis: What is the Morningstar rating? What has been the fund’s year-to-date return?

2.

Total returns: What are the 5- and 10-year returns and how do they compare with the return of the S&P?

3.

Ratings and risk: What is the beta of the fund? What are the mean and standard deviation of returns? What is the 10-year rating on the fund?

4.

Portfolio: What two sectors’ weightings are the largest? What percent of the portfolio assets are in cash?

5.

Nuts and bolts: What is the fund’s total expense ratio? Who is the current manager of the fund and what was his/her start date? How long has the fund been in operation?

1. NAV ⫽ ($14,754 ⫺ $1,934)/419.4 ⫽ $30.57 2. The net investment in the Class A shares after the 4% commission is $9,600. If the fund earns a 10% return, the investment will grow after n years to $9,600 ⫻ (1.10)n. The Class B shares have no front-end load. However, the net return to the investor after 12b-1 fees will be only 9.5%. In addition, there is a back-end load that reduces the sales proceeds by a percentage equal to (5 ⫺ years until sale) until the fifth year, when the back-end load expires. Class A Shares

Class B Shares

Horizon

$9,600 ⴛ (1.10)

1 year 4 years 10 years

$10,560.00 14,055.36 $24,899.93

n

$10,000 ⴛ (1.095)n ⴛ (1 ⴚ percentage exit fee) $10,000 ⫻ (1.095) ⫻ (1 ⫺ .04) $10,000 ⫻ (1.095)4 ⫻ (1 ⫺ .01) $10,000 ⫻ (1.095)10

⫽ $10,512.00 ⫽ $14,232.89 ⫽ $24,782.28

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For a very short horizon such as one year, the Class A shares are the better choice. The front-end and back-end loads are equal, but the Class A shares don’t have to pay the 12b-1 fees. For moderate horizons such as four years, the Class B shares dominate because the front-end load of the Class A shares is more costly than the 12b-1 fees and the now smaller exit fee. For long horizons of 10 years or more, Class A again dominates. In this case, the one-time front-end load is less expensive than the continuing 12b-1 fees. 3. a. Turnover ⫽ $160,000 in trades per $1 million of portfolio value ⫽ 16%. b. Realized capital gains are $10 ⫻ 1,000 ⫽ $10,000 on Microsoft and $5 ⫻ 2,000 ⫽ $10,000 on Ford. The tax owed on the capital gains is therefore .20 ⫻ $20,000 ⫽ $4,000.

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4. Twenty percent of the managers are skilled, which accounts for .2 ⫻ 400 ⫽ 80 of those managers who appear in the top half. There are 120 slots left in the top half, and 320 other managers, so the probability of an unskilled manager “lucking into” the top half in any year is 120/320, or .375. Therefore, of the 120 lucky managers in the first year, we would expect .375 ⫻ 120 ⫽ 45 to repeat as top-half performers next year. Thus, we should expect a total of 80 ⫹ 45 ⫽ 125, or 62.5%, of the better initial performers to repeat their top-half performance.

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Introduction

PA RT

TWO

PORTFOLIO THEORY

uppose you believe that investments in stocks offer an expected rate of return of 10% while the expected rate of return on bonds is only 6%. Would you invest all of your money in stocks? Probably not: putting all of your eggs in one basket in such a manner would violate even the most basic notion of diversification. But what is the optimal combination of these two asset classes? And how will the opportunity to invest in other asset classes—for example, real estate, foreign stocks, precious metals, and so on—affect your decision? In short, is there a “best” solution to your asset allocation problem? These questions are the focus of the first chapters of Part II, which address what has come to be known as Modern Portfolio Theory, or MPT. In large part, MPT addresses the question of “efficient diversification,” how to achieve the best trade-off between portfolio risk and reward.

S

>

This analysis quickly leads to other questions. For example, how should one measure the risk of an individual asset held as part of a diversified portfolio? You will probably be surprised at the answer. Once we have an acceptable measure of risk, what precisely should be the relation between risk and return? And what is the minimally acceptable rate of return for an investment to be considered attractive? These questions also are addressed in this Part of the text. Finally, we come to one of the most controversial topics in investment management, the question of whether portfolio managers— amateur or professional—can outperform simple investment strategies such as “buy a market index fund.” The evidence will at least make you pause before pursuing active strategies. You will come to appreciate how good active managers must be to outperform their passive counterparts.

5

Risk and Return: Past and Prologue

6

Efficient Diversification

7

Capital Asset Pricing and Arbitrage Pricing Theory

8

The Efficient Market Hypothesis

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5 RISK AND RETURN: PAST AND PROLOGUE

AFTER STUDYING THIS CHAPTER YOU SHOULD BE ABLE TO:

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Use data on the past performance of stocks and bonds to characterize the risk and return features of these investments.

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Determine the expected return and risk of portfolios that are constructed by combining risky assets with risk-free investments in Treasury bills.

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Evaluate the performance of a passive strategy.

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Related Websites http://www.bloomberg.com/markets/wei.html http://app.marketwatch.com/intl/default.asp http://www.quote.com/quotecom/markets/ snapshot.asp These websites list returns on various equity indexes.

http://www.standardandpoors.com This site gives detailed analysis on index returns. Analysis of historical returns and comparisons to other indexes are available. The site also reports on changes to the index.

http://www.indexfunds.com/data/ IndexScreener.php This site contains information on virtually all available indexes. It also has a screening program that allows you to rank indexes by various return measures.

http://online.wsj.com/home/us http://www.smartmoney.com/bonds http://www.bloomberg.com/markets/rates.html These sites report current rates on U.S. and international government bonds.

http://www.bondmarkets.com http://www.investinginbonds.com These two sites are pages from the bond market association. General information on a variety of bonds and strategies can be accessed online at no charge. Current information on rates is also available at investinginbonds.com.

http://www.stls.frb.org This site contains current and historical information on a variety of interest rates. Historical data can be downloaded in spreadsheet format, which is available through the Federal Reserve Economic Database (FRED).

hat constitutes a satisfactory investment portfolio? Until the early 1970s, a reasonable answer would have been a bank savings account (a risk-free asset) plus a risky portfolio of U.S. stocks. Nowadays, investors have access to a vastly wider array of assets and may contemplate complex portfolio strategies that may include foreign stocks and bonds, real estate, precious metals, and collectibles. Even more complex strategies may include futures and options to insure portfolios against unacceptable losses. How might such portfolios be constructed? Clearly every individual security must be judged on its contributions to both the expected return and the risk of the entire portfolio. These contributions must be evaluated in the context of the expected performance of the overall portfolio. To guide us in forming reasonable expectations for portfolio performance, we will start this chapter with an examination of various conventions for measuring and reporting rates of return. Given these measures, we turn to the historical performance of several broadly diversified investment portfolios. In doing so, we use a risk-free portfolio of Treasury bills as a benchmark to evaluate the historical performance of diversified stock and bond portfolios. We then proceed to consider the trade-offs investors face when they practice the simplest form of risk control: choosing the fraction of the portfolio invested in virtually risk-free money market securities versus risky securities such as stocks. We show how to calculate the performance one may reasonably expect from various allocations between a risk-free asset and a risky portfolio and discuss the considerations that determine the mix that would best suit different investors. With this background, we can evaluate a passive strategy that will serve as a benchmark for the active strategies considered in the next chapter.

W

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5.1 holding-period return Rate of return over a given investment period.

RATES OF RETURN

A key measure of investors’ success is the rate at which their funds have grown during the investment period. The total holding-period return (HPR) of a share of stock depends on the increase (or decrease) in the price of the share over the investment period as well as on any dividend income the share has provided. The rate of return is defined as dollars earned over the investment period (price appreciation as well as dividends) per dollar invested HPR

Ending price Beginning price Cash dividend Beginning price

This definition of the HPR assumes that the dividend is paid at the end of the holding period. To the extent that dividends are received earlier, the definition ignores reinvestment income between the receipt of the dividend and the end of the holding period. Recall also that the percentage return from dividends is called the dividend yield, and so the dividend yield plus the capital gains yield equals the HPR. This definition of holding return is easy to modify for other types of investments. For example, the HPR on a bond would be calculated using the same formula, except that the bond’s interest or coupon payments would take the place of the stock’s dividend payments.

5.1 EXAMPLE Holding-Period Return

Suppose you are considering investing some of your money, now all invested in a bank account, in a stock market index fund. The price of a share in the fund is currently $100, and your time horizon is one year. You expect the cash dividend during the year to be $4, so your expected dividend yield is 4%. Your HPR will depend on the price one year from now. Suppose your best guess is that it will be $110 per share. Then your capital gain will be $10, so your capital gains yield is $10/$100 .10, or 10%. The total holding period rate of return is the sum of the dividend yield plus the capital gain yield, 4% 10% 14%. HPR

$110 $100 $4 $100

.14, or 14%

Measuring Investment Returns over Multiple Periods The holding period return is a simple and unambiguous measure of investment return over a single period. But often you will be interested in average returns over longer periods of time. For example, you might want to measure how well a mutual fund has performed over the preceding five-year period. In this case, return measurement is more ambiguous. Consider, for example, a fund that starts with $1 million under management at the beginning of the year. The fund receives additional funds to invest from new and existing shareholders, and also receives requests for redemptions from existing shareholders. Its net cash inflow can be positive or negative. Suppose its quarterly results are as given in Table 5.1 with negative numbers reported in parentheses. The story behind these numbers is that when the firm does well (i.e., reports a good HPR), it attracts new funds; otherwise it may suffer a net outflow. For example, the 10% return in the first quarter by itself increased assets under management by 0.10 $1 million $100,000; it also elicited new investments of $100,000, thus bringing assets under management to $1.2 million by the end of the quarter. An even better HPR in the second quarter elicited a larger net inflow, and the second quarter ended with $2 million under management. However, HPR in the third quarter was negative, and net inflows were negative.

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TA B L E 5.1 Quarterly cash flows and rates of return of a mutual fund

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Assets under management at start of quarter ($ million) Holding-period return (%) Total assets before net inflows Net inflow ($ million)* Assets under management at end of quarter ($ million)

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1st Quarter

2nd Quarter

3rd Quarter

4th Quarter

1.0

1.2

2.0

0.8

10.0 1.1 0.1 1.2

25.0 1.5 0.5 2.0

(20.0) 1.6 (0.8) 0.8

25.0 1.0 0.0 1.0

*

New investment less redemptions and distributions, all assumed to occur at the end of each quarter.

How would we characterize fund performance over the year, given that the fund experienced both cash inflows and outflows? There are several candidate measures of performance, each with its own advantages and shortcomings. These are the arithmetic average, the geometric average, and the dollar-weighted return. These measures may vary considerably, so it is important to understand their differences.

Arithmetic average The arithmetic average of the quarterly returns is just the sum of

the quarterly returns divided by the number of quarters; in the above example: (10 25 20 25)/4 10%. Since this statistic ignores compounding, it does not represent an equivalent, single quarterly rate for the year. The arithmetic average is useful, though, because it is the best forecast of performance in future quarters, using this particular sample of historic returns. (Whether the sample is large enough or representative enough to make accurate forecasts is, of course, another question.)

Geometric average The geometric average of the quarterly returns is equal to the single per-period return that would give the same cumulative performance as the sequence of actual returns. We calculate the geometric average by compounding the actual period-by-period returns and then finding the equivalent single per-period return. In this case, the geometric average quarterly return, rG, is defined by: (1 0.10) (1 0.25) (1 0.20) (1 0.25) (1 rG)4 so that rG [(1 0.10) (1 0.25) (1 0.20) (1 0.25)]1/4 1 .0829, or 8.29% The geometric return also is called a time-weighted average return because it ignores the quarter-to-quarter variation in funds under management. In fact, an investor will obtain a larger cumulative return if high returns are earned in those periods when additional sums have been invested, while the lower returns are realized when less money is at risk. Here, the highest returns (25%) were achieved in quarters 2 and 4, when the fund managed $1,200,000 and $800,000, respectively. The worst returns (20% and 10%) occurred when the fund managed $2,000,000 and $1,000,000, respectively. In this case, better returns were earned when less money was under management—an unfavorable combination. The appeal of the time-weighted return is that in some cases we wish to ignore variation in money under management. For example, published data on past returns earned by mutual funds actually are required to be time-weighted returns. The rationale for this practice is that since the fund manager does not have full control over the amount of assets under management, we should not weight returns in one period more heavily than those in other periods when assessing “typical” past performance.

arithmetic average The sum of returns in each period divided by the number of periods.

geometric average The single per-period return that gives the same cumulative performance as the sequence of actual returns.

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Dollar-weighted return When we wish to account for the varying amounts under management, we treat the fund cash flows to investors as we would a capital budgeting problem in corporate finance. The initial value of $1 million and the net cash inflows are treated as the cash flows associated with an investment “project.” The final “liquidation value” of the project is the ending value of the portfolio. In this case, therefore, investor net cash flows are as follows: Time

Net cash flow ($ million)

dollar-weighted average return The internal rate of return on an investment.

0

1

2

3

4

1.0

0.1

0.5

0.8

1.0

The entry for time 0 reflects the starting contribution of $1 million, while the entries for times 1, 2, and 3 represent net inflows at the end of the first three quarters. Finally, the entry for time 4 represents the value of the portfolio at the end of the fourth quarter. This is the value for which the portfolio could have been liquidated by year-end based on the initial investment and net additional investments earlier in the year. The dollar-weighted average return is the internal rate of return (IRR) of the project, which is 4.17%. The IRR is the interest rate that sets the present value of the cash flows realized on the portfolio (including the $1 million for which the portfolio can be liquidated at the end of the year) equal to the initial cost of establishing the portfolio. It therefore is the interest rate that satisfies the following equation: 0.8 1.0 0.1 0.5 1.0 3 (1 IRR) (1 IRR)4 1 IRR (1 IRR)2 The dollar-weighted return in this example is less than the time-weighted return of 8.29% because, as we noted, the portfolio returns were higher when less money was under management. The difference between the dollar- and time-weighted average return in this case is quite large.

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1. A fund begins with $10 million and reports the following three-month results (with negative figures in parentheses): Month

Net inflows (end of month, $ million) HPR (%)

1

2

3

3 2

5 8

0 (4)

Compute the arithmetic, time-weighted, and dollar-weighted average returns.

Conventions for Quoting Rates of Return We’ve seen that there are several ways to compute average rates of return. There also is some variation in how the mutual fund in our example might annualize its quarterly returns. Returns on assets with regular cash flows, such as mortgages (with monthly payments) and bonds (with semiannual coupons), usually are quoted as annual percentage rates, or APRs, which annualize per-period rates using a simple interest approach, ignoring compound interest. The APR can be translated to an effective annual rate (EAR) by remembering that APR Per-period rate Periods per year

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Therefore, to obtain the EAR if there are n compounding periods in the year, we first recover the rate per period as APR/n and then compound that rate for the number of periods in a year. (For example, n 12 for mortgages and n 2 for bonds making payments semiannually).

(

1 EAR (1 Rate per period)n 1

APR n

n

)

Rearranging, APR [(1 EAR)1/n 1] n

(5.1)

The formula assumes that you can earn the APR each period. Therefore, after one year (when n periods have passed), your cumulative return would be (1 APR/n)n. Note that one needs to know the holding period when given an APR in order to convert it to an effective rate. The EAR diverges from the APR as n becomes larger (that is, as we compound cash flows more frequently). In the limit, we can envision continuous compounding when n becomes extremely large in Equation 5.1. With continuous compounding, the relationship between the APR and EAR becomes EAR eAPR 1 or equivalently, APR ln(1 EAR)

(5.2)

Suppose you buy a Treasury bill maturing in one month for $9,900. On the bill’s maturity date, you collect the face value of $10,000. Since there are no other interest payments, the holding period return for this one-month investment is: HPR

Cash income Price change Initial price

$100 $9,900

0.0101 1.01%

The APR on this investment is therefore 1.01% 12 12.12%. The effective annual rate is higher: 1 EAR (1.0101)12 1.1282 which implies that EAR .1282 12.82%

The difficulties in interpreting rates of return over time do not end here. Two thorny issues remain: the uncertainty surrounding the investment in question and the effect of inflation.

5.2

RISK AND RISK PREMIUMS

Any investment involves some degree of uncertainty about future holding period returns, and in most cases that uncertainty is considerable. Sources of investment risk range from macroeconomic fluctuations, to the changing fortunes of various industries, to asset-specific unexpected developments. Analysis of these multiple sources of risk is presented in Part Four on Security Analysis.

Scenario Analysis and Probability Distributions When we attempt to quantify risk, we begin with the question: What HPRs are possible, and how likely are they? A good way to approach this question is to devise a list of possible economic

EXAMPLE 5.2 Annualizing Treasury-Bill Returns

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TA B L E 5.2

State of the Economy

Probability distribution of HPR on the stock market

Boom Normal growth Recession

scenario analysis Process of devising a list of possible economic scenarios and specifying the likelihood of each one, as well as the HPR that will be realized in each case.

probability distribution List of possible outcomes with associated probabilities.

expected return The mean value of the distribution of holding period returns.

variance The expected value of the squared deviation from the mean.

Scenario, s

Probability, p(s)

1 2 3

0.25 0.50 0.25

The square root of the variance.

HPR 44% 14 16

outcomes, or scenarios, and specify both the likelihood (i.e., the probability) of each scenario and the HPR the asset will realize in that scenario. Therefore, this approach is called scenario analysis. The list of possible HPRs with associated probabilities is called the probability distribution of HPRs. Consider an investment in a broad portfolio of stocks, say an index fund, which we will refer to as the “stock market.” A very simple scenario analysis for the stock market (assuming only three possible scenarios) is illustrated in Table 5.2. The probability distribution lets us derive measurements for both the reward and the risk of the investment. The reward from the investment is its expected return, which you can think of as the average HPR you would earn if you were to repeat an investment in the asset many times. The expected return also is called the mean of the distribution of HPRs and often is referred to as the mean return. To compute the expected return from the data provided, we label scenarios by s and denote the HPR in each scenario as r(s), with probability p(s). The expected return, denoted E(r), is then the weighted average of returns in all possible scenarios, s 1, . . . , S, with weights equal to the probability of that particular scenario. E(r)

S

兺 s1

p(s)r(s)

(5.3)

We show in Example 5.3, which follows shortly, that the data in Table 5.2 imply E(r) 14%. Of course, there is risk to the investment, and the actual return may be more or less than 14%. If a “boom” materializes, the return will be better, 44%, but in a recession, the return will be only 16%. How can we quantify the uncertainty of the investment? The “surprise” return on the investment in any scenario is the difference between the actual return and the expected return. For example, in a boom (scenario 1) the surprise is 30%: r(1) E(r) 44% 14% 30%. In a recession (scenario 3), the surprise is 30%: r(3) E(r) 16% 14% 30%. Uncertainty surrounding the investment is a function of the magnitudes of the possible surprises. To summarize risk with a single number we first define the variance as the expected value of the squared deviation from the mean (i.e., the expected value of the squared “surprise” across scenarios). Var(r) ⬅ 2

standard deviation

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S

兺 s1

p(s)[r(s) E(r)]2

(5.4)

We square the deviations because if we did not, negative deviations would offset positive deviations, with the result that the expected deviation from the mean return would necessarily be zero. Squared deviations are necessarily positive. Of course, squaring (a nonlinear transformation) exaggerates large (positive or negative) deviations and relatively deemphasizes small deviations. Another result of squaring deviations is that the variance has a dimension of percent squared. To give the measure of risk the same dimension as expected return (%), we use the standard deviation, defined as the square root of the variance: SD(r) ⬅ 兹苵苵苵苵苵 Var(r)

(5.5)

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A potential drawback to the use of variance and standard deviation as measures of risk is that they treat positive deviations and negative deviations from the expected return symmetrically. In practice, of course, investors welcome positive surprises, and a natural measure of risk would focus only on bad outcomes. However, if the distribution of returns is symmetric (meaning that the likelihood of negative surprises is roughly equal to the probability of positive surprises of the same magnitude), then standard deviation will approximate risk measures that concentrate solely on negative deviations. In the special case that the distribution of returns is approximately normal—represented by the well-known bell-shaped curve—the standard deviation will be perfectly adequate to measure risk. The evidence shows that for fairly short holding periods, the returns of most diversified portfolios are well described by a normal distribution. Applying Equation 5.3 to the data in Table 5.2, we find that the expected rate of return on the stock index fund is E(r) 0.25 44% 0.50 14% 0.25 (16%) 14% We use Equation 5.4 to find the variance. First we take the difference between the holding period return in each scenario and the mean return, then we square that difference, and finally we multiply by the probability of each scenario to find the average of the squared deviations. The result is

EXAMPLE 5.3 Expected Return and Standard Deviation

2 0.25(44 14)2 0.50(14 14)2 0.25(16 14)2 450 and so the standard deviation is 兹苵苵苵 450 21.21%

2. A share of stock of A-Star Inc. is now selling for $23.50. A financial analyst summarizes the uncertainty about the rate of return on the stock by specifying three possible scenarios: Business Conditions

Scenario, s

Probability, p

End-of-Year Price

Annual Dividend

High growth Normal growth No growth

1 2 3

0.35 0.30 0.35

$35 27 15

$4.40 4.00 4.00

5. a. Suppose the real interest rate is 3% per year, and the expected inflation rate is 8%. What is the nominal interest rate? b. Suppose the expected inflation rate rises to 10%, but the real rate is unchanged. What happens to the nominal interest rate?

5.5

asset allocation Portfolio choice among broad investment classes.

ASSET ALLOCATION ACROSS RISKY AND RISK-FREE PORTFOLIOS

History shows us that long-term bonds have been riskier investments than investments in Treasury bills and that stock investments have been riskier still. On the other hand, the riskier investments have offered higher average returns. Investors, of course, do not make all-ornothing choices from these investment classes. They can and do construct their portfolios using securities from all asset classes. Some of the portfolio may be in risk-free Treasury bills and some in high-risk stocks. The most straightforward way to control the risk of the portfolio is through the fraction of the portfolio invested in Treasury bills and other safe money market securities versus risky assets. This is an example of an asset allocation choice—a choice among broad investment classes, rather than among the specific securities within each asset class. Most investment professionals consider asset allocation the most important part of portfolio construction. Consider this statement by John Bogle, made when he was the chairman of the Vanguard Group of Investment Companies: The most fundamental decision of investing is the allocation of your assets: How much should you own in stock? How much should you own in bonds? How much should you own in cash reserves? . . . That decision [has been shown to account] for an astonishing 94% of the differences

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in total returns achieved by institutionally managed pension funds. . . . There is no reason to believe that the same relationship does not also hold true for individual investors.4

Therefore, we start our discussion of the risk-return trade-off available to investors by examining the most basic asset allocation choice: the choice of how much of the portfolio to place in risk-free money market securities versus other risky asset classes. We will denote the investor’s portfolio of risky assets as P, and the risk-free asset as F. We will assume for the sake of illustration that the risky component of the investor’s overall portfolio comprises two mutual funds: one invested in stocks and the other invested in long-term bonds. For now, we take the composition of the risky portfolio as given and focus only on the allocation between it and risk-free securities. In the next chapter, we turn to asset allocation and security selection across risky assets.

The Risky Asset When we shift wealth from the risky portfolio (P) to the risk-free asset, we do not change the relative proportions of the various risky assets within the risky portfolio. Rather, we reduce the relative weight of the risky portfolio as a whole in favor of risk-free assets. A simple example demonstrates the procedure. Assume the total market value of an investor’s portfolio is $300,000. Of that, $90,000 is invested in the Ready Assets money market fund, a risk-free asset. The remaining $210,000 is in risky securities, say $113,400 in the Vanguard S&P 500 index fund (called the Vanguard 500 Index Fund) and $96,600 in Fidelity’s Investment Grade Bond Fund. The Vanguard fund (V) is a passive equity fund that replicates the S&P 500 portfolio. The Fidelity Investment Grade Bond Fund (IG) invests primarily in corporate bonds with high safety ratings and also in Treasury bonds. We choose these two funds for the risky portfolio in the spirit of a low-cost, well-diversified portfolio. While in the next chapter we discuss portfolio optimization, here we simply assume the investor considers the given weighting of V and IG to be optimal. The holdings in Vanguard and Fidelity make up the risky portfolio, with 54% in V and 46% in IG. wV 113,400/210,000 0.54 (Vanguard) wIG 96,600/210,000 0.46 (Fidelity) The weight of the risky portfolio, P, in the complete portfolio, including risk-free as well as risky investments, is denoted by y, and so the weight of the money market fund is 1 y. y 210,000/300,000 0.7 (risky assets, portfolio P) 1 y 90,000/300,000 0.3 (risk-free assets) The weights of the individual assets in the complete portfolio (C) are: Vanguard Fidelity

113,400/300,000 0.378 96,600/300,000 0.322

Portfolio P 210,000/300,000 0.700 Ready Assets F 90,000/300,000 0.300 Portfolio C

300,000/300,000 1.000

Suppose the investor decides to decrease risk by reducing the exposure to the risky portfolio from y 0.7 to y 0.56. The risky portfolio would total only 0.56 300,000 $168,000, requiring the sale of $42,000 of the original $210,000 risky holdings, with the proceeds used to 4

John C. Bogle, Bogle on Mutual Funds (Burr Ridge, IL: Irwin Professional Publishing, 1994), p. 235.

complete portfolio The entire portfolio including risky and risk-free assets.

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purchase more shares in Ready Assets. Total holdings in the risk-free asset will increase to 300,000 (1 0.56) $132,000 (the original holdings plus the new contribution to the money market fund: 90,000 42,000 $132,000). The key point is that we leave the proportion of each asset in the risky portfolio unchanged. Because the weights of Vanguard and Fidelity in the risky portfolio are 0.54 and 0.46 respectively, we sell 0.54 42,000 $22,680 of Vanguard and 0.46 42,000 $19,320 of Fidelity. After the sale, the proportions of each fund in the risky portfolio are unchanged. wV

113,400 22,680 0.54 (Vanguard) 210,000 42,000

wIG

96,600 19,320 0.46 (Fidelity) 210,000 42,000

This procedure shows that rather than thinking of our risky holdings as Vanguard and Fidelity separately, we may view our holdings as if they are in a single fund holding Vanguard and Fidelity in fixed proportions. In this sense, we may treat the risky fund as a single risky asset, that asset being a particular bundle of securities. As we shift in and out of safe assets, we simply alter our holdings of that bundle of securities commensurately. Given this simplification, we now can turn to the desirability of reducing risk by changing the risky/risk-free asset mix, that is, reducing risk by decreasing the proportion y. Because we do not alter the weights of each asset within the risky portfolio, the probability distribution of the rate of return on the risky portfolio remains unchanged by the asset reallocation. What will change is the probability distribution of the rate of return on the complete portfolio that is made up of the risky and risk-free assets.

Concept CHECK

>

6. What will be the dollar value of your position in Vanguard and its proportion in your complete portfolio if you decide to hold 50% of your investment budget in Ready Assets?

The Risk-Free Asset The power to tax and to control the money supply lets the government, and only government, issue default-free bonds. The default-free guarantee by itself is not sufficient to make the bonds risk-free in real terms, since inflation affects the purchasing power of the proceeds from an investment in T-bills. The only risk-free asset in real terms would be a price-indexed government bond. Even then, a default-free, perfectly indexed bond offers a guaranteed real rate to an investor only if the maturity of the bond is identical to the investor’s desired holding period. These qualifications notwithstanding, it is common to view Treasury bills as the risk-free asset. Because they are short-term investments, their prices are relatively insensitive to interest rate fluctuations. An investor can lock in a short-term nominal return by buying a bill and holding it to maturity. Any inflation uncertainty over the course of a few weeks, or even months, is negligible compared to the uncertainty of stock market returns. In practice, most investors treat a broader range of money market instruments as effectively risk-free assets. All the money market instruments are virtually immune to interest rate risk (unexpected fluctuations in the price of a bond due to changes in market interest rates) because of their short maturities, and all are fairly safe in terms of default or credit risk. Money market mutual funds hold, for the most part, three types of securities: Treasury bills, bank certificates of deposit (CDs), and commercial paper. The instruments differ slightly in their default risk. The yields to maturity on CDs and commercial paper, for identical maturities, are always slightly higher than those of T-bills. A history of this yield spread for 90-day CDs is shown in Figure 2.3 in Chapter 2.

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Money market funds have changed their relative holdings of these securities over time, but by and large, T-bills make up only about 15% of their portfolios. Nevertheless, the risk of such blue-chip, short-term investments as CDs and commercial paper is minuscule compared to that of most other assets, such as long-term corporate bonds, common stocks, or real estate. Hence, we treat money market funds as representing the most easily accessible risk-free asset for most investors.

Portfolio Expected Return and Risk Now that we have specified the risky portfolio and the risk-free asset, we can examine the risk-return combinations that result from various investment allocations between these two assets. Finding the available combinations of risk and return is the “technical” part of asset allocation; it deals only with the opportunities available to investors given the features of the asset markets in which they can invest. In the next section, we address the “personal” part of the problem, the specific individual’s choice of the best risk-return combination from the set of feasible combinations, given his or her level of risk aversion. Since we assume the composition of the optimal risky portfolio (P) already has been determined, the concern here is with the proportion of the investment budget (y) to be allocated to the risky portfolio. The remaining proportion (1 y) is to be invested in the risk-free asset (F). We denote the actual risky rate of return by rP, the expected rate of return on P by E(rP), and its standard deviation by P. The rate of return on the risk-free asset is denoted as rf. In the numerical example, we assume E(rP) 15%, P 22%, and rf 7%. Thus, the risk premium on the risky asset is E(rP) rf 8%. Let’s start with two extreme cases. If you invest all of your funds in the risky asset, that is, if you choose y 1.0, the expected return on your complete portfolio will be 15% and the standard deviation will be 22%. This combination of risk and return is plotted as point P in Figure 5.5. At the other extreme, you might put all of your funds into the risk-free asset, that

E(r)

CAL = Capital allocation line P

E(rP) = 15% y = .50 rƒ = 7% F

y = 1.25 E(rP) – rƒ = 8%

S = 8/22

σP = 22%

F I G U R E 5.5 The investment opportunity set with a risky asset and a risk-free asset

σ

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is, you choose y 0. In this case, your portfolio would behave just as the risk-free asset, and you would earn a riskless return of 7%. (This choice is plotted as point F in Figure 5.5.) Now consider more moderate choices. For example, if you allocate equal amounts of your overall or complete portfolio, C, to the risky and risk-free assets, that is, if you choose y 0.5, the expected return on the complete portfolio will be an average of the expected return on portfolios F and P. Therefore, E(rC) 0.5 7% 0.5 15% 11%. The risk premium of the complete portfolio is therefore 11% 7% 4%, which is half of the risk premium of P. The standard deviation of the portfolio also is one-half of P’s, that is, 11%. When you reduce the fraction of the complete portfolio allocated to the risky asset by half, you reduce both the risk and risk premium by half. To generalize, the risk premium of the complete portfolio, C, will equal the risk premium of the risky asset times the fraction of the portfolio invested in the risky asset. E(rC) rf y[E(rP) rf]

(5.9)

The standard deviation of the complete portfolio will equal the standard deviation of the risky asset times the fraction of the portfolio invested in the risky asset. C yP

(5.10)

In sum, both the risk premium and the standard deviation of the complete portfolio increase in proportion to the investment in the risky portfolio. Therefore, the points that describe the risk and return of the complete portfolio for various asset allocations, that is, for various choices of y, all plot on the straight line connecting F and P, as shown in Figure 5.5, with an intercept of rf and slope (rise/run) of S

Concept CHECK

>

E(rP) rf 15 7 0.36 P 22

(5.11)

7. What are the expected return, risk premium, standard deviation, and ratio of risk premium to standard deviation for a complete portfolio with y 0.75?

The Capital Allocation Line capital allocation line Plot of risk-return combinations available by varying portfolio allocation between a risk-free asset and a risky portfolio.

The line plotted in Figure 5.5 depicts the risk-return combinations available by varying asset allocation, that is, by choosing different values of y. For this reason, it is called the capital allocation line, or CAL. The slope, S, of the CAL equals the increase in expected return that an investor can obtain per unit of additional standard deviation. In other words, it shows extra return per extra risk. For this reason, the slope also is called the reward-to-variability ratio. Notice that the reward-to-variability ratio is the same for risky portfolio P and the complete portfolio that was formed by mixing P and the risk-free asset in equal proportions. Expected Return

Risk Premium

Standard Deviation

reward-tovariability ratio

Portfolio P:

15%

8%

22%

Ratio of risk premium to standard deviation.

Portfolio C:

11%

4%

11%

Reward-toVariability Ratio 8 0.36 22 4 0.36 11

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In fact, the reward-to-variability ratio is the same for all complete portfolios that plot on the capital allocation line. While the risk-return combinations differ, the ratio of reward to risk is constant. What about points on the line to the right of portfolio P in the investment opportunity set? If investors can borrow at the (risk-free) rate of rf 7%, they can construct complete portfolios that plot on the CAL to the right of P. They simply choose values of y greater than 1.0. Suppose the investment budget is $300,000, and our investor borrows an additional $120,000, investing the $420,000 in the risky asset. This is a levered position in the risky asset, which is financed in part by borrowing. In that case y 420,000 1.4 300,000 and 1 y 1 1.4 0.4, reflecting a short position in the risk-free asset, or a borrowing position. Rather than lending at a 7% interest rate, the investor borrows at 7%. The portfolio rate of return is

EXAMPLE 5.6 Levered Complete Portfolios

E(rC) 7 (1.4 8) 18.2 Another way to find this portfolio rate of return is as follows. Your income statement will show that you expect to earn $63,000 (15% of $420,000) and pay $8,400 (7% of $120,000) in interest on the loan. Simple subtraction yields an expected profit of $54,000, which is 18.2% of your investment budget of $300,000. Your portfolio still exhibits the same reward-to-variability ratio: C 1.4 22 30.8 11.2 E(rC) rf S C 30.8

0.36

As you might have expected, the levered portfolio has both a higher expected return and a higher standard deviation than an unlevered position in the risky asset.

Of course, nongovernment investors cannot borrow at the risk-free rate. The risk of a borrower’s default leads lenders to demand higher interest rates on loans. Therefore, the nongovernment investor’s borrowing cost will exceed the lending rate of rf 7%. Suppose the borrowing rate is rB 9%. Then, for y greater than 1.0 (the borrowing range), the reward-to-variability ratio (the slope of the CAL) will be: [E(rP) rB]/P 6/22 0.27. Here, the borrowing rate (rB) replaces the lending rate (rf), reducing the “reward” (numerator) in the reward-to-variability ratio. The CAL will be “kinked” at point P as in Figure 5.6. To the left of P, where y 1, the investor is lending at 7% and the slope of the CAL is 0.36. To the right of P, where y 1, the investor is borrowing (at a higher than risk-free rate) to finance extra investments in the risky asset, and the slope is 0.27. In practice, borrowing to invest in the risky portfolio is easy and straightforward if you have a margin account with a broker. All you have to do is tell your broker you want to buy “on margin.” Margin purchases may not exceed 50% of the purchase value. For example, if your net worth in the account is $300,000, the broker is allowed to lend you up to $300,000 to purchase additional stock. You would then have $600,000 on the asset side of your account and $300,000 on the liability side, resulting in y 2.0. 8. Suppose there is a shift upward in the expected rate of return on the risky asset, from 15% to 17%. If all other parameters remain unchanged, what will be the slope of the CAL for y 1 and y 1?

1) = .27

S(y ≤ 1) = .36

σP = 22%

σ

F I G U R E 5.6 The opportunity set with differential borrowing and lending rates

Risk Tolerance and Asset Allocation We have developed the CAL, the graph of all feasible risk-return combinations available from allocating the complete portfolio between a risky portfolio and a risk-free asset. The investor confronting the CAL now must choose one optimal combination from the set of feasible choices. This choice entails a trade-off between risk and return. Individual investors with different levels of risk aversion, given an identical capital allocation line, will choose different positions in the risky asset. Specifically, the more risk-averse investors will choose to hold less of the risky asset and more of the risk-free asset. Graphically, more risk-averse investors will choose portfolios near point F on the capital allocation line plotted in Figure 5.5. More risk-tolerant investors will choose points closer to P, with higher expected return and higher risk. The most risk-tolerant investors will choose portfolios to the right of point P. These levered portfolios provide even higher expected returns, but even greater risk. The nearby box contains a further discussion of this risk-return trade-off, which sometimes is characterized as a decision to “eat well,” versus “sleep well.” You will eat well if you earn a high expected rate of return on your portfolio. However, this requires that you accept a large risk premium and, therefore, a large amount of risk. Unfortunately, this risk may make it difficult to sleep well. The investor’s asset allocation choice also will depend on the trade-off between risk and return. If the reward-to-variability ratio increases, then investors might well decide to take on riskier positions. For example, suppose an investor reevaluates the probability distribution of the risky portfolio and now perceives a greater expected return without an accompanying increase in the standard deviation. This amounts to an increase in the reward-to-variability ratio

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The Right Mix: Make Money vs. Sleep Soundly Plunged into doubt? Amid the recent market turmoil, maybe you are wondering whether you really have the right mix of investments. Here are a few thoughts to keep in mind:

TAKING STOCK If you are a bond investor who is petrified of stocks, the wild price swings of the past few weeks have probably confirmed all of your worst suspicions. But the truth is, adding stocks to your bond portfolio could bolster your returns, without boosting your portfolio’s overall gyrations. How can that be? While stocks and bonds often move up and down in tandem, this isn’t always the case, and sometimes stocks rise when bonds are tumbling. Indeed, Chicago researchers Ibbotson Associates figure a portfolio that’s 100% in longer-term government bonds has the same risk profile as a mix that includes 83% in longer-term government bonds and 17% in the blue-chip stocks that constitute Standard & Poor’s 500 stock index. The bottom line? Everybody should own some stocks. Even cowards.

PADDING THE MATTRESS On the other hand, maybe you’re a committed stock market investor, but you would like to add a calming influence to your portfolio. What’s your best bet? When investors look to mellow their stock portfolios, they usually turn to bonds. Indeed, the traditional balanced portfolio, which typically includes 60% stocks

and 40% bonds, remains a firm favorite with many investment experts. A balanced portfolio isn’t a bad bet. But if you want to calm your stock portfolio, I would skip bonds and instead add cash investments such as Treasury bills and money market funds. Ibbotson calculates that, over the past 25 years, a mix of 75% stocks and 25% Treasury bills would have performed about as well as a mix of 60% stocks and 40% longer-term government bonds, and with a similar level of portfolio price gyrations. Moreover, the stock–cash mix offers more certainty, because you know that even if your stocks fall in value, your cash never will. By contrast, both the stocks and bonds in a balanced portfolio can get hammered at the same time.

PATIENCE HAS ITS REWARDS, SOMETIMES Stocks are capable of generating miserable short-run results. During the past 50 years, the worst five-calendaryear stretch for stocks left investors with an annualized loss of 2.4%. But while any investment can disappoint in the short run, stocks do at least sparkle over the long haul. As a long-term investor, your goal is to fend off the dual threats of inflation and taxes and make your money grow. And on that score, stocks have been supreme. SOURCE: Abridged from Jonathan Clements, “The Right Mix: FineTuning a Portfolio to Make Money and Still Sleep Soundly,” The Wall Street Journal, July 23, 1996. Reprinted by permission of Dow Jones & Company, Inc. via Copyright Clearance Center, Inc. © 1996 Dow Jones & Company, Inc. All rights reserved Worldwide.

or, equivalently, an increase in the slope of the CAL. As a result, this investor will choose a higher y, that is, a greater position in the risky portfolio. One role of a professional financial adviser is to present investment opportunity alternatives to clients, obtain an assessment of the client’s risk tolerance, and help determine the appropriate complete portfolio.5

5.6

PASSIVE STRATEGIES AND THE CAPITAL MARKET LINE

The capital allocation line shows the risk-return trade-offs available by mixing risk-free assets with the investor’s risky portfolio. Investors can choose the assets included in the risky 5

“Risk tolerance” is simply the flip side of “risk aversion.” Either term is a reasonable way to describe attitudes toward risk. We generally find it easier to talk about risk aversion, but practitioners often use the term risk tolerance.

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Risk Premium (%)

TA B L E 5.5 Average rates of return, standard deviations, and the reward-to-variability ratio of the risk premiums of large common stocks over one-month bills over 1926–2001 and various subperiods.

1926–1944 1945–1963 1964–1982 1983–2001 1926–2001

Mean

Standard Deviation

Reward-toVariability Ratio

8.03 14.41 2.22 9.91 8.64

28.69 18.83 17.56 14.77 20.70

0.2798 0.7655 0.1265 0.6709 0.4176

Source: Prepared from data in Table 5.3.

passive strategy Investment policy that avoids security analysis.

capital market line The capital allocation line using the market index portfolio as the risky asset.

portfolio using either passive or active strategies. A passive strategy is based on the premise that securities are fairly priced and it avoids the costs involved in undertaking security analysis. Such a strategy might at first blush appear to be naive. However, we will see in Chapter 8 that intense competition among professional money managers might indeed force security prices to levels at which further security analysis is unlikely to turn up significant profit opportunities. Passive investment strategies may make sense for many investors. To avoid the costs of acquiring information on any individual stock or group of stocks, we may follow a “neutral” diversification approach. A natural strategy is to select a diversified portfolio of common stocks that mirrors the corporate sector of the broad economy. This results in a value-weighted portfolio, which, for example, invests a proportion in GM stock that equals the ratio of GM’s market value to the market value of all listed stocks. Such strategies are called indexing. The investor chooses a portfolio with all the stocks in a broad market index such as the Standard & Poor’s 500 index. The rate of return on the portfolio then replicates the return on the index. Indexing has become an extremely popular strategy for passive investors. We call the capital allocation line provided by one-month T-bills and a broad index of common stocks the capital market line (CML). That is, a passive strategy based on stocks and bills generates an investment opportunity set that is represented by the CML.

Historical Evidence on the Capital Market Line Can we use past data to help forecast the risk-return trade-off offered by the CML? The notion that one can use historical returns to forecast the future seems straightforward but actually is somewhat problematic. On one hand, you wish to use all available data to obtain a large sample. But when using long time series, old data may no longer be representative of future circumstances. Another reason for weeding out subperiods is that some past events simply may be too improbable to be given equal weight with results from other periods. Do the data we have pose this problem? Table 5.5 breaks the 76-year period, 1926–2001 into four subperiods and shows the risk premium, standard deviation, and reward-to-variability ratio for each subperiod. That ratio is

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Triumph of the Optimists As a whole, the last 7 decades have been very kind to U.S. equity investors. Stock investments have outperformed investments in safe Treasury bills by more than 8% per year. The real rate of return averaged more than 9%, implying an expected doubling of the real value of the investment portfolio about every 8 years! Is this experience representative? A new book by three professors at the London Business School, Elroy Dimson, Paul Marsh, and Mike Staunton, extends the U.S. evidence to other countries and to longer time periods. Their conclusion is given in the book’s title, Triumph of the Optimists*: in every country in their study (which included markets in North America, Europe, Asia, and Africa), the investment optimists—those who bet on the economy by investing in stocks rather than bonds or bills—were vindicated. Over the long haul, stocks beat bonds everywhere. On the other hand, the equity risk premium is probably not as large as the post-1926 evidence from

Table 5.1 would seem to indicate. First, results from the first 25 years of the last century (which included the first World War) were less favorable to stocks. Second, U.S. returns have been better than that of most other countries, and so a more representative value for the historical risk premium may be lower than the U.S. experience. Finally, the sample that is amenable to historical analysis suffers from a self-selection problem. Only those markets that have survived to be studied can be included in the analysis. This leaves out countries such as Russia or China, whose markets were shut down during communist rule, and whose results if included would surely bring down the average performance of equity investments. Nevertheless, there is powerful evidence of a risk premium that shows its force everywhere the authors looked. *Elroy Dimson, Paul Marsh, Mike Staunton, Triumph of the Optimists: 101 Years of Global Investment Returns. Princeton University Press, Princeton, N.J.: 2002.

the slope of the CML based on the subperiod data. Indeed, the differences across subperiods are quite striking. The most plausible explanation for the variation in subperiod returns is based on the observation that the standard deviation of returns is quite large in all subperiods. If we take the 76-year standard deviation of 20.3% as representative and assume that returns in one year are nearly uncorrelated with those in other years (the evidence suggests that any correlation across years is small), then the standard deviation of our estimate of the mean return in any of our 19-year subperiods will be 20.3/ 兹苵苵 19 4.7% , which is fairly large. This means that in approximately one out of three cases, a 19-year average will deviate by 4.7% or more from the true mean. Applying this insight to the data in Table 5.5 tells us that we cannot reject with any confidence the possibility that the true mean is similar in all subperiods! In other words, the “noise” in the data is so large that we simply cannot make reliable inferences from average returns in any subperiod. The variation in returns across subperiods may simply reflect statistical variation, and we have to reconcile ourselves to the fact that the market return and the reward-to-variability ratio for passive (as well as active!) strategies is simply very hard to predict. The instability of average excess return on stocks over the 19-year subperiods in Table 5.5 also calls into question the precision of the 76-year average excess return (8.64%) as an estimate of the risk premium on stocks looking into the future. In fact, there has been considerable recent debate among financial economists about the “true” equity risk premium, with an emerging consensus that the historical average is an unrealistically high estimate of the future risk premium. This argument is based on several factors: the use of longer time periods in

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which equity returns are examined; a broad range of countries rather than just the U.S. in which excess returns are computed (Dimson, Marsh, and Staunton, 2001); direct surveys of financial executives about their expectations for stock market returns (Graham and Harvey, 2001); and inferences from stock market data about investor expectations (Jagannathan, McGrattan, and Scherbina, 2000; Fama and French, 2002). The nearby box discusses some of this evidence.

Costs and Benefits of Passive Investing How reasonable is it for an investor to pursue a passive strategy? We cannot answer such a question definitively without comparing passive strategy results to the costs and benefits accruing to an active portfolio strategy. Some issues are worth considering, however. First, the alternative active strategy entails costs. Whether you choose to invest your own valuable time to acquire the information needed to generate an optimal active portfolio of risky assets or whether you delegate the task to a professional who will charge a fee, constructing an active portfolio is more expensive than constructing a passive one. The passive portfolio requires only small commissions on purchases of U.S. T-bills (or zero commissions if you purchase bills directly from the government) and management fees to a mutual fund company that offers a market index fund to the public. An index fund has the lowest operating expenses of all mutual stock funds because it requires minimal effort. A second argument supporting a passive strategy is the free-rider benefit. If you assume there are many active, knowledgeable investors who quickly bid up prices of undervalued assets and offer down overvalued assets (by selling), you have to conclude that most of the time most assets will be fairly priced. Therefore, a well-diversified portfolio of common stock will be a reasonably fair buy, and the passive strategy may not be inferior to that of the average active investor. We will expand on this insight and provide a more comprehensive analysis of the relative success of passive strategies in Chapter 8. To summarize, a passive strategy involves investment in two passive portfolios: virtually risk-free short-term T-bills (or a money market fund) and a fund of common stocks that mimics a broad market index. Recall that the capital allocation line representing such a strategy is called the capital market line. Using Table 5.5, we see that using 1926 to 2001 data, the passive risky portfolio has offered an average excess return of 8.6% with a standard deviation of 20.7%, resulting in a reward-to-variability ratio of 0.42.

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SUMMARY

• Investors face a trade-off between risk and expected return. Historical data confirm our intuition that assets with low degrees of risk provide lower returns on average than do those of higher risk. • Shifting funds from the risky portfolio to the risk-free asset is the simplest way to reduce risk. Another method involves diversification of the risky portfolio. We take up diversification in later chapters. • U.S. T-bills provide a perfectly risk-free asset in nominal terms only. Nevertheless, the standard deviation of real rates on short-term T-bills is small compared to that of assets such as long-term bonds and common stocks, so for the purpose of our analysis, we consider T-bills the risk-free asset. Besides T-bills, money market funds hold short-term, safe obligations such as commercial paper and CDs. These entail some default risk but relatively little compared to most other risky assets. For convenience, we often refer to money market funds as risk-free assets. • A risky investment portfolio (referred to here as the risky asset) can be characterized by its reward-to-variability ratio. This ratio is the slope of the capital allocation line (CAL), the

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line connecting the risk-free asset to the risky asset. All combinations of the risky and riskfree asset lie on this line. Investors would prefer a steeper sloping CAL, because that means higher expected returns for any level of risk. If the borrowing rate is greater than the lending rate, the CAL will be “kinked” at the point corresponding to an investment of 100% of the complete portfolio in the risky asset. • An investor’s preferred choice among the portfolios on the capital allocation line will depend on risk aversion. Risk-averse investors will weight their complete portfolios more heavily toward Treasury bills. Risk-tolerant investors will hold higher proportions of their complete portfolios in the risky asset. • The capital market line is the capital allocation line that results from using a passive investment strategy that treats a market index portfolio, such as the Standard & Poor’s 500, as the risky asset. Passive strategies are low-cost ways of obtaining well-diversified portfolios with performance that will reflect that of the broad stock market. expected return, 136 geometric average, 133 holding-period return, 132 inflation rate, 147 nominal interest rate, 147 passive strategy, 156 probability distribution, 136 real interest rate, 147

reward-to-variability ratio, 152 risk aversion, 138 risk-free rate, 137 risk premium, 137 scenario analysis, 136 standard deviation, 136 variance, 136

1. A portfolio of nondividend-paying stocks earned a geometric mean return of 5.0% between January 1, 1996, and December 31, 2002. The arithmetic mean return for the same period was 6.0 %. If the market value of the portfolio at the beginning of 1996 was $100,000, what was the market value of the portfolio at the end of 2002? 2. Which of the following statements about the standard deviation is/are true? A standard deviation: i. Is the square root of the variance. ii. Is denominated in the same units as the original data. iii. Can be a positive or a negative number. 3. Which of the following statements reflects the importance of the asset allocation decision to the investment process? The asset allocation decision: a. Helps the investor decide on realistic investment goals. b. Identifies the specific securities to include in a portfolio. c. Determines most of the portfolio’s returns and volatility over time. d. Creates a standard by which to establish an appropriate investment time horizon. 4. Look at Table 5.2 in the text. Suppose you now revise your expectations regarding the stock market as follows: State of the Economy

Probability

HPR

Boom Normal growth Recession

0.3 0.4 0.3

44% 14 16

KEY TERMS

PROBLEM SETS

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arithmetic average, 133 asset allocation, 148 capital allocation line, 152 capital market line, 156 complete portfolio, 149 dollar-weighted average return, 134 excess return, 138

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Use Equations 5.3–5.5 to compute the mean and standard deviation of the HPR on stocks. Compare your revised parameters with the ones in the text. 5. The stock of Business Adventures sells for $40 a share. Its likely dividend payout and end-of-year price depend on the state of the economy by the end of the year as follows: Dividend

Stock Price

$2.00 1.00 .50

$50 43 34

Boom Normal economy Recession

a. Calculate the expected holding-period return and standard deviation of the holdingperiod return. All three scenarios are equally likely. b. Calculate the expected return and standard deviation of a portfolio invested half in Business Adventures and half in Treasury bills. The return on bills is 4%. Use the following data in answering questions 6, 7, and 8. Utility Formula Data Investment

Expected Return E(r)

Standard Deviation

1 2 3 4

.12 .15 .21 .24

.30 .50 .16 .21

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U E(r) 1⁄2A2

where A 4

6. Based on the utility formula above, which investment would you select if you were risk averse with A 4? a. 1 b. 2 c. 3 d. 4 7. Based on the utility formula above, which investment would you select if you were risk neutral? a. 1 b. 2 c. 3 d. 4 8. The variable (A) in the utility formula represents the: a. investor’s return requirement. b. investor’s aversion to risk. c. certainty equivalent rate of the portfolio. d. preference for one unit of return per four units of risk. Use the following expectations on Stocks X and Y to answer questions 9 through 12 (round to the nearest percent).

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Bear Market

Normal Market

Bull Market

0.2 20% 15%

0.5 18% 20%

0.3 50% 10%

Probability Stock X Stock Y

161

9. What are the expected returns for Stocks X and Y? Stock X

Stock Y

18% 18% 20% 20%

5% 12% 11% 10%

a. b. c. d.

10. What are the standard deviations of returns on Stocks X and Y? Stock X

Stock Y

15% 20% 24% 28%

26% 4% 13% 8%

a. b. c. d.

Probability of Economic State

Stock Performance

Probability of Stock Performance in Given Economic State

Good

.3

Neutral

.5

Poor

.2

Good Neutral Poor Good Neutral Poor Good Neutral Poor

.6 .3 .1 .4 .3 .3 .2 .3 .5

State of Economy

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11. Assume that of your $10,000 portfolio, you invest $9,000 in Stock X and $1,000 in Stock Y. What is the expected return on your portfolio? a. 18% b. 19% c. 20% d. 23% 12. Probabilities for three states of the economy, and probabilities for the returns on a particular stock in each state are shown in the table below.

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The probability that the economy will be neutral and the stock will experience poor performance is a. .06 c. .50 b. .15 d. .80 13. An analyst estimates that a stock has the following probabilities of return depending on the state of the economy: State of Economy

Probability

Return

.1 .6 .3

15% 13 7

Good Normal Poor

The expected return of the stock is: a. 7.8% b. 11.4% c. 11.7% d. 13.0% 14. XYZ stock price and dividend history are as follows:

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15.

16. 17. 18.

Year

Beginning-of-Year Price

Dividend Paid at Year-End

1999 2000 2001 2002

$100 $110 $ 90 $ 95

$4 $4 $4 $4

An investor buys three shares of XYZ at the beginning of 1999 buys another two shares at the beginning of 2000, sells one share at the beginning of 2001, and sells all four remaining shares at the beginning of 2002. a. What are the arithmetic and geometric average time-weighted rates of return for the investor? b. What is the dollar-weighted rate of return. Hint: Carefully prepare a chart of cash flows for the four dates corresponding to the turns of the year for January 1, 1999, to January 1, 2002. If your calculator cannot calculate internal rate of return, you will have to use trial and error. a. Suppose you forecast that the standard deviation of the market return will be 20% in the coming year. If the measure of risk aversion in equation 5.6 is A 4, what would be a reasonable guess for the expected market risk premium? b. What value of A is consistent with a risk premium of 9%? c. What will happen to the risk premium if investors become more risk tolerant? Using the historical risk premiums as your guide, what is your estimate of the expected annual HPR on the S&P 500 stock portfolio if the current risk-free interest rate is 5%? What has been the historical average real rate of return on stocks, Treasury bonds, and Treasury notes? Consider a risky portfolio. The end-of-year cash flow derived from the portfolio will be either $50,000 or $150,000, with equal probabilities of 0.5. The alternative riskless investment in T-bills pays 5%.

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a. If you require a risk premium of 10%, how much will you be willing to pay for the portfolio? b. Suppose the portfolio can be purchased for the amount you found in (a). What will the expected rate of return on the portfolio be? c. Now suppose you require a risk premium of 15%. What is the price you will be willing to pay now? d. Comparing your answers to (a) and (c), what do you conclude about the relationship between the required risk premium on a portfolio and the price at which the portfolio will sell? For problems 19–23, assume that you manage a risky portfolio with an expected rate of return of 17% and a standard deviation of 27%. The T-bill rate is 7%. 19. a. Your client chooses to invest 70% of a portfolio in your fund and 30% in a T-bill money market fund. What is the expected return and standard deviation of your client’s portfolio? b. Suppose your risky portfolio includes the following investments in the given proportions:

20.

21.

22.

23.

27% 33% 40%

What are the investment proportions of your client’s overall portfolio, including the position in T-bills? c. What is the reward-to-variability ratio (S) of your risky portfolio and your client’s overall portfolio? d. Draw the CAL of your portfolio on an expected return/standard deviation diagram. What is the slope of the CAL? Show the position of your client on your fund’s CAL. Suppose the same client in problem 19 decides to invest in your risky portfolio a proportion (y) of his total investment budget so that his overall portfolio will have an expected rate of return of 15%. a. What is the proportion y? b. What are your client’s investment proportions in your three stocks and the T-bill fund? c. What is the standard deviation of the rate of return on your client’s portfolio? Suppose the same client in problem 19 prefers to invest in your portfolio a proportion (y) that maximizes the expected return on the overall portfolio subject to the constraint that the overall portfolio’s standard deviation will not exceed 20%. a. What is the investment proportion, y? b. What is the expected rate of return on the overall portfolio? You estimate that a passive portfolio invested to mimic the S&P 500 stock index yields an expected rate of return of 13% with a standard deviation of 25%. Draw the CML and your fund’s CAL on an expected return/standard deviation diagram. a. What is the slope of the CML? b. Characterize in one short paragraph the advantage of your fund over the passive fund. Your client (see problem 19) wonders whether to switch the 70% that is invested in your fund to the passive portfolio. a. Explain to your client the disadvantage of the switch.

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Stock A Stock B Stock C

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b. Show your client the maximum fee you could charge (as a percent of the investment in your fund deducted at the end of the year) that would still leave him at least as well off investing in your fund as in the passive one. (Hint: The fee will lower the slope of your client’s CAL by reducing the expected return net of the fee.) 24. What do you think would happen to the expected return on stocks if investors perceived an increase in the volatility of stocks? 25. The change from a straight to a kinked capital allocation line is a result of the: a. Reward-to-variability ratio increasing. b. Borrowing rate exceeding the lending rate. c. Investor’s risk tolerance decreasing. d. Increase in the portfolio proportion of the risk-free asset. 26. You manage an equity fund with an expected risk premium of 10% and an expected standard deviation of 14%. The rate on Treasury bills is 6%. Your client chooses to invest $60,000 of her portfolio in your equity fund and $40,000 in a T-bill money market fund. What is the expected return and standard deviation of return on your client’s portfolio? Expected Return

a. b. c. d.

8.4% 8.4 12.0 12.0

Standard Deviation of Return 8.4% 14.0 8.4 14.0

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27. What is the reward-to-variability ratio for the equity fund in problem 26? a. .71 b. 1.00 c. 1.19 d. 1.91 For problems 28–30, download Table 5.3: Rates of return, 1926–2001, from www.mhhe.com/ blkm. 28. Calculate the same subperiod means and standard deviations for small stocks as Table 5.5 of the text provides for large stocks. a. Do small stocks provide better reward-to-variability ratios than large stocks? b. Do small stocks show a similar declining trend in standard deviation as Table 5.5 documents for large stocks? 29. Convert the nominal returns on both large and small stocks to real rates. Reproduce Table 5.5 using real rates instead of excess returns. Compare the results to those of Table 5.5. 30. Repeat problem 29 for small stocks and compare with the results for nominal rates.

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WEBMA STER Inflation and Interest Rates The Federal Reserve Bank of St. Louis has several sources of information available on interest rates and economic conditions. One publication called Monetary Trends contains graphs and tabular information relevant to assess conditions in the capital markets. Go to the most recent edition of Monetary Trends at http://www.stls.frb.org/ docs/publications/mt/mt.pdf and answer the following questions: 1.

What is the current level of three-month and long-term Treasury yields?

2.

Have nominal interest rates increased, decreased, or remained the same over the last three months?

3.

Have real interest rates increased, decreased, or remained the same over the last two years?

4.

Examine the information comparing recent U.S. inflation and long-term interest rates with the inflation and long-term interest rate experience of Japan. Are the results consistent with theory?

1. a. The arithmetic average is (2 8 4)/3 2% per month. b. The time-weighted (geometric) average is [(1 .02) (1 .08) (1 .04)]1/3 .0188 1.88% per month c. We compute the dollar-weighted average (IRR) from the cash flow sequence (in $ millions):

SOLUTIONS TO

> > >

168

Show how covariance and correlation affect the power of diversification to reduce portfolio risk. Construct efficient portfolios. Calculate the composition of the optimal risky portfolio. Use factor models to analyze the risk characteristics of securities and portfolios.

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Related Websites http://finance.yahoo.com http://moneycentral.msn.com/investor These sites can be used to find historical price information for estimating returns, standard deviation of returns, and covariance of returns for individual securities.

http://www.financialengines.com This site provides risk measures that can be used to compare individual stocks to an average hypothetical portfolio.

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The risk measure is based on the concept of value at risk and includes some capabilities of stress testing.

http://aida.econ.yale.edu/~shiller/data.htm Professor Shiller provides historical data used in his applications in Irrational Exuberance. The site also has links to other data sites.

http://www.mhhe.com/edumarketinsight The Education Version of Market Insight contains information on monthly, weekly, and daily returns. You can use these data in estimating correlation coefficients and covariance to find optimal portfolios.

http://www.portfolioscience.com Here you’ll find historical information to calculate potential losses on individual securities or portfolios.

n this chapter we describe how investors can construct the best possible risky portfolio. The key concept is efficient diversification. The notion of diversification is age-old. The adage “don’t put all your eggs in one basket” obviously predates economic theory. However, a formal model showing how to make the most of the power of diversification was not devised until 1952, a feat for which Harry Markowitz eventually won the Nobel Prize in economics. This chapter is largely developed from his work, as well as from later insights that built on his work. We start with a bird’s-eye view of how diversification reduces the variability of portfolio returns. We then turn to the construction of optimal risky portfolios. We follow a top-down approach, starting with asset allocation across a small set of broad asset classes, such as stocks, bonds, and money market securities. Then we show how the principles of optimal asset allocation can easily be generalized to solve the problem of security selection among many risky assets. We discuss the efficient set of risky portfolios and show how it leads us to the best attainable capital allocation. Finally, we show how factor models of security returns can simplify the search for efficient portfolios and the interpretation of the risk characteristics of individual securities. An appendix examines the common fallacy that long-term investment horizons mitigate the impact of asset risk. We argue that the common belief in “time diversification” is in fact an illusion and is not real diversification.

I

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6.1

market risk, systematic risk, nondiversifiable risk Risk factors common to the whole economy.

F I G U R E 6.1

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DIVERSIFICATION AND PORTFOLIO RISK

Suppose you have in your risky portfolio only one stock, say, Dell Computer Corporation. What are the sources of risk affecting this “portfolio”? We can identify two broad sources of uncertainty. The first is the risk that has to do with general economic conditions, such as the business cycle, the inflation rate, interest rates, exchange rates, and so forth. None of these macroeconomic factors can be predicted with certainty, and all affect the rate of return Dell stock eventually will provide. Then you must add to these macro factors firm-specific influences, such as Dell’s success in research and development, its management style and philosophy, and so on. Firm-specific factors are those that affect Dell without noticeably affecting other firms. Now consider a naive diversification strategy, adding another security to the risky portfolio. If you invest half of your risky portfolio in ExxonMobil, leaving the other half in Dell, what happens to portfolio risk? Because the firm-specific influences on the two stocks differ (statistically speaking, the influences are independent), this strategy should reduce portfolio risk. For example, when oil prices fall, hurting ExxonMobil, computer prices might rise, helping Dell. The two effects are offsetting, which stabilizes portfolio return. But why stop at only two stocks? Diversifying into many more securities continues to reduce exposure to firm-specific factors, so portfolio volatility should continue to fall. Ultimately, however, even with a large number of risky securities in a portfolio, there is no way to avoid all risk. To the extent that virtually all securities are affected by common (risky) macroeconomic factors, we cannot eliminate our exposure to general economic risk, no matter how many stocks we hold. Figure 6.1 illustrates these concepts. When all risk is firm-specific, as in Figure 6.1A, diversification can reduce risk to low levels. With all risk sources independent, and with investment spread across many securities, exposure to any particular source of risk is negligible. This is just an application of the law of averages. The reduction of risk to very low levels because of independent risk sources is sometimes called the insurance principle. When common sources of risk affect all firms, however, even extensive diversification cannot eliminate risk. In Figure 6.1B, portfolio standard deviation falls as the number of securities increases, but it is not reduced to zero. The risk that remains even after diversification is called market risk, risk that is attributable to marketwide risk sources. Other names are systematic

σ

σ

Portfolio risk as a function of the number of stocks in the portfolio Unique risk

Market risk n A: Firm-specific risk only

n B: Market and unique risk

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risk or nondiversifiable risk. The risk that can be eliminated by diversification is called unique risk, firm-specific risk, nonsystematic risk, or diversifiable risk. This analysis is borne out by empirical studies. Figure 6.2 shows the effect of portfolio diversification, using data on NYSE stocks. The figure shows the average standard deviations of equally weighted portfolios constructed by selecting stocks at random as a function of the number of stocks in the portfolio. On average, portfolio risk does fall with diversification, but the power of diversification to reduce risk is limited by common sources of risk. The box on the following page highlights the dangers of neglecting diversification and points out that such neglect is widespread.

unique risk, firm-specific risk, nonsystematic risk, diversifiable risk

6

6.2

Risk that can be eliminated by diversification.

ASSET ALLOCATION WITH TWO RISKY ASSETS

In the last chapter we examined the simplest asset allocation decision, that involving the choice of how much of the portfolio to place in risk-free money market securities versus in a risky portfolio. We simply assumed that the risky portfolio comprised a stock and a bond fund in given proportions. Of course, investors need to decide on the proportion of their portfolios to allocate to the stock versus the bond market. This, too, is an asset allocation decision. As the box on page 173 emphasizes, most investment professionals recognize that the asset allocation decision must take precedence over the choice of particular stocks or mutual funds. We examined capital allocation between risky and risk-free assets in the last chapter. We turn now to asset allocation between two risky assets, which we will continue to assume are two mutual funds, one a bond fund and the other a stock fund. After we understand the properties of portfolios formed by mixing two risky assets, we will reintroduce the choice of the third, risk-free portfolio. This will allow us to complete the basic problem of asset allocation across the three key asset classes: stocks, bonds, and risk-free money market securities. Once you understand this case, it will be easy to see how portfolios of many risky securities might best be constructed.

Covariance and Correlation

100%

50 40

75%

30 50% 40%

20 10 0

Risk compared to a one-stock portfolio

Average portfolio standard deviation (%)

Because we now envision forming a risky portfolio from two risky assets, we need to understand how the uncertainties of asset returns interact. It turns out that the key determinant of portfolio risk is the extent to which the returns on the two assets tend to vary either in tandem

0

2 4 6 8 10 12 14 16 18 20 Number of stocks in portfolio

0 100 200 300 400 500 600 700 800 9001,000

F I G U R E 6.2 Portfolio risk decreases as diversification increases Source: Meir Statman, “How Many Stocks Make a Diversified Portfolio?” Journal of Financial and Quantitative Analysis 22, September 1987.

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Dangers of Not Diversifying Hit Investors Enron, Tech Bubble Are Wake-Up Calls Mutual-fund firms and financial planners have droned on about the topic for years. But suddenly, it’s at the epicenter of lawsuits, congressional hearings and presidential reform proposals. Diversification—that most basic of investing principles—has returned with a vengeance. During the late 1990s, many people scoffed at being diversified, because the idea of investing in a mix of stocks, bonds and other financial assets meant missing out on some of the soaring gains of tech stocks. But with the collapse of the tech bubble and now the fall of Enron Corp. wiping out the 401(k) holdings of many current and retired Enron employees, the dangers of overloading a portfolio with one stock—or even with a group of similar stocks—has hit home for many investors. The pitfalls of holding too much of one company’s stock aren’t limited to Enron. Since the beginning of 2000, nearly one of every five U.S. stocks has fallen by two-thirds or more, while only 1% of diversified stock mutual funds have swooned as much, according to research firm Morningstar Inc. While not immune from losses, mutual funds tend to weather storms better, because they spread their bets over dozens or hundreds of companies. “Most

people think their company is safer than a stock mutual fund, when the data show that the opposite is true,” says John Rekenthaler, president of Morningstar’s online-advice unit. While some companies will match employees’ 401(k) contributions exclusively in company stock, investors can almost always diversify a large portion of their 401(k)—namely, the part they contribute themselves. Half or more of the assets in a typical 401(k) portfolio are contributed by employees themselves, so diversifying this portion of their portfolio can make a significant difference in reducing overall investing risk. But in picking an investing alternative to buying your employer’s stock, some choices are more useful than others. For example, investors should take into account the type of company they work for when diversifying. Workers at small technology companies—the type of stock often held by growth funds—might find better diversification with a fund focusing on large undervalued companies. Conversely, an auto-company worker might want to put more money in funds that specialize in smaller companies that are less tied to economic cycles.

SOURCE: Abridged from Aaron Luccheth and Theo Francis, “Dangers of Not Diversifying Hit Investors,” The Wall Street Journal, February 15, 2002.

or in opposition. Portfolio risk depends on the correlation between the returns of the assets in the portfolio. We can see why using a simple scenario analysis. Suppose there are three possible scenarios for the economy: a recession, normal growth, and a boom. The performance of stock funds tends to follow the performance of the broad economy. So suppose that in a recession, the stock fund will have a rate of return of 11%, in a normal period it will have a rate of return of 13%, and in a boom period it will have a rate of return of 27%. In contrast, bond funds often do better when the economy is weak. This is because interest rates fall in a recession, which means that bond prices rise. Suppose that a bond fund will provide a rate of return of 16% in a recession, 6% in a normal period, and 4% in a boom. These assumptions and the probabilities of each scenario are summarized in Spreadsheet 6.1. The expected return on each fund equals the probability-weighted average of the outcomes in the three scenarios. The last row of Spreadsheet 6.1 shows that the expected return of the stock fund is 10%, and that of the bond fund is 6%. As we discussed in the last chapter, the variance is the probability-weighted average across all scenarios of the squared deviation between the actual return of the fund and its expected return; the standard deviation is the square root of the variance. These values are computed in Spreadsheet 6.2. What about the risk and return characteristics of a portfolio made up from the stock and bond funds? The portfolio return is the weighted average of the returns on each fund with weights equal to the proportion of the portfolio invested in each fund. Suppose we form a 172

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First Take Care of Asset-Allocation Needs If you want to build a top-performing mutual-fund portfolio, you should start by hunting for top-performing funds, right? Wrong. Too many investors gamely set out to find top-notch funds without first settling on an overall portfolio strategy. Result? These investors wind up with a mishmash of funds that don’t add up to a decent portfolio. . . . . . . So what should you do? With more than 11,000 stock, bond, and money-market funds to choose from, you couldn’t possibly analyze all the funds available. Instead, to make sense of the bewildering array of funds available, you should start by deciding what basic mix of stock, bond, and money-market funds you want to hold. This is what experts call your “asset allocation.” This asset allocation has a major influence on your portfolio’s performance. The more you have in stocks, the higher your likely long-run return. But with the higher potential return from stocks come sharper short-term swings in a portfolio’s value. As a result, you may want to include a healthy dose of bond and money-market funds, especially if you are a conservative investor or you will need to tap your portfolio for cash in the near future.

Once you have settled on your asset-allocation mix, decide what sort of stock, bond, and money-market funds you want to own. This is particularly critical for the stock portion of your portfolio. One way to damp the price swings in your stock portfolio is to spread your money among large, small, and foreign stocks. You could diversify even further by making sure that, when investing in U.S. large- and small-company stocks, you own both growth stocks with rapidly increasing sales or earnings and also beaten-down value stocks that are inexpensive compared with corporate assets or earnings. Similarly, among foreign stocks, you could get additional diversification by investing in both developed foreign markets such as France, Germany, and Japan, and also emerging markets like Argentina, Brazil, and Malaysia.

Source: Abridged from Jonathan Clements, “It Pays for You to Take Care of Asset-Allocation Needs before Latching onto Fads,” The Wall Street Journal, April 6, 1998. Reprinted by permission of Dow Jones & Company, Inc. via Copyright Clearance Center, Inc. © 1998 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

portfolio with 60% invested in the stock fund and 40% in the bond fund. Then the portfolio return in each scenario is the weighted average of the returns on the two funds. For example Portfolio return in recession 0.60 (11%) 0.40 16% 0.20% which appears in cell C5 of Spreadsheet 6.3. Spreadsheet 6.3 shows the rate of return of the portfolio in each scenario, as well as the portfolio’s expected return, variance, and standard deviation. Notice that while the portfolio’s expected return is just the average of the expected return of the two assets, the standard deviation is actually less than that of either asset.

S P R E A D S H E E T 6.1 Capital market expectations for the stock and bond funds

A

B

1 2 3 4 5 6

Scenario Probability Recession 0.3 Normal 0.4 Boom 0.3 Expected or Mean Return:

C

D

Stock Fund Rate of Return Col. B Col. C 11 3.3 13 5.2 27 8.1 SUM: 10.0

E

F

Bond Fund Rate of Return Col. B Col. E 16 4.8 6 2.4 4 1.2 SUM: 6.0

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S P R E A D S H E E T 6.2 Variance of returns

A 1 2 3 4 5 6 7 8 9 10

B

C

D

E

F

Stock Fund Deviation Rate from Column B of Expected Squared x Prob. Return Return Deviation Column E 0.3 -11 -21 441 132.3 0.4 13 3 9 3.6 0.3 27 17 289 86.7 Variance = SUM 222.6 Standard deviation = SQRT(Variance) 14.92

Scenario Recession Normal Boom

G

Rate of Return 16 6 -4

H

I

J

Bond Fund Deviation from Column B Expected Squared x Return Deviation Column I 10 100 30 0 0 0 -10 100 30 Sum: 60 Sum: 7.75

S P R E A D S H E E T 6.3 Performance of the portfolio of stock and bond funds

A 1 2 3 4 5 6 7 8 9

Scenario Recession Normal Boom

B

C

D

E

F

G

Portfolio of 60% in stocks and 40% in bonds Rate Column B Deviation from Column B of x Expected Squared x Probability Return Column C Return Deviation Column F 0.3 -0.2 -0.06 -8.60 73.96 22.188 0.4 10.2 4.08 1.80 3.24 1.296 0.3 14.6 4.38 6.20 38.44 11.532 Expected return: 8.40 Variance: 35.016 Standard deviation: 5.92

The low risk of the portfolio is due to the inverse relationship between the performance of the two funds. In a recession, stocks fare poorly, but this is offset by the good performance of the bond fund. Conversely, in a boom scenario, bonds fall, but stocks do well. Therefore, the portfolio of the two risky assets is less risky than either asset individually. Portfolio risk is reduced most when the returns of the two assets most reliably offset each other. The natural question investors should ask, therefore, is how one can measure the tendency of the returns on two assets to vary either in tandem or in opposition to each other. The statistics that provide this measure are the covariance and the correlation coefficient. The covariance is calculated in a manner similar to the variance. Instead of measuring the typical difference of an asset return from its expected value, however, we wish to measure the extent to which the variation in the returns on the two assets tend to reinforce or offset each other. We start in Spreadsheet 6.4 with the deviation of the return on each fund from its expected or mean value. For each scenario, we multiply the deviation of the stock fund return from its mean by the deviation of the bond fund return from its mean. The product will be positive if both asset returns exceed their respective means in that scenario or if both fall short of their respective means. The product will be negative if one asset exceeds its mean return, while the other falls short of its mean return. For example, Spreadsheet 6.4 shows that the stock fund return in the recession falls short of its expected value by 21%, while the bond fund return exceeds its mean by 10%. Therefore, the product of the two deviations in the recession is 21 10 210, as reported in column E. The product of deviations is negative if one asset performs well when the other is performing poorly. It is positive if both assets perform well or poorly in the same scenarios.

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S P R E A D S H E E T 6.4 Covariance between the returns of the stock and bond funds

A 1 2 3 4 5 6 7

B

C

D

E

F

Deviation from Mean Return Covariance Scenario Probability Stock Fund Bond Fund Product of Dev Col. B Col. E Recession 0.3 21 10 210 63 Normal 0.4 3 0 0 0 Boom 0.3 17 10 170 51 Covariance: SUM: 114 Correlation coefficient = Covariance/(StdDev(stocks)*StdDev(bonds)): 0.99

If we compute the probability-weighted average of the products across all scenarios, we obtain a measure of the average tendency of the asset returns to vary in tandem. Since this is a measure of the extent to which the returns tend to vary with each other, that is, to co-vary, it is called the covariance. The covariance of the stock and bond funds is computed in the next-tolast line of Spreadsheet 6.4. The negative value for the covariance indicates that the two assets vary inversely, that is, when one asset performs well, the other tends to perform poorly. Unfortunately, it is difficult to interpret the magnitude of the covariance. For instance, does the covariance of 114 indicate that the inverse relationship between the returns on stock and bond funds is strong or weak? It’s hard to say. An easier statistic to interpret is the correlation coefficient, which is simply the covariance divided by the product of the standard deviations of the returns on each fund. We denote the correlation coefficient by the Greek letter rho, . Correlation coefficient

Covariance 114 .99 stock bond 14.92 7.75

Correlations can range from values of 1 to 1. Values of 1 indicate perfect negative correlation, that is, the strongest possible tendency for two returns to vary inversely. Values of 1 indicate perfect positive correlation. Correlations of zero indicate that the returns on the two assets are unrelated to each other. The correlation coefficient of 0.99 confirms the overwhelming tendency of the returns on the stock and bond funds to vary inversely in this scenario analysis. We are now in a position to derive the risk and return features of portfolios of risky assets. 1. Suppose the rates of return of the bond portfolio in the three scenarios of Spreadsheet 6.4 are 10% in a recession, 7% in a normal period, and 2% in a boom. The stock returns in the three scenarios are 12% (recession), 10% (normal), and 28% (boom). What are the covariance and correlation coefficient between the rates of return on the two portfolios?

Using Historical Data We’ve seen that portfolio risk and return depend on the means and variances of the component securities, as well as on the covariance between their returns. One way to obtain these inputs is a scenario analysis as in Spreadsheets 6.1–6.4. As we noted in Chapter 5, however, a common alternative approach to produce these inputs is to make use of historical data. In this approach, we use realized returns to estimate mean returns and volatility as well as the tendency for security returns to co-vary. The estimate of the mean return for each security is its average value in the sample period; the estimate of variance is the average value of the squared deviations around the sample average; the estimate of the covariance is the average

2. Suppose that for some reason you are required to invest 50% of your portfolio in bonds and 50% in stocks. a. If the standard deviation of your portfolio is 15%, what must be the correlation coefficient between stock and bond returns? b. What is the expected rate of return on your portfolio? c. Now suppose that the correlation between stock and bond returns is 0.22 but that you are free to choose whatever portfolio proportions you desire. Are you likely to be better or worse off than you were in part (a)?

Let’s return to the data for ABC and XYZ in Example 6.1. Using the spreadsheet estimates of the means and standard deviations obtained from the AVERAGE and STDEV functions, and the estimate of the correlation coefficient we obtained in that example, we can compute the risk-return trade-off for various portfolios formed from ABC and XYZ. Columns E and F in the lower half of the spreadsheet on the following page are calculated from Equations 6.2 and 6.3 respectively, and show the risk-return opportunities. These calculations use the estimates of the stocks’ means in cells B16 and C16, the standard deviations in cells B17 and C17, and the correlation coefficient in cell F10. Examination of column E shows that the portfolio mean starts at XYZ’s mean of 11.97% and moves toward ABC’s mean as we increase the weight of ABC and correspondingly reduce that of XYZ. Examination of the standard deviation in column F shows that diversification reduces the standard deviation until the proportion in ABC increases above 30%; thereafter, standard deviation increases. Hence, the minimum-variance portfolio uses weights of approximately 30% in ABC and 70% in XYZ. The exact proportion in ABC in the minimum-variance portfolio can be computed from the formula shown in Spreadsheet 6.6. Note, however, that achieving a minimum-variance portfolio is not a compelling goal. Investors may well be willing to take on more risk in order to increase expected return. The investment opportunity set offered by stocks ABC and XYZ may be found by graphing the expected return–standard deviation pairs in columns E and F.

6.3 EXAMPLE Using Historical Data to Estimate the Investment Opportunity Set

Concept CHECK

>

3. The following tables present returns on various pairs of stocks in several periods. In part A, we show you a scatter diagram of the returns on the first pair of stocks. Draw (or prepare in Excel) similar scatter diagrams for cases B through E. Match up the diagrams (A–E) to the following list of correlation coefficients by choosing the correlation that best describes the relationship between the returns on the two stocks: ⴝ ⴚ1, 0, 0.2, 0.5, 1.0. (continued) The proportion in bonds that will drive the standard deviation to zero when 1 is:

2

wB

S B S

Compare this formula to the formula in footnote 1 for the variance-minimizing proportions when 0.

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Spreadsheet for Example 6.3

(concluded) B.

% Return

C.

Stock 1 Stock 2 1 2 3 4 5

6.3

% Return Stock 1 Stock 2

1 2 3 4 5

1 2 3 4 5

5 4 3 2 1

D.

% Return

E.

Stock 1 Stock 2 5 1 4 2 3

% Return Stock 1 Stock 2

5 3 3 0 5

5 1 4 2 3

4 3 1 0 5

THE OPTIMAL RISKY PORTFOLIO WITH A RISK-FREE ASSET

Now we can expand the asset allocation problem to include a risk-free asset. Let us continue to use the input data from the bottom of Spreadsheet 6.5, but now assume a realistic correlation coefficient between stocks and bonds of 0.20. Suppose then that we are still confined to the risky bond and stock funds, but now can also invest in risk-free T-bills yielding 5%. Figure 6.5 shows the opportunity set generated from the bond and stock funds. This is the same opportunity set as graphed in Figure 6.4 with BS 0.20. Two possible capital allocation lines (CALs) are drawn from the risk-free rate (rf 5%) to two feasible portfolios. The first possible CAL is drawn through the variance-minimizing portfolio (A), which invests 87.06% in bonds and 12.94% in stocks. Portfolio A’s expected return is 6.52% and its standard deviation is 11.54%. With a T-bill rate (rf) of 5%, the reward-tovariability ratio of portfolio A (which is also the slope of the CAL that combines T-bills with portfolio A) is SA

F I G U R E 6.5

12 11 Expected return (%)

The opportunity set using bonds and stocks and two capital allocation lines

E(rA) rf 6.52 5 0.13 A 11.54

10 Stocks 9 8 7

B

CALB CALA

A Bonds

6 5 4 0

5

10

15 20 25 Standard deviation (%)

30

35

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Now consider the CAL that uses portfolio B instead of A. Portfolio B invests 80% in bonds and 20% in stocks, providing an expected return of 6.80% with a standard deviation of 11.68%. Thus, the reward-to-variability ratio of any portfolio on the CAL of B is 6.80 5 .15 11.68

SB

This is higher than the reward-to-variability ratio of the CAL of the variance-minimizing portfolio A. The difference in the reward-to-variability ratios is SB SA 0.02. This implies that portfolio B provides 2 extra basis points (0.02%) of expected return for every percentage point increase in standard deviation. The higher reward-to-variability ratio of portfolio B means that its capital allocation line is steeper than that of A. Therefore, CALB plots above CALA in Figure 6.5. In other words, combinations of portfolio B and the risk-free asset provide a higher expected return for any level of risk (standard deviation) than combinations of portfolio A and the risk-free asset. Therefore, all risk-averse investors would prefer to form their complete portfolio using the risk-free asset with portfolio B rather than with portfolio A. In this sense, portfolio B dominates A. But why stop at portfolio B? We can continue to ratchet the CAL upward until it reaches the ultimate point of tangency with the investment opportunity set. This must yield the CAL with the highest feasible reward-to-variability ratio. Therefore, the tangency portfolio (O) in Figure 6.6 is the optimal risky portfolio to mix with T-bills, which may be defined as the risky portfolio resulting in the highest possible CAL. We can read the expected return and standard deviation of portfolio O (for “optimal”) off the graph in Figure 6.6 as E(rO) 8.68% O 17.97% which can be identified as the portfolio that invests 32.99% in bonds and 67.01% in stocks.3 We can obtain a numerical solution to this problem using a computer program.

The optimal capital allocation line with bonds, stocks, and T-bills

11 Expected return (%)

The best combination of risky assets to be mixed with safe assets to form the complete portfolio.

F I G U R E 6.6

12 Stocks

10 E(ro) 8.68%

9

O

8 7 6

Bonds

5

σo 17.97%

4 0

5

10

15

20

25

30

Standard deviation (%)

3

The proportion of portfolio O invested in bonds is: wB

optimal risky portfolio

[E(rB) rf]S2 [E(rS) rf]B S BS [E(rB) rf]S2 [E(rS) rf]B2 [E(rB) rf E(rS) rf]B S BS

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F I G U R E 6.7

E(rP)

The complete portfolio CALo 8.68%

O, optimal risky portfolio

7.02% 5%

C, complete portfolio

9.88%

σP

17.97%

The CAL with our optimal portfolio has a slope of SO

8.68 5 .20 17.97

which is the reward-to-variability ratio of portfolio O. This slope exceeds the slope of any other feasible portfolio, as it must if it is to be the slope of the best feasible CAL. In the last chapter we saw that the preferred complete portfolio formed from a risky portfolio and a risk-free asset depends on the investor’s risk aversion. More risk-averse investors will prefer low-risk portfolios despite the lower expected return, while more risk-tolerant investors will choose higher-risk, higher-return portfolios. Both investors, however, will choose portfolio O as their risky portfolio since that portfolio results in the highest return per unit of risk, that is, the steepest capital allocation line. Investors will differ only in their allocation of investment funds between portfolio O and the risk-free asset. Figure 6.7 shows one possible choice for the preferred complete portfolio, C. The investor places 55% of wealth in portfolio O and 45% in Treasury bills. The rate of return and volatility of the portfolio are E(rC) 5 0.55 (8.68 5) 7.02% C 0.55 17.97 9.88% In turn, we found above that portfolio O is formed by mixing the bond fund and stock fund with weights of 32.99% and 67.01%. Therefore, the overall asset allocation of the complete portfolio is as follows: Weight in risk-free asset Weight in bond fund Weight in stock fund Total

45.00% 0.3299 55% 18.14 0.6701 55% 36.86 100.00%

Figure 6.8 depicts the overall asset allocation. The allocation reflects considerations of both efficient diversification (the construction of the optimal risky portfolio, O) and risk aversion (the allocation of funds between the risk-free asset and the risky portfolio O to form the complete portfolio, C).

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F I G U R E 6.8 The composition of the complete portfolio: The solution to the asset allocation problem

Bonds 18.14% T-bills 45% Stocks 36.86%

Portfolio O 55%

4. A universe of securities includes a risky stock (X), a stock index fund (M), and T-bills. The data for the universe are:

X M T-bills

Expected Return

Standard Deviation

15% 10 5

50% 20 0

The correlation coefficient between X and M is ⴚ0.2. a. Draw the opportunity set of securities X and M. b. Find the optimal risky portfolio (O) and its expected return and standard deviation. c. Find the slope of the CAL generated by T-bills and portfolio O. d. Suppose an investor places 2/9 (i.e., 22.22%) of the complete portfolio in the risky portfolio O and the remainder in T-bills. Calculate the composition of the complete portfolio.

6.4

EFFICIENT DIVERSIFICATION WITH MANY RISKY ASSETS

We can extend the two-risky-assets portfolio construction methodology to cover the case of many risky assets and a risk-free asset. First, we offer an overview. As in the two-risky-assets example, the problem has three separate steps. To begin, we identify the best possible or most efficient risk-return combinations available from the universe of risky assets. Next we determine the optimal portfolio of risky assets by finding the portfolio that supports the steepest CAL. Finally, we choose an appropriate complete portfolio based on the investor’s risk aversion by mixing the risk-free asset with the optimal risky portfolio.

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Two-Security Portfolio

The Excel model “Two-Security Portfolio” is based on the asset allocation problem between stocks and bonds that appears in this chapter. You can change correlations, mean returns, and standard deviation of return for any two securities or, as it is used in the text example, any two portfolios. All of the concepts that are covered in this section can be explored using the model. You can learn more about this spreadsheet model by using the interactive version available on our website at www.mhhe.com/bkm.

A 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

B

C

Asset Allocation Analysis: Risk and Return Expected Standard Return Deviation Bonds 6.00% 12.00% Stocks 10.00% 25.00% T-Bill 5.00% 0.00%

Weight Bonds 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

Weight Stocks 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Minimum Variance Portfolio Weight Bonds Weight Stocks Return Risk CAL(MV)

D

Corr. Coeff s,b 0

E

F

Covariance 0

Expected Standard Reward to Return Deviation Variability 6.0000% 12.0000% 0.08333 6.4000% 11.0856% 0.12629 6.8000% 10.8240% 0.16630 7.2000% 11.2610% 0.19536 7.6000% 12.3223% 0.21100 8.0000% 13.8654% 0.21637 8.4000% 15.7493% 0.21588 8.8000% 17.8664% 0.21269 9.2000% 20.1435% 0.20850 9.6000% 22.5320% 0.20415 10.0000% 25.0000% 0.20000 Short Sales No Short Allowed Sales 0.81274 0.81274 0.18726 0.18726 6.7490% 6.7490% 10.8183% 10.8183%

The Efficient Frontier of Risky Assets To get a sense of how additional risky assets can improve the investor’s investment opportunities, look at Figure 6.9. Points A, B, and C represent the expected returns and standard deviations of three stocks. The curve passing through A and B shows the risk-return combinations of all the portfolios that can be formed by combining those two stocks. Similarly, the curve passing through B and C shows all the portfolios that can be formed from those two stocks. Now observe point E on the AB curve and point F on the BC curve. These points represent two

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35 30 Expected return (%)

C F

25 20 B 15 E 10

A

5 0 0

10

20

30

40

Standard deviation (%)

F I G U R E 6.9 Portfolios constructed with three stocks (A, B, and C)

portfolios chosen from the set of AB combinations and BC combinations. The curve that passes through E and F in turn represents all the portfolios that can be constructed from portfolios E and F. Since E and F are themselves constructed from A, B, and C, this curve also may be viewed as depicting some of the portfolios that can be constructed from these three securities. Notice that curve EF extends the investment opportunity set to the northwest, which is the desired direction. Now we can continue to take other points (each representing portfolios) from these three curves and further combine them into new portfolios, thus shifting the opportunity set even farther to the northwest. You can see that this process would work even better with more stocks. Moreover, the efficient frontier, the boundary or “envelope” of all the curves thus developed, will lie quite away from the individual stocks in the northwesterly direction, as shown in Figure 6.10. The analytical technique to derive the efficient frontier of risky assets was developed by Harry Markowitz at the University of Chicago in 1951 and ultimately earned him the Nobel Prize in economics. We will sketch his approach here. First, we determine the risk-return opportunity set. The aim is to construct the northwestern-most portfolios in terms of expected return and standard deviation from the universe of securities. The inputs are the expected returns and standard deviations of each asset in the universe, along with the correlation coefficients between each pair of assets. These data come from security analysis, to be discussed in Part Four. The graph that connects all the northwestern-most portfolios is called the efficient frontier of risky assets. It represents

efficient frontier Graph representing a set of portfolios that maximizes expected return at each level of portfolio risk.

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F I G U R E 6.10 The efficient frontier of risky assets and individual assets

Portfolio expected return E(rP)

Minimum variance portfolio

Efficient frontier of risky assets

Individual assets

σP Portfolio standard deviation

the set of portfolios that offers the highest possible expected rate of return for each level of portfolio standard deviation. These portfolios may be viewed as efficiently diversified. One such frontier is shown in Figure 6.10. Expected return-standard deviation combinations for any individual asset end up inside the efficient frontier, because single-asset portfolios are inefficient—they are not efficiently diversified. When we choose among portfolios on the efficient frontier, we can immediately discard portfolios below the minimum-variance portfolio. These are dominated by portfolios on the upper half of the frontier with equal risk but higher expected returns. Therefore, the real choice is among portfolios on the efficient frontier above the minimum-variance portfolio. Various constraints may preclude a particular investor from choosing portfolios on the efficient frontier, however. If an institution is prohibited by law from taking short positions in any asset, for example, the portfolio manager must add constraints to the computeroptimization program that rule out negative (short) positions. Short sale restrictions are only one possible constraint. Some clients may want to assure a minimum level of expected dividend yield. In this case, data input must include a set of expected dividend yields. The optimization program is made to include a constraint to ensure that the expected portfolio dividend yield will equal or exceed the desired level. Another common constraint forbids investments in companies engaged in “undesirable social activity.” In principle, portfolio managers can tailor an efficient frontier to meet any particular objective. Of course, satisfying constraints carries a price tag. An efficient frontier subject to a number of constraints will offer a lower reward-to-variability ratio than a less constrained one. Clients should be aware of this cost and may want to think twice about constraints that are not mandated by law. Deriving the efficient frontier may be quite difficult conceptually, but computing and graphing it with any number of assets and any set of constraints is quite straightforward. For a small number of assets, and in the absence of constraints beyond the obvious one that

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Efficient Frontier for Many Stocks

Excel spreadsheets can be used to construct an efficient frontier for a group of individual securities or a group of portfolios of securities. The Excel model “Efficient Portfolio” is built using a sample of actual returns on stocks that make up a part of the Dow Jones Industrial Average Index. The efficient frontier is graphed, similar to Figure 6.10, using various possible target returns. The model is built for eight securities and can be easily modified for any group of eight assets. You can learn more about this spreadsheet model by using the interactive version available on our website at www.mhhe.com/bkm.

A 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34

TKR SYM C GE HD INTC JNJ MRK SBC WMT

B

C

Return

D

E

F

G

H

I

S.D. 46.6 37.3 41.8 46.0 24.6 32.6 19.0 41.2

34.8 25.0 31.4 45.9 26.2 31.0 28.1 31.4 Correlation Matrix

C

GE

HD

C GE HD INTC JNJ MRK SBC WMT

1.00 0.54 0.26 0.26 0.35 0.29 0.25 0.40

0.54 1.00 0.58 0.26 0.29 0.20 0.34 0.52

C GE HD INTC JNJ MRK SBC WMT

C 1211.55 468.81 282.30 419.81 320.52 308.52 239.86 440.95

GE 468.81 627.47 451.99 299.86 189.64 158.28 240.96 409.29

INTC

0.35 0.29 -0.02 0.09 1.00 0.58 0.28 0.28

MRK 0.29 0.20 -0.12 0.11 0.58 1.00 0.37 0.12

SBC

0.26 0.26 -0.09 1.00 0.09 0.11 -0.05 -0.02

0.25 0.34 0.15 -0.05 0.28 0.37 1.00 0.16

0.40 0.52 0.58 -0.02 0.28 0.12 0.16 1.00

Covariance Matrix HD INTC 282.30 419.81 451.99 299.86 983.39 -133.54 -133.54 2106.34 -17.19 113.73 -117.25 151.78 133.28 -63.77 566.72 -34.46

JNJ 320.52 189.64 -17.19 113.73 686.88 473.15 203.37 229.77

MRK 308.52 158.28 -117.25 151.78 473.15 961.63 324.53 119.16

SBC 239.86 240.96 133.28 -63.77 203.37 324.53 790.22 140.90

WMT 440.95 409.29 566.72 -34.46 229.77 119.16 140.90 987.13

0.26 0.58 1.00 -0.09 -0.02 -0.12 0.15 0.58

JNJ

WMT

portfolio proportions must sum to 1.0, the efficient frontier can be computed and graphed with a spreadsheet program.

Choosing the Optimal Risky Portfolio The second step of the optimization plan involves the risk-free asset. Using the current riskfree rate, we search for the capital allocation line with the highest reward-to-variability ratio (the steepest slope), as shown in Figures 6.5 and 6.6.

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The CAL formed from the optimal risky portfolio (O) will be tangent to the efficient frontier of risky assets discussed above. This CAL dominates all alternative feasible lines (the dashed lines that are drawn through the frontier). Portfolio O, therefore, is the optimal risky portfolio.

The Preferred Complete Portfolio and the Separation Property

separation property The property that implies portfolio choice can be separated into two independent tasks: (1) determination of the optimal risky portfolio, which is a purely technical problem, and (2) the personal choice of the best mix of the risky portfolio and the risk-free asset.

Concept CHECK

>

factor model Statistical model to measure the firmspecific versus systematic risk of a stock’s rate of return.

Finally, in the third step, the investor chooses the appropriate mix between the optimal risky portfolio (O) and T-bills, exactly as in Figure 6.7. A portfolio manager will offer the same risky portfolio (O) to all clients, no matter what their degrees of risk aversion. Risk aversion comes into play only when clients select their desired point on the CAL. More risk-averse clients will invest more in the risk-free asset and less in the optimal risky portfolio O than less risk-averse clients, but both will use portfolio O as the optimal risky investment vehicle. This result is called a separation property, introduced by James Tobin (1958), the 1983 Nobel Laureate for economics: It implies that portfolio choice can be separated into two independent tasks. The first task, which includes steps one and two, determination of the optimal risky portfolio (O), is purely technical. Given the particular input data, the best risky portfolio is the same for all clients regardless of risk aversion. The second task, construction of the complete portfolio from bills and portfolio O, however, depends on personal preference. Here the client is the decision maker. Of course, the optimal risky portfolio for different clients may vary because of portfolio constraints such as dividend yield requirements, tax considerations, or other client preferences. Our analysis, though, suggests that a few portfolios may be sufficient to serve the demands of a wide range of investors. We see here the theoretical basis of the mutual fund industry. If the optimal portfolio is the same for all clients, professional management is more efficient and less costly. One management firm can serve a number of clients with relatively small incremental administrative costs. The (computerized) optimization technique is the easiest part of portfolio construction. If different managers use different input data to develop different efficient frontiers, they will offer different “optimal” portfolios. Therefore, the real arena of the competition among portfolio managers is in the sophisticated security analysis that underlies their choices. The rule of GIGO (garbage in–garbage out) applies fully to portfolio selection. If the quality of the security analysis is poor, a passive portfolio such as a market index fund can yield better results than an active portfolio tilted toward seemingly favorable securities. 5. Two portfolio managers work for competing investment management houses. Each employs security analysts to prepare input data for the construction of the optimal portfolio. When all is completed, the efficient frontier obtained by manager A dominates that of manager B in that A’s optimal risky portfolio lies northwest of B’s. Is the more attractive efficient frontier asserted by manager A evidence that she really employs better security analysts?

6.5

A SINGLE-FACTOR ASSET MARKET

We started this chapter with the distinction between systematic and firm-specific risk. Systematic risk is largely macroeconomic, affecting all securities, while firm-specific risk factors affect only one particular firm or, perhaps, its industry. Factor models are statistical models designed to estimate these two components of risk for a particular security or portfolio. The

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first to use a factor model to explain the benefits of diversification was another Nobel Prize winner, William S. Sharpe (1963). We will introduce his major work (the capital asset pricing model) in the next chapter. The popularity of factor models is due to their practicality. To construct the efficient frontier from a universe of 100 securities, we would need to estimate 100 expected returns, 100 variances, and 100 99/2 4,950 covariances. And a universe of 100 securities is actually quite small. A universe of 1,000 securities would require estimates of 1,000 999/2 499,500 covariances, as well as 1,000 expected returns and variances. We will see shortly that the assumption that one common factor is responsible for all the covariability of stock returns, with all other variability due to firm-specific factors, dramatically simplifies the analysis. Let us use Ri to denote the excess return on a security, that is, the rate of return in excess of the risk-free rate: Ri ri rf. Then we can express the distinction between macroeconomic and firm-specific factors by decomposing this excess return in some holding period into three components Ri E(Ri ) iM ei

(6.5)

In Equation 6.5, E(Ri) is the expected excess holding-period return (HPR) at the start of the holding period. The next two terms reflect the impact of two sources of uncertainty. M quantifies the market or macroeconomic surprises (with zero meaning that there is “no surprise”) during the holding period. i is the sensitivity of the security to the macroeconomic factor. Finally, ei is the impact of unanticipated firm-specific events. Both M and ei have zero expected values because each represents the impact of unanticipated events, which by definition must average out to zero. The beta ( i) denotes the responsiveness of security i to macroeconomic events; this sensitivity will be different for different securities. As an example of a factor model, suppose that the excess return on Dell stock is expected to be 9% in the coming holding period. However, on average, for every unanticipated increase of 1% in the vitality of the general economy, which we take as the macroeconomic factor M, Dell’s stock return will be enhanced by 1.2%. Dell’s is therefore 1.2. Finally, Dell is affected by firm-specific surprises as well. Therefore, we can write the realized excess return on Dell stock as follows RD 9% 1.2M ei If the economy outperforms expectations by 2%, then we would revise upward our expectations of Dell’s excess return by 1.2 2%, or 2.4%, resulting in a new expected excess return of 11.4%. Finally, the effects of Dell’s firm-specific news during the holding period must be added to arrive at the actual holding-period return on Dell stock. Equation 6.5 describes a factor model for stock returns. This is a simplification of reality; a more realistic decomposition of security returns would require more than one factor in Equation 6.5. We treat this issue in the next chapter, but for now, let us examine the singlefactor case.

Specification of a Single-Index Model of Security Returns A factor model description of security returns is of little use if we cannot specify a way to measure the factor that we say affects security returns. One reasonable approach is to use the rate of return on a broad index of securities, such as the S&P 500, as a proxy for the common macro factor. With this assumption, we can use the excess return on the market index, RM , to measure the direction of macro shocks in any period.

193

excess return Rate of return in excess of the risk-free rate.

beta The sensitivity of a security’s returns to the systematic or market factor.

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Part TWO Portfolio Theory

index model

The index model separates the realized rate of return on a security into macro (systematic) and micro (firm-specific) components much like Equation 6.5. The excess rate of return on each security is the sum of three components:

A model of stock returns using a market index such as the S&P 500 to represent common or systematic risk factors.

Symbol 1. The stock’s excess return if the market factor is neutral, that is, if the market’s excess return is zero. 2. The component of return due to movements in the overall market (as represented by the index RM); i is the security’s responsiveness to the market. 3. The component attributable to unexpected events that are relevant only to this security (firm-specific).

i

iRM ei

The excess return on the stock now can be stated as Ri i i RM ei

(6.6)

Equation 6.6 specifies two sources of security risk: market or systematic risk ( i RM), attributable to the security’s sensitivity (as measured by beta) to movements in the overall market, and firm-specific risk (ei ), which is the part of uncertainty independent of the market factor. Because the firm-specific component of the firm’s return is uncorrelated with the market return, we can write the variance of the excess return of the stock as4 Variance (Ri ) Variance (i i RM ei ) Variance ( i RM) Variance (ei ) 2i M2

2(ei )

Systematic risk Firm-specific risk

(6.7)

Therefore, the total variability of the rate of return of each security depends on two components: 1. The variance attributable to the uncertainty common to the entire market. This systematic risk is attributable to the uncertainty in RM . Notice that the systematic risk of each stock depends on both the volatility in RM (that is, M2 ) and the sensitivity of the stock to fluctuations in RM . That sensitivity is measured by i . 2. The variance attributable to firm-specific risk factors, the effects of which are measured by ei . This is the variance in the part of the stock’s return that is independent of market performance. This single-index model is convenient. It relates security returns to a market index that investors follow. Moreover, as we soon shall see, its usefulness goes beyond mere convenience.

Statistical and Graphical Representation of the Single-Index Model Equation 6.6, Ri i i RM ei , may be interpreted as a single-variable regression equation of Ri on the market excess return RM . The excess return on the security (Ri ) is the dependent variable that is to be explained by the regression. On the right-hand side of the equation are the intercept i; the regression (or slope) coefficient beta, i , multiplying the independent (or explanatory) variable RM; and the security residual (unexplained) return, ei . Notice that because i is a constant, it has no bearing on the variance of Ri .

4

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We can plot this regression relationship as in Figure 6.11, which shows a possible scatter diagram for Dell Computer Corporation’s excess return against the excess return of the market index. The horizontal axis of the scatter diagram measures the explanatory variable, here the market excess return, RM. The vertical axis measures the dependent variable, here Dell’s excess return, RD. Each point on the scatter diagram represents a sample pair of returns (RM, RD) that might be observed for a particular holding period. Point T, for instance, describes a holding period when the excess return was 17% on the market index and 27% on Dell. Regression analysis lets us use the sample of historical returns to estimate a relationship between the dependent variable and the explanatory variable. The regression line in Figure 6.11 is drawn so as to minimize the sum of all the squared deviations around it. Hence, we say the regression line “best fits” the data in the scatter diagram. The line is called the security characteristic line, or SCL. The regression intercept (D) is measured from the origin to the intersection of the regression line with the vertical axis. Any point on the vertical axis represents zero market excess return, so the intercept gives us the expected excess return on Dell during the sample period when market performance was neutral. The intercept in Figure 6.11 is about 4.5%. The slope of the regression line can be measured by dividing the rise of the line by its run. It also is expressed by the number multiplying the explanatory variable, which is called the regression coefficient or the slope coefficient or simply the beta. The regression beta is a natural measure of systematic risk since it measures the typical response of the security return to market fluctuations. The regression line does not represent the actual returns: that is, the points on the scatter diagram almost never lie on the regression line, although the actual returns are used to calculate the regression coefficients. Rather, the line represents average tendencies; it shows the effect of the index return on our expectation of RD. The algebraic representation of the regression line is E(RD RM) D D RM

195

security characteristic line Plot of a security’s excess return as a function of the excess return of the market.

(6.8)

which reads: The expectation of RD given a value of RM equals the intercept plus the slope coefficient times the given value of RM .

Dell’s excess return (%) RD 30

F I G U R E 6.11 Scatter diagram for Dell

T

20 10 αD

RM 10

20

30

40

Market excess return (%)

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Because the regression line represents expectations, and because these expectations may not be realized in any or all of the actual returns (as the scatter diagram shows), the actual security returns also include a residual, the firm-specific surprise, ei. This surprise (at point T, for example) is measured by the vertical distance between the point of the scatter diagram and the regression line. For example, the expected return on Dell, given a market return of 17%, would have been 4.5% 1.4 17% 28.3%. The actual return was only 27%, so point T falls below the regression line by 1.3%. Equation 6.7 shows that the greater the beta of the security, that is, the greater the slope of the regression, the greater the security’s systematic risk ( 2D M2 ), as well as its total variance (D2 ). The average security has a slope coefficient (beta) of 1.0: Because the market is composed of all securities, the typical response to a market movement must be one for one. An “aggressive” investment will have a beta higher than 1.0; that is, the security has aboveaverage market risk.5 In Figure 6.11, Dell’s beta is 1.4. Conversely, securities with betas lower than 1.0 are called defensive. A security may have a negative beta. Its regression line will then slope downward, meaning that, for more favorable macro events (higher RM), we would expect a lower return, and vice versa. The latter means that when the macro economy goes bad (negative RM) and securities with positive beta are expected to have negative excess returns, the negative-beta security will shine. The result is that a negative-beta security has negative systematic risk, that is, it provides a hedge against systematic risk. The dispersion of the scatter of actual returns about the regression line is determined by the residual variance 2(eD), which measures the effects of firm-specific events. The magnitude of firm-specific risk varies across securities. One way to measure the relative importance of systematic risk is to measure the ratio of systematic variance to total variance. 2

Systematic (or explained) variance Total variance

2D 2M

2D 2M 2D

2D 2M 2(eD)

(6.9)

where is the correlation coefficient between RD and RM . Its square measures the ratio of explained variance to total variance, that is, the proportion of total variance that can be attributed to market fluctuations. But if beta is negative, so is the correlation coefficient, an indication that the explanatory and dependent variables are expected to move in opposite directions. At the extreme, when the correlation coefficient is either 1.0 or 1.0, the security return is fully explained by the market return, that is, there are no firm-specific effects. All the points of the scatter diagram will lie exactly on the line. This is called perfect correlation (either positive or negative); the return on the security is perfectly predictable from the market return. A large correlation coefficient (in absolute value terms) means systematic variance dominates the total variance; that is, firm-specific variance is relatively unimportant. When the correlation coefficient is small (in absolute value terms), the market factor plays a relatively unimportant part in explaining the variance of the asset, and firm-specific factors predominate. 5

Note that the average beta of all securities will be 1.0 only when we compute a weighted average of betas (using market values as weights), since the stock market index is value weighted. We know from Chapter 5 that the distribution of securities by market value is not symmetric: There are relatively few large corporations and many more smaller ones. Thus, if you were to take a randomly selected sample of stocks, you should expect smaller companies to dominate. As a result, the simple average of the betas of individual securities, when computed against a value-weighted index such as the S&P 500, will be greater than 1.0, pushed up by the tendency for stocks of low-capitalization companies to have betas greater than 1.0.

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Use the implications of capital market theory to compute security risk premiums. Construct and use the security market line. Take advantage of an arbitrage opportunity with a portfolio that includes mispriced securities. Use arbitrage pricing theory with more than one factor to identify mispriced securities.

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Related Websites

http://www.mhhe.com/edumarketinsight

http://finance.yahoo.com http://moneycentral.msn.com/investor/home.asp http://bloomberg.com http://www.411stocks.com/ http://www.morningstar.com

This site contains information on monthly, weekly, and daily returns that can be used in estimating beta coefficients.

http://www.efficientfrontier.com Here you’ll find information on modern portfolio theory and portfolio allocation.

You can use these sites to assess beta coefficients for individual securities and mutual funds.

he capital asset pricing model, almost always referred to as the CAPM, is a centerpiece of modern financial economics. It was first proposed by William F. Sharpe, who was awarded the 1990 Nobel Prize for economics. The CAPM provides a precise prediction of the relationship we should observe between the risk of an asset and its expected return. This relationship serves two vital functions. First, it provides a benchmark rate of return for evaluating possible investments. For example, a security analyst might want to know whether the expected return she forecasts for a stock is more or less than its “fair” return given its risk. Second, the model helps us make an educated guess as to the expected return on assets that have not yet been traded in the marketplace. For example, how do we price an initial public offering of stock? How will a major new investment project affect the return investors require on a company’s stock? Although the CAPM does not fully withstand empirical tests, it is widely used because of the insight it offers and because its accuracy suffices for many important applications. The exploitation of security mispricing to earn risk-free economic profits is called arbitrage. It typically involves the simultaneous purchase and sale of equivalent securities (often in different markets) in order to profit from discrepancies in their price relationship. The most basic principle of capital market theory is that equilibrium market prices should rule out arbitrage opportunities. If actual security prices allow for arbitrage, the resulting opportunities for profitable trading will lead to strong pressure on security prices that will persist until equilibrium is restored. Only a few investors need be aware of arbitrage opportunities to bring about a large volume of trades, and these trades will bring prices back into alignment. Therefore, no-arbitrage restrictions on security prices are extremely powerful. The implications of no-arbitrage principles for financial economics were first explored by Modigliani and Miller, both Nobel Laureates (1985 and 1990).

T

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TA B L E 7.1 Share prices and market values of Bottom Up (BU) and Top Down (TD)

Price per share ($) Shares outstanding Market value ($ millions)

BU

TD

39.00 5,000,000 195

39.00 4,000,000 156

The Arbitrage Pricing Theory (APT) developed by Stephen Ross uses a no-arbitrage argument to derive the same relationship between expected return and risk as the CAPM. We explore the risk-return relationship using well-diversified portfolios and discuss the similarities and differences between the APT and the CAPM.

7.1

DEMAND FOR STOCKS AND EQUILIBRIUM PRICES

So far we have been concerned with efficient diversification, the optimal risky portfolio, and its risk-return profile. We haven’t had much to say about how expected returns are determined in a competitive securities market. To understand how market equilibrium is formed we must connect the determination of optimal portfolios with security analysis and actual buy/sell transactions of investors. We will show in this section how the quest for efficient diversification leads to a demand schedule for shares. In turn, the supply and demand for shares determine equilibrium prices and expected rates of return. Imagine a simple world with only two corporations: Bottom Up Inc. (BU) and Top Down Inc. (TD). Stock prices and market values are shown in Table 7.1. Investors can also invest in a money market fund (MMF) that yields a risk-free interest rate of 5%. Sigma Fund is a new actively managed mutual fund that has raised $220 million to invest in the stock market. The security analysis staff of Sigma believes that neither BU nor TD will grow in the future and, therefore, each firm will pay level annual dividends for the foreseeable future. This is a useful simplifying assumption because, if a stock is expected to pay a stream of level dividends, the income derived from each share is a perpetuity. The present value of each share—often called the intrinsic value of the share—equals the dividend divided by the appropriate discount rate. A summary of the report of the security analysts appears in Table 7.2. The expected returns in Table 7.2 are based on the assumption that next year’s dividends will conform to Sigma’s forecasts, and share prices will be equal to intrinsic values at yearend. The standard deviations and the correlation coefficient between the two stocks were estimated by Sigma’s security analysts from past returns and assumed to remain at these levels for the coming year. Using these data and assumptions Sigma easily generates the efficient frontier shown in Figure 7.1 and computes the optimal portfolio proportions corresponding to the tangency portfolio. These proportions, combined with the total investment budget, yield the Fund’s buy orders. With a budget of $220 million, Sigma wants a position in BU of $220,000,000 ⫻ .8070 ⫽ $177,540,000, or $177,540,000/39 ⫽ 4,552,308 shares, and a position in TD of $220,000,000 ⫻ .1930 ⫽ $42,460,000, which corresponds to 1,088,718 shares.

Sigma’s Demand for Shares The expected rates of return that Sigma used to derive its demand for shares of BU and TD were computed from the forecast of year-end stock prices and the current prices. If, say, a share of BU could be purchased at a lower price, Sigma’s forecast of the rate of return on BU would be higher. Conversely, if BU shares were selling at a higher price, expected returns would be lower. A new expected return would result in a different optimal portfolio and a different demand for shares.

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TA B L E 7.2 Capital market expectations of Sigma’s portfolio manager and optimal portfolio weights

Expected annual dividend ($/share) Discount rate ⫽ Required return* (%) Expected end-of-year price† ($/share) Current price Expected return (%): Dividend yield (div/price) Capital gain (P1 ⫺ P0)/P0 Total rate of return Standard deviation of rate of return (%) Correlation coefficient between BU and TD () Risk-free rate (%) Optimal portfolio weight‡

BU

TD

6.40 16 40 39 16.41 2.56 18.97 40

3.80 10 38 39 9.74 ⫺2.56 7.18 20 .20 5

.8070

.1930

*Based on assessment of risk. †

Obtained by discounting the dividend perpetuity at the required rate of return.

‡

Using footnote 3 of Chapter 6, we obtain the weight in BU as

wBU ⫽

[E(rBU) ⫺ rf ]2TD ⫺ [E(rTD) ⫺ rf ]BUTD [E(rBU) ⫺ rf ]2TD ⫹ [E(rTD) ⫺ rf ]2BU ⫺ [E(rBU) ⫺ rf ⫹ E(rTD) ⫺ rf ]BUTD

The weight in TD equals 1.0 ⫺ wBU.

F I G U R E 7.1

45 Optimal Portfolio wBU ⫽ 80.70% wTD ⫽ 19.30% Mean ⫽ 16.69% Standard deviation ⫽ 33.27%

40

Expected return (%)

35 30

Sigma’s efficient frontier and optimal portfolio

CAL

Efficient frontier of risky assets

25 20 BU 15 10

Optimal portfolio TD

5 0 0

20

40 60 Standard deviation (%)

80

100

We can think of Sigma’s demand schedule for a stock as the number of shares Sigma would want to hold at different share prices. In our simplified world, producing the demand for BU

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TA B L E 7.3 Calculation of Sigma’s demand for BU shares

Current Price ($)

Capital Gain (%)

Dividend Yield (%)

Expected Return (%)

BU Optimal Proportion

Desired BU Shares

45.0 42.5 40.0 37.5 35.0

⫺11.11 ⫺5.88 0 6.67 14.29

14.22 15.06 16.00 17.07 18.29

3.11 9.18 16.00 23.73 32.57

⫺.4113 .3192 .7011 .9358 1.0947

⫺2,010,582 1,652,482 3,856,053 5,490,247 6,881,225

46

Supply ⫽ 5 million shares

Price per share ($)

44 Sigma demand

42 40

Equilibrium price $40.85 Aggregate (total) demand

Index fund demand

38 36 34 32 ⫺3

⫺1

0

1 3 5 Number of shares (millions)

7

9

11

F I G U R E 7.2 Supply and demand for BU shares

shares is not difficult. First, we revise Table 7.2 to recompute the expected return on BU at different current prices given the forecasted year-end price. Then, for each price and associated expected return, we construct the optimal portfolio and find the implied position in BU. A few samples of these calculations are shown in Table 7.3. The first four columns in Table 7.3 show the expected returns on BU shares given their current price. The optimal proportion (column 5) is calculated using these expected returns. Finally, Sigma’s investment budget, the optimal proportion in BU, and the current price of a BU share determine the desired number of shares. Note that we compute the demand for BU shares given the price and expected return for TD. This means that the entire demand schedule must be revised whenever the price and expected return on TD are changed.

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40

Price per share ($)

Supply ⫽ 4 million shares

Aggregate demand

40 Sigma demand

39

Equilibrium price $38.41

39 Index fund demand

38 38 37 ⫺3

⫺2

⫺1

0

1

2

3

4

Number of shares (millions)

F I G U R E 7.3 Supply and demand for TD shares

Sigma’s demand curve for BU stock is given by the Desired Shares column in Table 7.3 and is plotted in Figure 7.2. Notice that the demand curve for the stock slopes downward. When BU’s stock price falls, Sigma will desire more shares for two reasons: (1) an income effect—at a lower price Sigma can purchase more shares with the same budget—and (2) a substitution effect—the increased expected return at the lower price will make BU shares more attractive relative to TD shares. Notice that one can desire a negative number of shares, that is, a short position. If the stock price is high enough, its expected return will be so low that the desire to sell will overwhelm diversification motives and investors will want to take a short position. Figure 7.2 shows that when the price exceeds $44, Sigma wants a short position in BU. The demand curve for BU shares assumes that the price of TD remains constant. A similar demand curve can be constructed for TD shares given a price for BU shares. As before, we would generate the demand for TD shares by revising Table 7.2 for various current prices of TD, leaving the price of BU unchanged. We use the revised expected returns to calculate the optimal portfolio for each possible price of TD, ultimately obtaining the demand curve shown in Figure 7.3.

Index Funds’ Demands for Stock We will see shortly that index funds play an important role in portfolio selection, so let’s see how an index fund would derive its demand for shares. Suppose that $130 million of investor funds in our hypothesized economy are given to an index fund—named Index—to manage. What will it do? Index is looking for a portfolio that will mimic the market. Suppose current prices and market values are as in Table 7.1. Then the required proportions to mimic the market portfolio are: wBU ⫽ 195/(195 ⫹ 156) ⫽ .5556 (55.56%); wTD ⫽ 1 ⫺ .5556 ⫽ .4444 (44.44%)

5

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With $130 million to invest, Index will place .5556 ⫻ $130 million ⫽ $72.22 million in BU shares. Table 7.4 shows a few other points on Index’s demand curve for BU shares. The second column of the table shows the proportion of BU in total stock market value at each assumed price. In our two-stock example, this is BU’s value as a fraction of the combined value of BU and TD. The third column is Index’s desired dollar investment in BU and the last column shows shares demanded. The bold row corresponds to the case we analyzed in Table 7.1, for which BU is selling at $39. Index’s demand curve for BU shares is plotted in Figure 7.2 next to Sigma’s demand, and in Figure 7.3 for TD shares. Index’s demand is smaller than Sigma’s because its budget is smaller. Moreover, the demand curve of the index fund is very steep, or “inelastic,” that is, demand hardly responds to price changes. This is because an index fund’s demand for shares does not respond to expected returns. Index funds seek only to replicate market proportions. As the stock price goes up, so does its proportion in the market. This leads the index fund to invest more in the stock. Nevertheless, because each share costs more, the fund will desire fewer shares.

Equilibrium Prices and the Capital Asset Pricing Model Market prices are determined by supply and demand. At any one time, the supply of shares of a stock is fixed, so supply is vertical at 5,000,000 shares of BU in Figure 7.2 and 4,000,000 shares of TD in Figure 7.3. Market demand is obtained by “horizontal aggregation,” that is, for each price we add up the quantity demanded by all investors. You can examine the horizontal aggregation of the demand curves of Sigma and Index in Figures 7.2 and 7.3. The equilibrium prices are at the intersection of supply and demand. However, the prices shown in Figures 7.2 and 7.3 will likely not persist for more than an instant. The reason is that the equilibrium price of BU ($40.85) was generated by demand curves derived by assuming that the price of TD was $39. Similarly, the equilibrium price of TD ($38.41) is an equilibrium price only when BU is at $39, which also is not the case. A full equilibrium would require that the demand curves derived for each stock be consistent with the actual prices of all other stocks. Thus, our model is only a beginning. But it does illustrate the important link between security analysis and the process by which portfolio demands, market prices, and expected returns are jointly determined. In the next section we will introduce the capital asset pricing model, which treats the problem of finding a set of mutually consistent equilibrium prices and expected rates of return across all stocks. When we argue there that market expected returns adjust to demand pressures, you will understand the process that underlies this adjustment.

TA B L E 7.4 Calculation of index demand for BU shares

Current Price

BU Market-Value Proportion

Dollar Investment* ($ million)

Shares Desired

$45.00 42.50 40.00 39.00 37.50 35.00

.5906 .5767 .5618 .5556 .5459 .5287

76.772 74.966 73.034 72.222 70.961 68.731

1,706,037 1,763,908 1,825,843 1,851,852 1,892,285 1,963,746

*Dollar investment ⫽ BU proportion ⫻ $130 million.

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221

THE CAPITAL ASSET PRICING MODEL

The capital asset pricing model, or CAPM, was developed by Treynor, Sharpe, Lintner, and Mossin in the early 1960s, and further refined later. The model predicts the relationship between the risk and equilibrium expected returns on risky assets. We will approach the CAPM in a simplified setting. Thinking about an admittedly unrealistic world allows a relatively easy leap to the solution. With this accomplished, we can add complexity to the environment, one step at a time, and see how the theory must be amended. This process allows us to develop a reasonably realistic and comprehensible model. A number of simplifying assumptions lead to the basic version of the CAPM. The fundamental idea is that individuals are as alike as possible, with the notable exceptions of initial wealth and risk aversion. The list of assumptions that describes the necessary conformity of investors follows:

capital asset pricing model (CAPM) A model that relates the required rate of return for a security to its risk as measured by beta.

1. Investors cannot affect prices by their individual trades. This means that there are many investors, each with an endowment of wealth that is small compared with the total endowment of all investors. This assumption is analogous to the perfect competition assumption of microeconomics. 2. All investors plan for one identical holding period. 3. Investors form portfolios from a universe of publicly traded financial assets, such as stocks and bonds, and have access to unlimited risk-free borrowing or lending opportunities. 4. Investors pay neither taxes on returns nor transaction costs (commissions and service charges) on trades in securities. In such a simple world, investors will not care about the difference between returns from capital gains and those from dividends. 5. All investors attempt to construct efficient frontier portfolios; that is, they are rational mean-variance optimizers. 6. All investors analyze securities in the same way and share the same economic view of the world. Hence, they all end with identical estimates of the probability distribution of future cash flows from investing in the available securities. This means that, given a set of security prices and the risk-free interest rate, all investors use the same expected returns, standard deviations, and correlations to generate the efficient frontier and the unique optimal risky portfolio. This assumption is called homogeneous expectations. Obviously, these assumptions ignore many real-world complexities. However, they lead to some powerful insights into the nature of equilibrium in security markets. Given these assumptions, we summarize the equilibrium that will prevail in this hypothetical world of securities and investors. We elaborate on these implications in the following sections. 1. All investors will choose to hold the market portfolio (M), which includes all assets of the security universe. For simplicity, we shall refer to all assets as stocks. The proportion of each stock in the market portfolio equals the market value of the stock (price per share times the number of shares outstanding) divided by the total market value of all stocks. 2. The market portfolio will be on the efficient frontier. Moreover, it will be the optimal risky portfolio, the tangency point of the capital allocation line (CAL) to the efficient frontier. As a result, the capital market line (CML), the line from the risk-free rate through the market portfolio, M, is also the best attainable capital allocation line. All investors hold M as their optimal risky portfolio, differing only in the amount invested in it as compared to investment in the risk-free asset.

market portfolio The portfolio for which each security is held in proportion to its market value.

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3. The risk premium on the market portfolio will be proportional to the variance of the market portfolio and investors’ typical degree of risk aversion. Mathematically E(rM) ⫺ rf ⫽ A*M2

(7.1)

where M is the standard deviation of the return on the market portfolio and A* is a scale factor representing the degree of risk aversion of the average investor. 4. The risk premium on individual assets will be proportional to the risk premium on the market portfolio (M) and to the beta coefficient of the security on the market portfolio. This implies that the rate of return on the market portfolio is the single factor of the security market. The beta measures the extent to which returns on the stock respond to the returns of the market portfolio. Formally, beta is the regression (slope) coefficient of the security return on the market portfolio return, representing the sensitivity of the stock return to fluctuations in the overall security market.

Why All Investors Would Hold the Market Portfolio Given all our assumptions, it is easy to see why all investors hold identical risky portfolios. If all investors use identical mean-variance analysis (assumption 5), apply it to the same universe of securities (assumption 3), with an identical time horizon (assumption 2), use the same security analysis (assumption 6), and experience identical tax consequences (assumption 4), they all must arrive at the same determination of the optimal risky portfolio. That is, they all derive identical efficient frontiers and find the same tangency portfolio for the capital allocation line (CAL) from T-bills (the risk-free rate, with zero standard deviation) to that frontier, as in Figure 7.4. With everyone choosing to hold the same risky portfolio, stocks will be represented in the aggregate risky portfolio in the same proportion as they are in each investor’s (common) risky portfolio. If GM represents 1% in each common risky portfolio, GM will be 1% of the aggregate risky portfolio. This in fact is the market portfolio since the market is no more than the aggregate of all individual portfolios. Because each investor uses the market portfolio for the optimal risky portfolio, the CAL in this case is called the capital market line, or CML, as in Figure 7.4.

F I G U R E 7.4

E(r)

The efficient frontier and the capital market line CML E(rM)

M

rf

σM

σ

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Suppose the optimal portfolio of our investors does not include the stock of some company, say, Delta Air Lines. When no investor is willing to hold Delta stock, the demand is zero, and the stock price will take a free fall. As Delta stock gets progressively cheaper, it begins to look more attractive, while all other stocks look (relatively) less attractive. Ultimately, Delta will reach a price at which it is desirable to include it in the optimal stock portfolio, and investors will buy. This price adjustment process guarantees that all stocks will be included in the optimal portfolio. The only issue is the price. At a given price level, investors will be willing to buy a stock; at another price, they will not. The bottom line is this: If all investors hold an identical risky portfolio, this portfolio must be the market portfolio.

The Passive Strategy Is Efficient A passive strategy, using the CML as the optimal CAL, is a powerful alternative to an active strategy. The market portfolio proportions are a result of profit-oriented “buy” and “sell” orders that cease only when there is no more profit to be made. And in the simple world of the CAPM, all investors use precious resources in security analysis. A passive investor who takes a free ride by simply investing in the market portfolio benefits from the efficiency of that portfolio. In fact, an active investor who chooses any other portfolio will end on a CAL that is less efficient than the CML used by passive investors. We sometimes call this result a mutual fund theorem because it implies that only one mutual fund of risky assets—the market portfolio—is sufficient to satisfy the investment demands of all investors. The mutual fund theorem is another incarnation of the separation property discussed in Chapter 6. Assuming all investors choose to hold a market index mutual fund, we can separate portfolio selection into two components: (1) a technical side, in which an efficient mutual fund is created by professional management; and (2) a personal side, in which an investor’s risk aversion determines the allocation of the complete portfolio between the mutual fund and the risk-free asset. Here, all investors agree that the mutual fund they would like to hold is the market portfolio. While different investment managers do create risky portfolios that differ from the market index, we attribute this in part to the use of different estimates of risk and expected return. Still, a passive investor may view the market index as a reasonable first approximation to an efficient risky portfolio. The logical inconsistency of the CAPM is this: If a passive strategy is costless and efficient, why would anyone follow an active strategy? But if no one does any security analysis, what brings about the efficiency of the market portfolio? We have acknowledged from the outset that the CAPM simplifies the real world in its search for a tractable solution. Its applicability to the real world depends on whether its predictions are accurate enough. The model’s use is some indication that its predictions are reasonable. We discuss this issue in Section 7.4 and in greater depth in Chapter 8. 1. If only some investors perform security analysis while all others hold the market portfolio (M), would the CML still be the efficient CAL for investors who do not engage in security analysis? Explain.

The Risk Premium of the Market Portfolio In Chapters 5 and 6 we showed how individual investors decide how much to invest in the risky portfolio when they can include a risk-free asset in the investment budget. Returning now to the decision of how much to invest in the market portfolio M and how much in the risk-free asset, what can we deduce about the equilibrium risk premium of portfolio M?

mutual fund theorem States that all investors desire the same portfolio of risky assets and can be satisfied by a single mutual fund composed of that portfolio.

E(rM) ⫽ rf ⫹ Equilibrium risk premium ⫽ 0.05 ⫹ 0.08 ⫽ 0.13 ⫽ 13% If investors were more risk averse, it would take a higher risk premium to induce them to hold shares. For example, if the average degree of risk aversion were 3, the market risk premium would be 3 ⫻ 0.202 ⫽ 0.12, or 12%, and the expected return would be 17%.

2. Historical data for the S&P 500 index show an average excess return over Treasury bills of about 8.5% with standard deviation of about 20%. To the extent that these averages approximate investor expectations for the sample period, what must have been the coefficient of risk aversion of the average investor? If the coefficient of risk aversion were 3.5, what risk premium would have been consistent with the market’s historical standard deviation?

Expected Returns on Individual Securities The CAPM is built on the insight that the appropriate risk premium on an asset will be determined by its contribution to the risk of investors’ overall portfolios. Portfolio risk is what matters to investors, and portfolio risk is what governs the risk premiums they demand. We know that nonsystematic risk can be reduced to an arbitrarily low level through diversification (Chapter 6); therefore, investors do not require a risk premium as compensation for bearing nonsystematic risk. They need to be compensated only for bearing systematic risk, which cannot be diversified. We know also that the contribution of a single security to the risk of a large diversified portfolio depends only on the systematic risk of the security as measured by its beta.2 Therefore, it should not be surprising that the risk premium of an asset is proportional to its beta; for example, if you double a security’s systematic risk, you must double its risk premium for investors still to be willing to hold the security. Thus, the ratio of risk premium to beta should be the same for any two securities or portfolios. 1

To use Equation 7.1, we must express returns in decimal form rather than as percentages. See Section 6.5. This is literally true with a sufficient number of securities so that all nonsystematic risk is diversified away. In a market as diversified as the U.S. stock market, this would be true for all practical purposes. 2

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For example, if we were to compare the ratio of risk premium to systematic risk for the market portfolio, which has a beta of 1.0, with the corresponding ratio for Dell stock, we would conclude that E(rM) ⫺ rf E(rD) ⫺ rf ⫽ 1 D Rearranging this relationship results in the CAPM’s expected return–beta relationship E(rD) ⫽ rf ⫹ D [E(rM) ⫺ rf]

(7.2)

In words, the rate of return on any asset exceeds the risk-free rate by a risk premium equal to the asset’s systematic risk measure (its beta) times the risk premium of the (benchmark) market portfolio. This expected return–beta relationship is the most familiar expression of the CAPM. The expected return–beta relationship of the CAPM makes a powerful economic statement. It implies, for example, that a security with a high variance but a relatively low beta of 0.5 will carry one-third the risk premium of a low-variance security with a beta of 1.5. Thus, Equation 7.2 quantifies the conclusion we reached in Chapter 6 that only systematic risk matters to investors who can diversify and that systematic risk is measured by the beta of the security.

Suppose the risk premium of the market portfolio is 9%, and we estimate the beta of Dell as D ⫽ 1.3. The risk premium predicted for the stock is therefore 1.3 times the market risk premium, or 1.3 ⫻ 9% ⫽ 11.7%. The expected rate of return on Dell is the risk-free rate plus the risk premium. For example, if the T-bill rate were 5%, the expected rate of return would be 5% ⫹ 11.7% ⫽ 16.7%, or using Equation 7.2 directly, E(rD) ⫽ rf ⫹ D[Market risk premium] ⫽ 5% ⫹ 1.3 ⫻ 9% ⫽ 16.7% If the estimate of the beta of Dell were only 1.2, the required risk premium for Dell would fall to 10.8%. Similarly, if the market risk premium were only 8% and D ⫽ 1.3, Dell’s risk premium would be only 10.4%.

The fact that few real-life investors actually hold the market portfolio does not necessarily invalidate the CAPM. Recall from Chapter 6 that reasonably well-diversified portfolios shed (for practical purposes) firm-specific risk and are subject only to systematic or market risk. Even if one does not hold the precise market portfolio, a well-diversified portfolio will be so highly correlated with the market that a stock’s beta relative to the market still will be a useful risk measure. In fact, several researchers have shown that modified versions of the CAPM will hold despite differences among individuals that may cause them to hold different portfolios. A study by Brennan (1970) examines the impact of differences in investors’ personal tax rates on market equilibrium. Another study by Mayers (1972) looks at the impact of nontraded assets such as human capital (earning power). Both find that while the market portfolio is no longer each investor’s optimal risky portfolio, a modified version of the expected return–beta relationship still holds. If the expected return–beta relationship holds for any individual asset, it must hold for any combination of assets. The beta of a portfolio is simply the weighted average of the betas of the stocks in the portfolio, using as weights the portfolio proportions. Thus, beta also predicts the portfolio’s risk premium in accordance with Equation 7.2.

expected return–beta relationship Implication of the CAPM that security risk premiums (expected excess returns) will be proportional to beta.

EXAMPLE 7.2 Expected Returns and Risk Premiums

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Consider the following portfolio:

7.3 EXAMPLE Portfolio Beta and Risk Premium

Asset

Beta

Risk Premium

Portfolio Weight

Microsoft Con Edison Gold

1.2 0.8 0.0

9.0% 6.0 0.0

0.5 0.3 0.2

Portfolio

0.84

?

1.0

If the market risk premium is 7.5%, the CAPM predicts that the risk premium on each stock is its beta times 7.5%, and the risk premium on the portfolio is 0.84 ⫻ 7.5% ⫽ 6.3%. This is the same result that is obtained by taking the weighted average of the risk premiums of the individual stocks. (Verify this for yourself.)

A word of caution: We often hear that well-managed firms will provide high rates of return. We agree this is true if one measures the firm’s return on investments in plant and equipment. The CAPM, however, predicts returns on investments in the securities of the firm. Say that everyone knows a firm is well run. Its stock price should, therefore, be bid up, and returns to stockholders who buy at those high prices will not be extreme. Security prices reflect public information about a firm’s prospects, but only the risk of the company (as measured by beta in the context of the CAPM) should affect expected returns. In a rational market, investors receive high expected returns only if they are willing to bear risk.

Concept CHECK

>

3. Suppose the risk premium on the market portfolio is estimated at 8% with a standard deviation of 22%. What is the risk premium on a portfolio invested 25% in GM with a beta of 1.15 and 75% in Ford with a beta of 1.25?

The Security Market Line

security market line (SML) Graphical representation of the expected return–beta relationship of the CAPM.

We can view the expected return–beta relationship as a reward-risk equation. The beta of a security is the appropriate measure of its risk because beta is proportional to the risk the security contributes to the optimal risky portfolio. Risk-averse investors measure the risk of the optimal risky portfolio by its standard deviation. In this world, we would expect the reward, or the risk premium on individual assets, to depend on the risk an individual asset contributes to the overall portfolio. Because the beta of a stock measures the stock’s contribution to the standard deviation of the market portfolio, we expect the required risk premium to be a function of beta. The CAPM confirms this intuition, stating further that the security’s risk premium is directly proportional to both the beta and the risk premium of the market portfolio; that is, the risk premium equals [E(rM ) ⫺ rf ]. The expected return–beta relationship is graphed as the security market line (SML) in Figure 7.5. Its slope is the risk premium of the market portfolio. At the point where  ⫽ 1.0 (which is the beta of the market portfolio) on the horizontal axis, we can read off the vertical axis the expected return on the market portfolio. It is useful to compare the security market line to the capital market line. The CML graphs the risk premiums of efficient portfolios (that is, complete portfolios made up of the risky market portfolio and the risk-free asset) as a function of portfolio standard deviation. This is appropriate because standard deviation is a valid measure of risk for portfolios that are candidates for an investor’s complete (overall) portfolio.

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F I G U R E 7.5

E(r) (%)

The security market line and a positivealpha stock

SML

Stock

17 15.6 14

α M

6

1.0 1.2

β

The SML, in contrast, graphs individual asset risk premiums as a function of asset risk. The relevant measure of risk for individual assets (which are held as parts of a well-diversified portfolio) is not the asset’s standard deviation; it is, instead, the contribution of the asset to the portfolio standard deviation as measured by the asset’s beta. The SML is valid both for portfolios and individual assets. The security market line provides a benchmark for evaluation of investment performance. Given the risk of an investment as measured by its beta, the SML provides the required rate of return that will compensate investors for the risk of that investment, as well as for the time value of money. Because the security market line is the graphical representation of the expected return–beta relationship, “fairly priced” assets plot exactly on the SML. The expected returns of such assets are commensurate with their risk. Whenever the CAPM holds, all securities must lie on the SML in market equilibrium. Underpriced stocks plot above the SML: Given their betas, their expected returns are greater than is indicated by the CAPM. Overpriced stocks plot below the SML. The difference between the fair and actually expected rate of return on a stock is called the stock’s alpha, denoted ␣. Suppose the return on the market is expected to be 14%, a stock has a beta of 1.2, and the T-bill rate is 6%. The SML would predict an expected return on the stock of E(r) ⫽ rf ⫹ [E(rM) ⫺ rf ] ⫽ 6 ⫹ 1.2 (14 ⫺ 6) ⫽ 15.6% If one believes the stock will provide instead a return of 17%, its implied alpha would be 1.4%, as shown in Figure 7.5.

Applications of the CAPM One place the CAPM may be used is in the investment management industry. Suppose the SML is taken as a benchmark to assess the fair expected return on a risky asset. Then an analyst calculates the return he or she actually expects. Notice that we depart here from the

alpha The abnormal rate of return on a security in excess of what would be predicted by an equilibrium model such as the CAPM.

EXAMPLE 7.4 The Alpha of a Security

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simple CAPM world in that some investors apply their own analysis to derive an “input list” that may differ from their competitors’. If a stock is perceived to be a good buy, or underpriced, it will provide a positive alpha, that is, an expected return in excess of the fair return stipulated by the SML. The CAPM also is useful in capital budgeting decisions. If a firm is considering a new project, the CAPM can provide the return the project needs to yield to be acceptable to investors. Managers can use the CAPM to obtain this cutoff internal rate of return (IRR) or “hurdle rate” for the project.

7.5 EXAMPLE The CAPM and Capital Budgeting

Suppose Silverado Springs Inc. is considering a new spring-water bottling plant. The business plan forecasts an internal rate of return of 14% on the investment. Research shows the beta of similar products is 1.3. Thus, if the risk-free rate is 4%, and the market risk premium is estimated at 8%, the hurdle rate for the project should be 4 ⫹ 1.3 ⫻ 8 ⫽ 14.4%. Because the IRR is less than the risk-adjusted discount or hurdle rate, the project has a negative net present value and ought to be rejected.

Yet another use of the CAPM is in utility rate-making cases. Here the issue is the rate of return a regulated utility should be allowed to earn on its investment in plant and equipment.

7.6 EXAMPLE The CAPM and Regulation

Concept CHECK

>

Suppose equityholders’ investment in the firm is $100 million, and the beta of the equity is 0.6. If the T-bill rate is 6%, and the market risk premium is 8%, then a fair annual profit will be 6 ⫹ (0.6 ⫻ 8) ⫽ 10.8% of $100 million, or $10.8 million. Since regulators accept the CAPM, they will allow the utility to set prices at a level expected to generate these profits.

4. a. Stock XYZ has an expected return of 12% and risk of  ⴝ 1.0. Stock ABC is expected to return 13% with a beta of 1.5. The market’s expected return is 11% and rf ⴝ 5%. According to the CAPM, which stock is a better buy? What is the alpha of each stock? Plot the SML and the two stocks and show the alphas of each on the graph. b. The risk-free rate is 8% and the expected return on the market portfolio is 16%. A firm considers a project with an estimated beta of 1.3. What is the required rate of return on the project? If the IRR of the project is 19%, what is the project alpha?

7.3

THE CAPM AND INDEX MODELS

The CAPM has two limitations: It relies on the theoretical market portfolio, which includes all assets (such as real estate, foreign stocks, etc.), and it deals with expected as opposed to actual returns. To implement the CAPM, we cast it in the form of an index model and use realized, not expected, returns. An index model uses actual portfolios, such as the S&P 500, rather than the theoretical market portfolio to represent the relevant systematic factors in the economy. The important advantage of index models is that the composition and rate of return of the index is easily measured and unambiguous.

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In contrast to an index model, the CAPM revolves around the “market portfolio.” However, because many assets are not traded, investors would not have full access to the market portfolio even if they could exactly identify it. Thus, the theory behind the CAPM rests on a shaky real-world foundation. But, as in all science, a theory may be viewed as legitimate if its predictions approximate real-world outcomes with a sufficient degree of accuracy. In particular, the reliance on the market portfolio shouldn’t faze us if we can verify that the predictions of the CAPM are sufficiently accurate when the index portfolio is substituted for the market. We can start with one central prediction of the CAPM: The market portfolio is meanvariance efficient. An index model can be used to test this hypothesis by verifying that an index chosen to be representative of the full market is a mean-variance efficient portfolio. Another aspect of the CAPM is that it predicts relationships among expected returns, while all we can observe are realized (historical) holding-period returns; actual returns in a particular holding period seldom, if ever, match our initial expectations. To test the mean-variance efficiency of an index portfolio, we would have to show that the reward-to-variability ratio of the index is not surpassed by any other portfolio. The reward-to-variability ratio, however, is set in terms of expectations, and we can measure it only in terms of realizations.

The Index Model, Realized Returns, and the Expected Return–Beta Relationship To move from a model cast in expectations to a realized-return framework, we start with a form of the single-index regression equation in realized excess returns, similar to that of Equation 6.6 in Chapter 6: ri ⫺ rf ⫽ ␣i ⫹ i (rM ⫺ rf ) ⫹ ei

(7.3)

where ri is the holding-period return (HPR) on asset i, and ␣i and i are the intercept and slope of the line that relates asset i’s realized excess return to the realized excess return of the index. We denote the index return by rM to emphasize that the index portfolio is proxying for the market. The ei measures firm-specific effects during the holding period; it is the deviation of security i’s realized HPR from the regression line, that is, the deviation from the forecast that accounts for the index’s HPR. We set the relationship in terms of excess returns (over the riskfree rate, rf ), for consistency with the CAPM’s logic of risk premiums. Given that the CAPM is a statement about the expectation of asset returns, we look at the expected return of security i predicted by Equation 7.3. Recall that the expectation of ei is zero (the firm-specific surprise is expected to average zero over time), so the relationship expressed in terms of expectations is E(ri) ⫺ rf ⫽ ␣i ⫹ i [E(rM ) ⫺ rf ]

(7.4)

Comparing this relationship to the expected return–beta relationship (Equation 7.2) of the CAPM reveals that the CAPM predicts ␣i ⫽ 0. Thus, we have converted the CAPM prediction about unobserved expectations of security returns relative to an unobserved market portfolio into a prediction about the intercept in a regression of observed variables: realized excess returns of a security relative to those of a specified index. Operationalizing the CAPM in the form of an index model has a drawback, however. If intercepts of regressions of returns on an index differ substantially from zero, you will not be able to tell whether it is because you chose a bad index to proxy for the market or because the theory is not useful. In actuality, few instances of persistent, positive significant alpha values have been identified; these will be discussed in Chapter 8. Among these are: (1) small versus large stocks; (2) stocks of companies that have recently announced unexpectedly good earnings; (3) stocks

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with high ratios of book value to market value; and (4) stocks that have experienced recent sharp price declines. In general, however, future alphas are practically impossible to predict from past values. The result is that index models are widely used to operationalize capital asset pricing theory.

Estimating the Index Model Equation 7.3 also suggests how we might go about actually measuring market and firm-specific risk. Suppose that we observe the excess return on the market index and a specific asset over a number of holding periods. We use as an example monthly excess returns on the S&P 500 index and GM stock for a particular year. We can summarize the results for a sample period in a scatter diagram, as illustrated in Figure 7.6. The horizontal axis in Figure 7.6 measures the excess return (over the risk-free rate) on the market index; the vertical axis measures the excess return on the asset in question (GM stock in our example). A pair of excess returns (one for the market index, one for GM stock) over a holding period constitutes one point on this scatter diagram. The points are numbered 1 through 12, representing excess returns for the S&P 500 and GM for each month from January through December. The single-index model states that the relationship between the excess returns on GM and the S&P 500 is given by RGMt ⫽ ␣GM ⫹ GMRMt ⫹ eGMt We have noted the resemblance of this relationship to a regression equation. In a single-variable linear regression equation, the dependent variable plots around a straight line with an intercept ␣ and a slope . The deviations from the line, ei , are assumed to

F I G U R E 7.6

8

Characteristic line for GM

7

5 11

6 1

Excess rate of return on GM stock (%)

5 4 3

12

2 1 6

0 –1

10

9

–2

7

–3 –4

2

8

–5 –6 –7 –8 –9 –5

4 3 –3 –1 0 1 3 5 7 Excess rate of return on the market index (%)

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be mutually independent and independent of the right-hand side variable. Because these assumptions are identical to those of the index model, we can look at the index model as a regression model. The sensitivity of GM to the market, measured by GM, is the slope of the regression line. The intercept of the regression line is ␣ (which represents the average firmspecific return), and deviations of particular observations from the regression line are denoted e. These residuals are the differences between the actual stock return and the return that would be predicted from the regression equation describing the usual relationship between the stock and the market; therefore, they measure the impact of firm-specific events during the particular month. The parameters of interest, ␣, , and Var(e), can be estimated using standard regression techniques. Estimating the regression equation of the single-index model gives us the security characteristic line (SCL), which is plotted in Figure 7.6. (The regression results and raw data appear in Table 7.5.) The SCL is a plot of the typical excess return on a security over the riskfree rate as a function of the excess return on the market. This sample of 12 monthly holding-period returns is, of course, too small to yield reliable statistics. We use it only for demonstration. For this sample period, we find that the beta coefficient of GM stock, as estimated by the slope of the regression line, is 1.136, and that the intercept for this SCL is ⫺2.59% per month. For each month, our estimate of the residual, e, which is the deviation of GM’s excess return from the prediction of the SCL, equals

security characteristic line (SCL) A plot of a security’s expected excess return over the riskfree rate as a function of the excess return on the market.

Residual ⫽ Actual ⫺ Predicted return eGMt ⫽ RGMt ⫺ (GMRMt ⫹ ␣GM)

TA B L E 7.5 Characteristic line for GM stock

Month January February March April May June July August September October November December Mean Standard deviation Regression results

GM Return

Market Return

Monthly T-Bill Rate

Excess GM Return

Excess Market Return

6.06 ⫺2.86 ⫺8.17 ⫺7.36 7.76 0.52 ⫺1.74 ⫺3.00 ⫺0.56 ⫺0.37 6.93 3.08

7.89 1.51 0.23 ⫺0.29 5.58 1.73 ⫺0.21 ⫺0.36 ⫺3.58 4.62 6.85 4.55

0.65 0.58 0.62 0.72 0.66 0.55 0.62 0.55 0.60 0.65 0.61 0.65

5.41 ⫺3.44 ⫺8.79 ⫺8.08 7.10 ⫺0.03 ⫺2.36 ⫺3.55 ⫺1.16 ⫺1.02 6.32 2.43

7.24 0.93 ⫺0.39 ⫺1.01 4.92 1.18 ⫺0.83 ⫺0.91 ⫺4.18 3.97 6.24 3.90

0.02 5.19

2.38 3.48

0.62 0.05

⫺0.60 5.19

1.76 3.46

rGM ⫺ rf ⫽ ␣ ⫹ (rM ⫺ rf)

␣ Estimated coefficient ⫺2.591 Standard error of estimate (1.59) Variance of residuals ⫽ 12.585 Standard deviation of residuals ⫽ 3.548 R-SQR ⫽ 0.575

 1.136 (0.309)

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TA B L E 7.6

A. Market index Expected excess return over T-bill rate, E(RM) ⫽ 8% Standard deviation of excess return, (RM) ⫽ 20% B. Individual stocks

True parameters of securities

Stock A Stock B

Beta

Standard Deviation of Residual, (e)

Total Standard Deviation of Returns*

1.30 0.70

54.07% 37.47

60% 40

*Standard deviation ⫽ [2M2 ⫹ 2(e)]1/2 Stock A: [1.32 ⫻ 202 ⫹ 54.072]1/2 ⫽ 60% Stock B: [0.72 ⫻ 202 ⫹ 37.472]1/2 ⫽ 40%

C. T-bills Average value in sample period ⫽ 5% Month-to-month variation results in a standard deviation across months of 1.5%

These residuals are estimates of the monthly unexpected firm-specific component of the rate of return on GM stock. Hence we can estimate the firm-specific variance by3 2(eGM) ⫽

1 12 2 兺 et ⫽ 12.60 10 t ⫽ 1

Therefore, the standard deviation of the firm-specific component of GM’s return, (eGM), equals 3.55% per month.

The CAPM and the Index Model We have introduced the CAPM and shown how the model can be made operational and how beta can be estimated with the additional simplification of the index model of security returns. Of course, when we estimate the statistical properties of security returns (e.g., betas or variances) using historical data, we are subject to sampling error. Regression parameters are only estimates and necessarily are subject to some imprecision. In this section, we put together much of the preceding material in an extended example. We show how historical data can be used in conjunction with the CAPM, but we also highlight some pitfalls to be avoided. Suppose that the true parameters for two stocks, A and B, and the market index portfolio are given in Table 7.6. However, investors cannot observe this information directly. They must estimate these parameters using historical returns. To illustrate the investor’s problem, we first produce 24 possible observations for the riskfree rate and the market index. Using the random number generator from a spreadsheet package (e.g., you can use “data analysis tools” in Microsoft Excel), we draw 24 observations from a normal distribution. These random numbers capture the phenomenon that actual returns will differ from expected returns: This is the “statistical noise” that accompanies all real-world return data. For the risk-free rate we set a mean of 5% and a standard deviation of 1.5% and

Because the mean of et is zero, e2t is the squared deviation from its mean. The average value of et2 is therefore the estimate of the variance of the firm-specific component. We divide the sum of squared residuals by the degrees of freedom of the regression, n ⫺ 2 ⫽ 12 ⫺ 2 ⫽ 10, to obtain an unbiased estimate of 2(e). 3

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TA B L E 7.7 Simulated data for estimation of security characteristic line (raw data from random number generator)

True mean True standard deviation Sample average Sample standard deviation

Residuals for Each Stock

Excess Returns

T-Bill Rate

Excess Return on Index

Stock A

Stock B

Stock A

Stock B

5.97 4.45 3.24 5.70 3.89 5.56 5.03 2.70 5.57 5.94 4.41 4.43 2.88 5.77 2.85 5.11 5.89 7.96 7.13 3.46 4.72 4.21 5.27 6.05

⫺3.75 ⫺9.46 26.33 6.06 38.97 ⫺1.35 ⫺24.18 15.20 39.52 ⫺2.84 ⫺0.97 29.82 0.73 16.54 ⫺39.43 ⫺4.94 3.01 36.98 42.22 24.67 ⫺11.64 19.15 ⫺19.13 5.05

7.52 26.14 18.09 ⫺0.88 48.37 ⫺30.80 ⫺10.74 68.91 ⫺14.09 0.43 73.75 25.31 ⫺83.07 ⫺33.45 60.21 3.84 47.37 ⫺32.91 ⫺58.15 77.05 ⫺51.49 14.06 ⫺80.44 ⫺91.90

44.13 ⫺38.79 ⫺65.43 69.24 61.51 26.25 0.93 ⫺18.53 16.80 ⫺36.15 ⫺20.33 68.88 ⫺10.82 43.85 ⫺11.82 2.95 12.80 ⫺30.88 ⫺58.68 3.89 ⫺16.87 ⫺18.79 59.07 ⫺67.83

2.64 13.85 52.32 7.00 99.03 ⫺32.56 ⫺42.18 88.66 37.29 ⫺3.26 72.48 64.08 ⫺82.13 ⫺11.95 8.95 ⫺2.59 51.29 15.16 ⫺3.26 109.11 ⫺66.62 38.95 ⫺105.31 ⫺85.33

41.50 ⫺45.41 ⫺46.99 73.49 88.78 25.30 ⫺16.00 ⫺7.89 44.46 ⫺38.14 ⫺21.01 89.76 ⫺10.31 55.43 ⫺39.42 ⫺0.51 14.91 ⫺4.99 ⫺29.12 21.15 ⫺25.02 ⫺5.39 45.69 ⫺64.29

5.00 1.50 4.93 1.34

8.00 20.00 7.77 21.56

0.00 54.07 ⫺0.70 50.02

0.00 37.47 0.64 41.48

10.40 60.00 9.40 58.31

5.60 40.00 6.08 43.95

record the results in the first column of Table 7.7. We then generate 24 observations for excess returns of the market index, using a mean of 8% and a standard deviation of 20%. We record these observations in the second column of Table 7.7. The bottom four rows in Table 7.7 show the true values for the means and standard deviations as well as the actual sample averages and standard deviations. As you would expect, the sample averages and standard deviations are close but not precisely equal to the true parameters of the probability distribution. This is a reflection of the statistical variation that gives rise to sampling error. In the next step we wish to generate excess returns for stocks A and B that are consistent with the CAPM. According to the CAPM, the rate of return on any security is given by r ⫺ rf ⫽ (rM ⫺ rf ) ⫹ e or using capital letters to denote excess returns, R ⫽ RM ⫹ e

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Coefficients

TA B L E 7.8 Regression analysis for stock A

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Alpha—Stock A Beta—Stock A

⫺0.46 1.27

Standard Error 11.12 0.50

t Stat ⫺0.04 2.52

Residual Output—Stock A Observation

Predicted A

Residuals

Actual Returns

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

⫺5.22 ⫺12.45 32.93 7.23 48.94 ⫺2.17 ⫺31.12 4.86 49.65 ⫺4.06 ⫺1.69 37.35 0.46 20.51 ⫺50.45 ⫺6.73 3.36 46.43 53.08 30.82 ⫺15.22 23.81 ⫺15.83 5.95

7.86 26.29 19.40 ⫺0.23 50.08 ⫺30.38 ⫺11.05 69.50 ⫺12.36 0.80 74.17 26.73 ⫺82.59 ⫺32.46 59.40 4.14 47.92 ⫺31.27 ⫺56.33 78.30 ⫺51.40 15.13 ⫺80.38 ⫺91.28

2.64 13.85 52.32 7.00 99.03 ⫺32.56 ⫺42.18 74.36 37.29 ⫺3.26 72.48 64.08 ⫺82.13 ⫺11.95 8.95 ⫺2.59 51.29 15.16 ⫺3.26 109.11 ⫺66.62 38.95 ⫺96.21 ⫺85.33

Therefore, the CAPM hypothesizes an alpha of zero in Equation 7.3. Given the values of  and RM, we need only random residuals, e, to generate a simulated sample of returns on each stock. Using the random number generator once again, we generate 24 observations for the residuals of stock A from a normal distribution with a mean of zero and a standard deviation of 54.07%. These observations are recorded in the third column of Table 7.7. Similarly, the randomly generated residuals for stock B use a standard deviation of 37.47% and are recorded in the fourth column of Table 7.7. The excess rates of return of stocks A and B are computed by multiplying the excess return on the market index by beta and adding the residual. The results appear in the last two columns of Table 7.7. Thus, the first two and last two columns of Table 7.7 correspond to the type of historical data that we might observe if the CAPM adequately describes capital market equilibrium. The numbers come from probability distributions consistent with the CAPM, but, because of the residuals, the CAPM’s expected return–beta relationship will not hold exactly due to sampling error. We now use a regression program (again, from the “data analysis” menu of our spreadsheet) to regress the excess return of each stock against the excess return of the index. The regression routine allows us to save the predicted return for each stock, based on the market return in that period, as well as the regression residuals. These values, and the regression statistics, are presented in Table 7.8 for stock A and Table 7.9 for stock B.

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Regression analysis for stock B

Alpha—Stock B Beta—Stock B

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Coefficients

TA B L E 7.9

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0.39 0.73

Standard Error 9.22 0.42

t Stat 0.04 1.76

Residual Output—Stock B Observation

Predicted B

Residuals

Actual Returns

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

⫺2.36 ⫺6.55 19.70 4.83 28.96 ⫺0.60 ⫺17.35 3.46 29.37 ⫺1.70 ⫺0.33 22.25 0.92 12.52 ⫺28.52 ⫺3.24 2.60 27.51 31.35 18.48 ⫺8.15 14.43 ⫺8.50 4.09

43.87 ⫺38.86 ⫺66.69 68.65 59.82 25.91 1.35 ⫺19.05 15.09 ⫺36.45 ⫺20.68 67.50 ⫺11.23 42.91 ⫺10.90 2.72 12.31 ⫺32.50 ⫺60.47 2.68 ⫺16.87 ⫺19.82 59.09 ⫺68.38

41.50 ⫺45.41 ⫺46.99 73.49 88.78 25.30 ⫺16.00 ⫺15.59 44.46 ⫺38.14 ⫺21.01 89.76 ⫺10.31 55.43 ⫺39.42 ⫺0.51 14.91 ⫺4.99 ⫺29.12 21.15 ⫺25.02 ⫺5.39 50.59 ⫺64.29

Observe from the regression statistics in Tables 7.8 and 7.9 that the beta of stock A is estimated at 1.27 (versus the true value of 1.3) and the beta of stock B is estimated at 0.73 (versus the true value of 0.7). The regression also shows estimates of alpha as ⫺0.46% for A and 0.39% for B (versus a true value of zero for both stocks), but the standard error of these estimates is large and their t-values are low, indicating that these are not statistically significant. The regression estimates allow us to plot the security characteristic line (SCL) for both stocks, shown in Figure 7.7 for stock A and Figure 7.8 for stock B. The CAPM representation of the securities is shown in Figures 7.9 and 7.10. Figure 7.9 shows the security market line (SML) supported by the risk-free rate and the market index. Stock A has a negative estimated alpha and is therefore below the line. This suggests that stock A is overpriced, that is, its expected return is below that which can be obtained with efficient portfolios and the risk-free rate. The negative estimated alpha is due to the effect of the firm-specific residuals. Similarly, stock B plots above the SML. Here, it appears that stock B is underpriced and has an expected return above that which can be obtained with the market index and the risk-free asset (given by the SML). Figure 7.10 shows the capital market line (CML) that is supported by the risk-free rate and the market index. The efficient frontier is generated by the Markowitz algorithm applied to the

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rA - rf (%) 150

100

50

–30

–10

rM - rf (%)

0 –50

10

30

50

10

30

50

–50

–100

F I G U R E 7.7 Security characteristic line for stock A

rB - rf (%) 150

100

50

–30

–10

rM - rf (%)

0 –50

–50

–100

F I G U R E 7.8 Security characteristic line for stock B

means, standard deviations, and correlation coefficients of the full set of risky assets in the universe of securities. (This additional information is not shown here.) Stocks A and B plot far

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20

SML Expected return (%)

15 A

B

M

10

5

rf

0 0

0.2

0.4

0.6

0.8

1

1.2

1.4

Beta

F I G U R E 7.9 Security market line

20

CML

Expected return (%)

15 M

Efficient frontier of risky assets

A

B

10

5

rf

0 0

10

20

30 40 Standard deviation (%)

50

F I G U R E 7.10 Capital market line

below the CML and below the efficient frontier, demonstrating that undiversified individual securities are dominated by efficiently diversified portfolios.

60

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E XC E L Applications

>

www.mhhe.com/bkm

Beta

This Excel model contains a data set that can be used to estimate beta coefficients for a number of stocks. The data contain individual stock and index returns and returns on Treasury bills. These were obtained from the Standard & Poor’s Educational Version of Market Insight, available at www.mhhe.com/edumarketinsight.com, and are analyzed using the regression function in Excel that was discussed in section 6.5, “A Single-Factor Asset Market.” You can learn more about this spreadsheet model by using the interactive version available on our website at www.mhhe.com/bkm.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

A B SUMMARY OUTPUT AXP

C

D

E

F

G

H

I

Regression Statistics Multiple R 0.69288601 R Square 0.48009103 Adjusted R Square 0.47112708 Standard Error 0.05887426 Observations 60 ANOVA

df Regression Residual Total

Intercept X Variable 1

SS MS F Significance F 1 0.185641557 0.1856416 53.55799 8.55186E-10 58 0.201038358 0.0034662 59 0.386679915

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 0.01181687 0.00776211 1.522379 0.133348 ⫺0.003720666 0.027354414 ⫺0.0037207 0.02735441 1.20877413 0.165170705 7.3183324 8.55E-10 0.878149288 1.539398969 0.87814929 1.53939897

Predicting Betas Even if a single-index model representation is not fully consistent with the CAPM, the concept of systematic versus diversifiable risk is still useful. Systematic risk is approximated well by the regression equation beta and nonsystematic risk by the residual variance of the regression. Often, we estimate betas in order to forecast the rate of return of an asset. The beta from the regression equation is an estimate based on past history; it will not reveal possible changes in future beta. As an empirical rule, it appears that betas exhibit a statistical property called “regression toward the mean.” This means that high  (that is,  ⬎ 1) securities in one period tend to exhibit a lower  in the future, while low  (that is,  ⬍ 1) securities exhibit a higher  in future periods. Researchers who desire predictions of future betas often adjust beta estimates derived from historical data to account for regression toward the mean. For this reason, it is necessary to verify whether the estimates are already “adjusted betas.” A simple way to account for the tendency of future betas to “regress” toward the average value of 1.0 is to use as your forecast of beta a weighted average of the sample estimate with the value 1.0. 238

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Suppose that past data yield a beta estimate of 0.65. A common weighting scheme is 2⁄3 on the sample estimate and 1⁄3 on the value 1.0. Thus, the final forecast of beta will be Adjusted beta ⫽ 2⁄3 ⫻ 0.65 ⫹ 1⁄3 ⫻ 1.0 ⫽ 0.77 The final forecast of beta is in fact closer to 1.0 than the sample estimate.

A more sophisticated technique would base the weight assigned to the sample estimate of beta on its statistical reliability. That is, if we have a more precise estimate of beta from historical data, we increase the weight placed on the sample estimate. However, obtaining a precise statistical estimate of beta from past data on individual stocks is a formidable task, because the volatility of rates of return is so large. In other words, there is a lot of “noise” in the data due to the impact of firm-specific events. The problem is less severe with diversified portfolios because diversification reduces the effect of firm-specific events. One might hope that more precise estimates of beta could be obtained by using more data, that is, by using a long time series of the returns on the stock. Unfortunately, this is not a solution, because regression analysis presumes that the regression coefficient (the beta) is constant over the sample period. If betas change over time, old data could provide a misleading guide to current betas. More complicated regression techniques that allow for time-varying coefficients also have not proved to be very successful. One promising avenue is an application of a technique that goes by the name of ARCH models.4 An ARCH model posits that changes in stock volatility, and covariance with other stocks, are partially predictable and analyzes recent levels and trends in volatility and covariance. This technique has penetrated the industry only recently and so has not yet produced truly reliable betas. Thus, the problem of estimating the critical parameters of the CAPM and index models has been a stick in the wheels of testing and applying the theory.

7.4

THE CAPM AND THE REAL WORLD

In limited ways, portfolio theory and the CAPM have become accepted tools in the practitioner community. Many investment professionals think about the distinction between firmspecific and systematic risk and are comfortable with the use of beta to measure systematic

WEBMA STER Beta Comparisons Go to http://moneycentral.msn.com/investor/research and http:nasdaq.com. Obtain the beta coefficients for IMB, PG, HWP, AEIS, and INTC. (Betas on the Nasdaq site can be found by using the info quotes and fundamental locations.) Compare the betas reported by these two sites. Then, answer the following questions:

4

1.

Are there any significant differences in the reported beta coefficients?

2.

What factors could lead to such differences?

ARCH stands for autoregressive conditional heteroskedasticity. This is a fancy way of saying that the volatility (and covariance) of stocks changes over time in ways that can be at least partially predicted from their past levels.

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EXAMPLE 7.7 Forecast of Beta

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Beta Beaten A battle between some of the top names in financial economics is attracting attention on Wall Street. Under attack is the famous capital asset pricing model (CAPM), widely used to assess risk and return. A new paper by two Chicago economists, Eugene Fama and Kenneth French, explodes that model by showing that its key analytical tool does not explain why returns on shares differ. According to the CAPM, returns reflect risk. The model uses a measure called beta—shorthand for relative volatility—to compare the riskiness of one share with that of the whole market, on the basis of past price changes. A share with a beta of one is just as risky as the market; one with a beta of 0.5 is less risky. Because investors need to earn more on riskier investments, share prices will reflect the requirement for higher-thanaverage returns on shares with higher betas. Whether beta does predict returns has long been debated. Studies have found that market capitalization, price/earnings ratios, leverage and book-to-market ratios do just as well. Messrs Fama and French are clear: Beta is not a good guide. The two economists look at all nonfinancial shares traded on the NYSE, Amex and Nasdaq between 1963 and 1990. The shares were grouped into portfolios. When grouped solely on the basis of size (that is, market capitalization), the CAPM worked—but each portfolio contained a wide range of betas. So the authors grouped shares of similar beta and size. Betas now were a bad guide to returns. Instead of beta, say Messrs Fama and French, differences in firm size and in the ratio of book value to market value explain differences in returns—especially the latter. When shares were grouped by book-to-

market ratios, the gap in returns between the portfolio with the lowest ratio and that with the highest was far wider than when shares were grouped by size. So should analysts stop using the CAPM? Probably not. Although Mr. Fama and Mr. French have produced intriguing results, they lack a theory to explain them. Their best hope is that size and book-to-market ratios are proxies for other fundamentals. For instance, a high book-to-market ratio may indicate a firm in trouble; its earnings prospects might thus be especially sensitive to economic conditions, so its shares would need to earn a higher return than its beta suggested. Advocates of CAPM—including Fischer Black, of Goldman Sachs, an investment bank, and William Sharpe of Stanford University, who won the Nobel Prize for economics in 1990—reckon the results of the new study can be explained without discarding beta. Investors may irrationally favor big firms. Or they may lack the cash to buy enough shares to spread risk completely, so that risk and return are not perfectly matched in the market. Those looking for a theoretical alternative to CAPM will find little satisfaction, however. Voguish rivals, such as the “arbitrage pricing theory,” are no better than CAPM and betas at explaining actual share returns. Which leaves Wall Street with an awkward choice: Believe the Fama–French evidence, despite its theoretical vacuum, and use size and the book-to-market ratios as a guide to returns; or stick with a theory that, despite the data, is built on impeccable logic. SOURCE: “Beta Beaten,” The Economist, March 7, 1992, p. 87, based on Eugene Fama and Kenneth French, “The Cross-Section of Expected Stock Returns,” University of Chicago Center for Research in Security Prices, 1991.

risk. Still, the nuances of the CAPM are not nearly as well established in the community. For example, the compensation of portfolio managers is not based on appropriate performance measures (see Chapter 20). What can we make of this? New ways of thinking about the world (that is, new models or theories) displace old ones when the old models become either intolerably inconsistent with data or when the new model is demonstrably more consistent with available data. For example, when Copernicus overthrew the age-old belief that the Earth is fixed in the center of the Universe and that the stars orbit about it in circular motions, it took many years before astronomers and navigators replaced old astronomical tables with superior ones based on his theory. The old tools fit the data available from astronomical observation with sufficient precision to suffice for the needs of the time. To some extent, the slowness with which the CAPM has permeated daily practice in the money management industry also has to do with its precision in fitting data, that is, in precisely explaining variation in rates of return across assets. Let’s review some of the evidence on this score. 240

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The CAPM was first published by Sharpe in the Journal of Finance (the journal of the American Finance Association) in 1964 and took the world of finance by storm. Early tests by Black, Jensen, and Scholes (1972) and Fama and MacBeth (1973) were only partially supportive of the CAPM: average returns were higher for higher-beta portfolios, but the reward for beta risk was less than the predictions of the simple theory. While all this accumulating evidence against the CAPM remained largely within the ivory towers of academia, Roll’s (1977) paper “A Critique of Capital Asset Pricing Tests” shook the practitioner world as well. Roll argued that since the true market portfolio can never be observed, the CAPM is necessarily untestable. The publicity given the now classic “Roll’s critique” resulted in popular articles such as “Is Beta Dead?” that effectively slowed the permeation of portfolio theory through the world of finance.5 This is quite ironic since, although Roll is absolutely correct on theoretical grounds, some tests suggest that the error introduced by using a broad market index as proxy for the true, unobserved market portfolio is perhaps the lesser of the problems involved in testing the CAPM. Fama and French (1992) published a study that dealt the CAPM an even harsher blow. They claimed that once you control for a set of widely followed characteristics of the firm, such as the size of the firm and its ratio of market value to book value, the firm’s beta (that is, its systematic risk) does not contribute anything to the prediction of future returns. This time, the piece was picked up by The Economist and the New York Times (see the nearby box) even before it was published in the Journal of Finance. Fama and French and several others have published many follow-up studies of this topic. We will review some of this literature in the next chapter. However, it seems clear from these studies that beta does not tell the whole story of risk. There seem to be risk factors that affect security returns beyond beta’s one-dimensional measurement of market sensitivity. In fact, in the next section of this chapter, we will introduce a theory of risk premiums that explicitly allows for multiple risk factors. Liquidity, a different kind of risk factor, has been ignored for a long time. Although first analyzed by Amihud and Mendelson as early as 1986, it is yet to be accurately measured and incorporated in portfolio management. Measuring liquidity and the premium commensurate with illiquidity is part of a larger field in financial economics, namely, market structure. We now know that trading mechanisms on stock exchanges affect the liquidity of assets traded on these exchanges and thus significantly affect their market value. Despite all these issues, beta is not dead. Other research shows that when we use a more inclusive proxy for the market portfolio than the S&P 500 (specifically, an index that includes human capital) and allow for the fact that beta changes over time, the performance of beta in explaining security returns is considerably enhanced (Jagannathan and Wang, 1996). We know that the CAPM is not a perfect model and that ultimately it will be far from the last word on security pricing. Still, the logic of the model is compelling, and more sophisticated models of security pricing all rely on the key distinction between systematic versus diversifiable risk. The CAPM therefore provides a useful framework for thinking rigorously about the relationship between security risk and return. This is as much as Copernicus had when he was shown the prepublication version of his book just before he passed away.

7.5

ARBITRAGE PRICING THEORY

In the 1970s, as researchers were working on test methodologies for variants of the CAPM, Stephen Ross (1976) stunned the world of finance with the arbitrage pricing theory (APT). 5

A. Wallace, “Is Beta Dead?” Institutional Investor 14 (July 1980), pp. 22–30.

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Moving away from construction of mean-variance efficient portfolios, Ross instead calculated relations among expected rates of return that would rule out riskless profits by any investor in well-functioning capital markets. This generated a theory of risk and return similar to the CAPM.

Arbitrage Opportunities and Profits arbitrage Creation of riskless profits made possible by relative mispricing among securities.

zero-investment portfolio A portfolio of zero net value, established by buying and shorting component securities, usually in the context of an arbitrage strategy.

To explain the APT, we begin with the concept of arbitrage, which is the exploitation of relative mispricing among two or more securities to earn risk-free economic profits. A riskless arbitrage opportunity arises when an investor can construct a zero-investment portfolio that will yield a sure profit. Zero investment means investors need not use any of their own money. To construct a zero-investment portfolio, one has to be able to sell short at least one asset and use the proceeds to purchase (go long) one or more assets. Even a small investor, using borrowed money in this fashion, can take a large position in such a portfolio. An obvious case of an arbitrage opportunity arises in the violation of the law of one price: When an asset is trading at different prices in two markets (and the price differential exceeds transaction costs), a simultaneous trade in the two markets will produce a sure profit (the net price differential) without any net investment. One simply sells short the asset in the highpriced market and buys it in the low-priced market. The net proceeds are positive, and there is no risk because the long and short positions offset each other. In modern markets with electronic communications and instantaneous execution, such opportunities have become rare but not extinct. The same technology that enables the market to absorb new information quickly also enables fast operators to make large profits by trading huge volumes at the instant an arbitrage opportunity opens. This is the essence of program trading and index arbitrage, to be discussed in Part Five. From the simple case of a violation of the law of one price, let us proceed to a less obvious (yet just as profitable) arbitrage opportunity. Imagine that four stocks are traded in an economy with only four possible scenarios. The rates of return on the four stocks for each inflation-interest rate scenario appear in Table 7.10. The current prices of the stocks and rate of return statistics are shown in Table 7.11. The rate of return data give no immediate clue to any arbitrage opportunity lurking in this set of investments. The expected returns, standard deviations, and correlations do not reveal any abnormality to the naked eye. Consider, however, an equally weighted portfolio of the first three stocks (Apex, Bull, and Crush), and contrast its possible future rates of return with those of the fourth stock, Dreck. We do this in Table 7.12. Table 7.12 reveals that in all four scenarios, the equally weighted portfolio will outperform Dreck. The rate of return statistics of the two alternatives are Mean

Standard Deviation

Three-stock portfolio

25.83

6.40

Dreck

22.25

8.58

Correlation 0.94

The two investments are not perfectly correlated and are not perfect substitutes. Nevertheless, the equally weighted portfolio will fare better under any circumstances. Any investor, no matter how risk averse, can take advantage of this dominance by taking a short position in Dreck and using the proceeds to purchase the equally weighted portfolio. Let us see how it would work.

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Probability: Stock Apex (A) Bull (B) Crush (C ) Dreck (D)

TA B L E 7.11 Rate of return statistics

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High Real Interest Rates

TA B L E 7.10 Rate of return projections

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Low Real Interest Rates

High Inflation

Low Inflation

High Inflation

Low Inflation

0.25

0.25

0.25

0.25

⫺20 0 90 15

20 70 ⫺20 23

40 30 ⫺10 15

60 ⫺20 70 36

Correlation Matrix

Stock

Current Price

Expected Return (%)

Standard Deviation (%)

A

B

C

D

A B C D

$10 10 10 10

25.0% 20.0 32.5 22.25

29.58% 33.91 48.15 8.58

1.00 ⫺0.15 ⫺0.29 0.68

⫺0.15 1.00 ⫺0.87 ⫺0.38

⫺0.29 ⫺0.87 1.00 0.22

0.68 ⫺0.38 0.22 1.00

TA B L E 7.12 Rate of return projections

Equally weighted portfolio: A, B, and C Dreck (D)

High Real Interest Rates

Low Real Interest Rates

Rate of Inflation

Rate of Inflation

High

Low

High

Low

23.33 15.00

23.33 23.00

20.00 15.00

36.67 36.00

Suppose we sell short 300,000 shares of Dreck and use the $3 million proceeds to buy 100,000 shares each of Apex, Bull, and Crush. The dollar profits in each of the four scenarios will be as follows. High Real Interest Rates

Low Real Interest Rates

Inflation Rate

Inflation Rate

Stock

Dollar Investment

High

Low

High

Low

Apex Bull Crush Dreck

$ 1,000,000 1,000,000 1,000,000 ⫺3,000,000

$⫺200,000 0 900,000 ⫺450,000

$ 200,000 700,000 ⫺200,000 ⫺690,000

$ 400,000 300,000 ⫺100,000 ⫺450,000

$

600,000 ⫺200,000 700,000 ⫺1,080,000

Portfolio

$

$ 250,000

$

$ 150,000

$

20,000

0

10,000

The first column verifies that the net investment in our portfolio is zero. Yet this portfolio yields a positive profit in all scenarios. It is therefore a money machine. Investors will want to

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take an infinite position in such a portfolio, for larger positions entail no risk of losses yet yield ever-growing profits.6 In principle, even a single investor would take such large positions that the market would react to the buying and selling pressure: The price of Dreck would come down, and/or the prices of Apex, Bull, and Crush would go up. The pressure would persist until the arbitrage opportunity was eliminated.

Concept CHECK

>

5. Suppose Dreck’s price starts falling without any change in its per-share dollar payoffs. How far must the price fall before arbitrage between Dreck and the equally weighted portfolio is no longer possible? (Hint: Account for the amount of the equally weighted portfolio that can be purchased with the proceeds of the short sale as Dreck’s price falls.) The critical property of an arbitrage portfolio is that any investor, regardless of risk aversion or wealth, will want to take an infinite position in it so that profits will be driven to an infinite level. Because those large positions will force some prices up and/or some down until the opportunity vanishes, we can derive restrictions on security prices that satisfy the condition that no arbitrage opportunities are left in the marketplace. The idea that equilibrium market prices ought to be rational in the sense that they rule out arbitrage opportunities is perhaps the most fundamental concept in capital market theory. Violation of this principle would indicate the grossest form of market irrationality. There is an important distinction between arbitrage and CAPM risk-versus-return dominance arguments in support of equilibrium price relationships. A dominance argument, as in the CAPM, holds that when an equilibrium price relationship is violated, many investors will make portfolio changes. Each individual investor will make a limited change, though, depending on wealth and degree of risk aversion. Aggregation of these limited portfolio changes over many investors is required to create a large volume of buying and selling, which restores equilibrium prices. When arbitrage opportunities exist, by contrast, each investor wants to take as large a position as possible; in this case, it will not take many investors to bring about the price pressures necessary to restore equilibrium. Implications derived from the no-arbitrage argument, therefore, are stronger than implications derived from a risk-versus-return dominance argument, because they do not depend on a large, well-educated population of investors. The CAPM argues that all investors hold mean-variance efficient portfolios. When a security (or a bundle of securities) is mispriced, investors will tilt their portfolios toward the underpriced and away from the overpriced securities. The resulting pressure on prices comes from many investors shifting their portfolios, each by a relatively small dollar amount. The assumption that a large number of investors are mean-variance optimizers, is critical; in contrast, even few arbitrageurs will mobilize large dollar amounts to take advantage of an arbitrage opportunity.

arbitrage pricing theory (APT) A theory of risk-return relationships derived from no-arbitrage considerations in large capital markets

Well-Diversified Portfolios and the Arbitrage Pricing Theory The arbitrage opportunity described in the previous section is further obscured by the fact that it is almost always impossible to construct a precise scenario analysis for individual stocks that would uncover an event of such straightforward mispricing. Using the concept of well-diversified portfolios, the arbitrage pricing theory, or APT, resorts to statistical modeling to attack the problem more systematically. By showing that 6

We have described pure arbitrage: the search for a costless sure profit. Practitioners often use the terms arbitrage and arbitrageurs more loosely. An arbitrageur may be a professional searching for mispriced securities in specific areas such as merger-target stocks, rather than one looking for strict (risk-free) arbitrage opportunities in the sense that no loss is possible. The search for mispriced securities is called risk arbitrage to distinguish it from pure arbitrage.

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mispriced portfolios would give rise to arbitrage opportunities, the APT arrives at an expected return–beta relationship for portfolios identical to that of the CAPM. In the next section, we will compare and contrast the two theories. In its simple form, just like the CAPM, the APT posits a single-factor security market. Thus, the excess rate of return on each security, Ri ⫽ ri ⫺ rf, can be represented by Ri ⫽ ␣i ⫹ iRM ⫹ e

(7.5)

where alpha, ␣i, and beta, i, are known, and where we treat RM as the single factor. Suppose now that we construct a highly diversified portfolio with a given beta. If we use enough securities to form the portfolio, the resulting diversification will strip the portfolio of nonsystematic risk. Because such a well-diversified portfolio has for all practical purposes zero firm-specific risk, we can write its returns as RP ⫽ ␣P ⫹ PRM

(7.6)

(This portfolio is risky, however, because the excess return on the index, RM, is random.) Figure 7.11 illustrates the difference between a single security with a beta of 1.0 and a welldiversified portfolio with the same beta. For the portfolio (Panel A), all the returns plot exactly on the security characteristic line. There is no dispersion around the line, as in Panel B, because the effects of firm-specific events are eliminated by diversification. Therefore, in Equation 7.6, there is no residual term, e. Notice that Equation 7.6 implies that if the portfolio beta is zero, then RP ⫽ ␣P. This implies a riskless rate of return: There is no firm-specific risk because of diversification and no factor risk because beta is zero. Remember, however, that R denotes excess returns. So the equation implies that a portfolio with a beta of zero has a riskless excess return of ␣P, that is, a return higher than the risk-free rate by the amount ␣P. But this implies that ␣P must equal zero, or else an immediate arbitrage opportunity opens up. For example, if ␣P is greater than zero, you can borrow at the risk-free rate and use the proceeds to buy the well-diversified zero-beta portfolio. You borrow risklessly at rate rf and invest risklessly at rate rf ⫹ ␣P, clearing the riskless differential of ␣P.

Return (%)

10

0

A: Well-diversified portfolio

Security characteristic lines

A portfolio sufficiently diversified that nonsystematic risk is negligible.

Return (%)

10

F I G U R E 7.11

well-diversified portfolio

RM

0

B: Single stock

RM

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7.8 EXAMPLE Arbitrage with a Zero-Beta Portfolio

Suppose that the risk-free rate is 6%, and a well-diversified zero-beta portfolio earns (a sure) rate of return of 7%, that is, an excess return of 1%. Then borrow at 6% and invest in the zerobeta portfolio to earn 7%. You will earn a sure profit of 1% of the invested funds without putting up any of your own money. If the zero-beta portfolio earns 5%, then you can sell it short and lend at 6% with the same result.

In fact, we can go further and show that the alpha of any well-diversified portfolio in Equation 7.6 must be zero, even if the beta is not zero. The proof is similar to the easy zero-beta case. If the alphas were not zero, then we could combine two of these portfolios into a zerobeta riskless portfolio with a rate of return not equal to the risk-free rate. But this, as we have just seen, would be an arbitrage opportunity. To see how the arbitrage strategy would work, suppose that portfolio V has a beta of v and an alpha of ␣v. Similarly, suppose portfolio U has a beta of u and an alpha of ␣u. Taking advantage of any arbitrage opportunity involves buying and selling assets in proportions that create a risk-free profit on a costless position. To eliminate risk, we buy portfolio V and sell portfolio U in proportions chosen so that the combination portfolio (V ⫹ U) will have a beta of zero. The portfolio weights that satisfy this condition are wv ⫽

⫺u v ⫺ u

wu ⫽

v v ⫺ u

Note that wv plus wu add up to 1.0 and that the beta of the combination is in fact zero: Beta(V ⫹ U) ⫽ v

⫺u v ⫹ u ⫽0 v ⫺ u v ⫺ u

Therefore, the portfolio is riskless: It has no sensitivity to the factor. But the excess return of the portfolio is not zero unless ␣v and ␣u equal zero. R(V ⫹ U) ⫽ ␣v

⫺u v ⫹ ␣u ⫽0 v ⫺ u v ⫺ u

Therefore, unless ␣v and ␣u equal zero, the zero-beta portfolio has a certain rate of return that differs from the risk-free rate (its excess return is different from zero). We have seen that this gives rise to an arbitrage opportunity.

7.9 EXAMPLE Arbitrage with Mispriced Portfolios

Suppose that the risk-free rate is 7% and a well-diversified portfolio, V, with beta of 1.3 has an alpha of 2% and another well-diversified portfolio, U, with beta of 0.8 has an alpha of 1%. We go long on V and short on U with proportions 1.3 ⫺0.8 wv ⫽ ⫽ ⫺1.6 wu ⫽ ⫽ 2.6 1.3 ⫺ 0.8 1.3 ⫺ 0.8 These proportions add up to 1.0 and result in a portfolio with beta ⫽ ⫺1.6 ⫻ 1.3 ⫹ 2.6 ⫻ 0.8 ⫽ 0. The alpha of the portfolio is: ⫺1.6 ⫻ 2% ⫹ 2.6 ⫻ 1% ⫽ ⫺0.6%. This means that the riskless portfolio will earn a rate of return that is less than the risk-free rate by .6%. We now complete the arbitrage by selling (or going short on) the combination portfolio and investing the proceeds at 7%, risklessly profiting by the 60 basis point differential in returns.

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We conclude that the only value for alpha that rules out arbitrage opportunities is zero. Therefore, rewrite Equation 7.6 setting alpha equal to zero RP ⫽ PRM rP ⫺ rf ⫽ P(rM ⫺ rf) E(rP) ⫽ rf ⫹ P[E(rM) ⫺ rf ] Hence, we arrive at the same expected return–beta relationship as the CAPM without any assumption about either investor preferences or access to the all-inclusive (and elusive) market portfolio.

The APT and the CAPM Why did we need so many restrictive assumptions to derive the CAPM when the APT seems to arrive at the expected return–beta relationship with seemingly fewer and less objectionable assumptions? The answer is simple: The APT applies only to well-diversified portfolios. Absence of riskless arbitrage alone cannot guarantee that, in equilibrium, the expected return–beta relationship will hold for any and all assets. With additional effort, however, one can use the APT to show that the relationship must hold approximately even for individual assets. The essence of the proof is that if the expected return–beta relationship were violated by many individual securities, it would be virtually impossible for all well-diversified portfolios to satisfy the relationship. So the relationship must almost surely hold true for individual securities. We say “almost” because, according to the APT, there is no guarantee that all individual assets will lie on the SML. If only a few securities violated the SML, their effect on welldiversified portfolios could conceivably be offsetting. In this sense, it is possible that the SML relationship is violated for single securities. If many securities violate the expected return–beta relationship, however, the relationship will no longer hold for well-diversified portfolios comprising these securities, and arbitrage opportunities will be available. The APT serves many of the same functions as the CAPM. It gives us a benchmark for fair rates of return that can be used for capital budgeting, security evaluation, or investment performance evaluation. Moreover, the APT highlights the crucial distinction between nondiversifiable risk (systematic or factor risk) that requires a reward in the form of a risk premium and diversifiable risk that does not. The bottom line is that neither of these theories dominates the other. The APT is more general in that it gets us to the expected return–beta relationship without requiring many of the unrealistic assumptions of the CAPM, particularly the reliance on the market portfolio. The latter improves the prospects for testing the APT. But the CAPM is more general in that it applies to all assets without reservation. The good news is that both theories agree on the expected return–beta relationship. It is worth noting that because past tests of the expected return–beta relationship examined the rates of return on highly diversified portfolios, they actually came closer to testing the APT than the CAPM. Thus, it appears that econometric concerns, too, favor the APT.

Multifactor Generalization of the APT and CAPM We’ve assumed all along that there is only one systematic factor affecting stock returns. This assumption may be too simplistic. It is easy to think of several factors that might affect stock returns: business cycles, interest rate fluctuations, inflation rates, oil prices, and so on. Presumably, exposure to any of these factors singly or together will affect a stock’s perceived

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riskiness and appropriate expected rate of return. We can use a multifactor version of the APT to accommodate these multiple sources of risk. Suppose we generalize the single-factor model expressed in Equation 7.5 to a two-factor model: Ri ⫽ ␣i ⫹ i1RM1 ⫹ i2RM2 ⫹ ei

factor portfolio A well-diversified portfolio constructed to have a beta of 1.0 on one factor and a beta of zero on any other factor.

(7.7)

where RM1 and RM2 are the excess returns on portfolios that represent the two systematic factors. Factor 1 might be, for example, unanticipated changes in industrial production, while factor 2 might represent unanticipated changes in short-term interest rates. We assume again that there are many securities available with any combination of betas. This implies that we can form well-diversified factor portfolios, that is, portfolios that have a beta of 1.0 on one factor and a beta of zero on all others. Thus, a factor portfolio with a beta of 1.0 on the first factor will have a rate of return of RM1; a factor portfolio with a beta of 1.0 on the second factor will have a rate of return of RM2; and so on. Factor portfolios can serve as the benchmark portfolios for a multifactor generalization of the security market line relationship. Suppose the two-factor portfolios, here called portfolios 1 and 2, have expected returns E(r1) ⫽ 10% and E(r2) ⫽ 12%. Suppose further that the risk-free rate is 4%. The risk premium on the first factor portfolio is therefore 6%, while that on the second factor portfolio is 8%. Now consider an arbitrary well-diversified portfolio (A), with beta on the first factor, A1 ⫽ 0.5, and on the second factor, A2 ⫽ 0.75. The multifactor APT states that the portfolio risk premium must equal the sum of the risk premiums required as compensation to investors for each source of systematic risk. The risk premium attributable to risk factor 1 is the portfolio’s exposure to factor 1, A1, times the risk premium earned on the first factor portfolio, E(r1) ⫺ rf . Therefore, the portion of portfolio A’s risk premium that is compensation for its exposure to the first risk factor is A1[E(r1) ⫺ rf ] ⫽ 0.5 (10% ⫺ 4%) ⫽ 3%, while the risk premium attributable to risk factor 2 is A2[E(r2) ⫺ rf ] ⫽ 0.75 (12% ⫺ 4%) ⫽ 6%. The total risk premium on the portfolio, therefore, should be 3 ⫹ 6 ⫽ 9%, and the total return on the portfolio should be 13%. 4%

Risk-free rate

⫹ 3%

Risk premium for exposure to factor 1

⫹ 6%

Risk premium for exposure to factor 2

13%

Total expected return

To generalize this argument, note that the factor exposure of any portfolio P is given by its betas, P1 and P2. A competing portfolio, Q, can be formed from factor portfolios with the following weights: P1 in the first factor portfolio; P2 in the second factor portfolio; and 1 ⫺ P2 ⫺ P2 in T-bills. By construction, Q will have betas equal to those of portfolio P and an expected return of E(rQ) ⫽ P1E(r1) ⫹ P2E(r2) ⫹ (1 ⫺ P1 ⫺ P2)rf ⫽ rf ⫹ P1[E(r1) ⫺ rf ] ⫹ P2[E(r2) ⫺ rf ]

(7.8)

Using our numbers, E(rQ) ⫽ 4 ⫹ .5 ⫻ (10 ⫺ 4) ⫹ .75 ⫻ (12 ⫺ 4) ⫽ 13% Because portfolio Q has precisely the same exposures as portfolio A to the two sources of risk, their expected returns also ought to be equal. So portfolio A also ought to have an expected return of 13%.

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E XCEL Applications

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Estimating the Index Model

The spreadsheet below (available at www.mhhe.com/bkm) also contains monthly returns for the stocks that comprise the Dow Jones Industrial Average. The spreadsheet contains workbooks that show raw returns, risk premiums, correlation coefficients, and beta coefficients for the stocks that are in the DJIA. The security characteristic lines are estimated with five years of monthly returns.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

A B SUMMARY OUTPUT AXP

C

D

E

F

G

H

I

Regression Statistics Multiple R 0.69288601 R Square 0.48009103 Adjusted R Square 0.47112708 Standard Error 0.05887426 Observations 60 ANOVA

df Regression Residual Total

Intercept X Variable 1

SS MS F Significance F 1 0.185641557 0.1856416 53.55799 8.55186E-10 58 0.201038358 0.0034662 59 0.386679915

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 0.01181687 0.00776211 1.522379 0.133348 ⫺0.003720666 0.027354414 ⫺0.0037207 0.02735441 1.20877413 0.165170705 7.3183324 8.55E-10 0.878149288 1.539398969 0.87814929 1.53939897

Suppose, however, that the expected return on portfolio A is 12% rather than 13%. This return would give rise to an arbitrage opportunity. Form a portfolio from the factor portfolios with the same betas as portfolio A. This requires weights of 0.5 on the first factor portfolio, 0.75 on the second portfolio, and ⫺ 0.25 on the risk-free asset. This portfolio has exactly the same factor betas as portfolio A: a beta of 0.5 on the first factor because of its 0.5 weight on the first factor portfolio and a beta of 0.75 on the second factor. Now invest $1 in portfolio Q and sell (short) $1 in portfolio A. Your net investment is zero, but your expected dollar profit is positive and equal to $1 ⫻ E(rQ) ⫺ $1 ⫻ E(rA) ⫽ $1 ⫻ .13 ⫺ $1 ⫻ .12 ⫽ $.01. Moreover, your net position is riskless. Your exposure to each risk factor cancels out because you are long $1 in portfolio Q and short $1 in portfolio A, and both of these well-diversified portfolios have exactly the same factor betas. Thus, if portfolio A’s expected return differs from that of portfolio Q’s, you can earn positive risk-free profits on a zero net investment position. This is an arbitrage opportunity. Hence, any well-diversified portfolio with betas P1 and P2 must have the return given in Equation 7.8 if arbitrage opportunities are to be ruled out. A comparison of Equations 7.2 and 7.8 shows that 7.8 is simply a generalization of the one-factor SML. Finally, extension of the multifactor SML of Equation 7.8 to individual assets is precisely the same as for the one-factor APT. Equation 7.8 cannot be satisfied by every well-diversified portfolio unless it is satisfied by virtually every security taken individually. Equation 7.8 thus represents the multifactor SML for an economy with multiple sources of risk. 249

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The generalized APT must be qualified with respect to individual assets just as in the single-factor case. A multifactor CAPM would, at the cost of additional assumptions, apply to any and all individual assets. As we have seen, the result will be a security market equation (a multidimensional SML) that is identical to that of the multifactor APT.

>

6. Using the factor portfolios just considered, find the fair rate of return on a security with 1 ⴝ 0.2 and 2 ⴝ 1.4.

SUMMARY

• The CAPM assumes investors are rational, single-period planners who agree on a common input list from security analysis and seek mean-variance optimal portfolios. • The CAPM assumes ideal security markets in the sense that: (a) markets are large and investors are price takers, (b) there are no taxes or transaction costs, (c) all risky assets are publicly traded, and (d) any amount can be borrowed and lent at a fixed, risk-free rate. • These assumptions mean that all investors will hold identical risky portfolios. The CAPM implies that, in equilibrium, the market portfolio is the unique mean-variance efficient tangency portfolio, which indicates that a passive strategy is efficient. • The market portfolio is a value-weighted portfolio. Each security is held in a proportion equal to its market value divided by the total market value of all securities. The risk premium on the market portfolio is proportional to its variance, M2 , and to the risk aversion of the average investor. • The CAPM implies that the risk premium on any individual asset or portfolio is the product of the risk premium of the market portfolio and the asset’s beta. The security market line shows the return demanded by investors as a function of the beta of their investment. This expected return is a benchmark for evaluating investment performance. • In a single-index security market, once an index is specified, a security beta can be estimated from a regression of the security’s excess return on the index’s excess return. This regression line is called the security characteristic line (SCL). The intercept of the SCL, called alpha, represents the average excess return on the security when the index excess return is zero. The CAPM implies that alphas should be zero. • An arbitrage opportunity arises when the disparity between two or more security prices enables investors to construct a zero net investment portfolio that will yield a sure profit. Rational investors will want to take infinitely large positions in arbitrage portfolios regardless of their degree of risk aversion. • The presence of arbitrage opportunities and the resulting volume of trades will create pressure on security prices that will persist until prices reach levels that preclude arbitrage. Only a few investors need to become aware of arbitrage opportunities to trigger this process because of the large volume of trades in which they will engage. • When securities are priced so that there are no arbitrage opportunities, the market satisfies the no-arbitrage condition. Price relationships that satisfy the no-arbitrage condition are important because we expect them to hold in real-world markets. • Portfolios are called well diversified if they include a large number of securities in such proportions that the residual or diversifiable risk of the portfolio is negligible. • In a single-factor security market, all well-diversified portfolios must satisfy the expected return–beta relationship of the SML in order to satisfy the no-arbitrage condition. • If all well-diversified portfolios satisfy the expected return–beta relationship, then all but a small number of securities also must satisfy this relationship.

Concept

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CHECK

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• The APT implies the same expected return–beta relationship as the CAPM, yet does not require that all investors be mean-variance optimizers. The price of this generality is that the APT does not guarantee this relationship for all securities at all times. • A multifactor APT generalizes the single-factor model to accommodate several sources of systematic risk. expected return–beta relationship, 225 factor portfolio, 248 market portfolio, 221 mutual fund theorem, 223 security characteristic line (SCL), 231

security market line (SML), 226 well-diversified portfolio, 245 zero-investment portfolio, 242

1. Which of the following statements about the security market line (SML) are true? a. The SML provides a benchmark for evaluating expected investment performance. b. The SML leads all investors to invest in the same portfolio of risky assets. c. The SML is a graphic representation of the relationship between expected return and beta. d. Properly valued assets plot exactly on the SML. 2. Risk aversion has all of the following implications for the investment process except: a. The security market line is upward sloping. b. The promised yield on AAA-rated bonds is higher than on A-rated bonds. c. Investors expect a positive relationship between expected return and risk. d. Investors prefer portfolios that lie on the efficient frontier to other portfolios with equal expected rates of return. 3. What is the beta of a portfolio with E(rP) ⫽ 20%, if rf ⫽ 5% and E(rM) ⫽ 15%? 4. The market price of a security is $40. Its expected rate of return is 13%. The risk-free rate is 7%, and the market risk premium is 8%. What will the market price of the security be if its beta doubles (and all other variables remain unchanged)? Assume the stock is expected to pay a constant dividend in perpetuity. 5. You are a consultant to a large manufacturing corporation considering a project with the following net after-tax cash flows (in millions of dollars) Years from Now

After-Tax CF

0 1–9 10

⫺20 10 20

The project’s beta is 1.7. Assuming rf ⫽ 9% and E(rM) ⫽ 19%, what is the net present value of the project? What is the highest possible beta estimate for the project before its NPV becomes negative? 6. Are the following statements true or false? Explain. a. Stocks with a beta of zero offer an expected rate of return of zero. b. The CAPM implies that investors require a higher return to hold highly volatile securities. c. You can construct a portfolio with a beta of 0.75 by investing 0.75 of the budget in T-bills and the remainder in the market portfolio.

KEY TERMS

PROBLEM SETS

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alpha, 227 arbitrage, 242 arbitrage pricing theory (APT), 244 capital asset pricing model (CAPM), 221

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7. Consider the following table, which gives a security analyst’s expected return on two stocks for two particular market returns: Market Return

Aggressive Stock

Defensive Stock

5% 20

2% 32

3.5% 14

a. What are the betas of the two stocks? b. What is the expected rate of return on each stock if the market return is equally likely to be 5% or 20%? c. If the T-bill rate is 8%, and the market return is equally likely to be 5% or 20%, draw the SML for this economy. d. Plot the two securities on the SML graph. What are the alphas of each? e. What hurdle rate should be used by the management of the aggressive firm for a project with the risk characteristics of the defensive firm’s stock? If the simple CAPM is valid, which of the situations in problems 8–14 below are possible? Explain. Consider each situation independently. 8. Portfolio

Expected Return

Beta

A B

20% 25

1.4 1.2

9. Portfolio

Expected Return

Standard Deviation

A B

30% 40

35% 25

Portfolio

Expected Return

Standard Deviation

Risk-free Market A

10% 18 16

0% 24 12

Portfolio

Expected Return

Standard Deviation

Risk-free Market A

10% 18 20

0% 24 22

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10.

11.

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Portfolio

Expected Return

Beta

Risk-free Market A

10% 18 16

0 1.0 1.5

Portfolio

Expected Return

Beta

Risk-free Market A

10% 18 16

0 1.0 .9

13.

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Portfolio

Expected Return

Standard Deviation

Risk-free Market A

10% 18 16

0% 24 22

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15. A share of stock is now selling for $100. It will pay a dividend of $9 per share at the end of the year. Its beta is 1.0. What do investors expect the stock to sell for at the end of the year? 16. I am buying a firm with an expected perpetual cash flow of $1,000 but am unsure of its risk. If I think the beta of the firm is zero, when the beta is really 1.0, how much more will I offer for the firm than it is truly worth? 17. A stock has an expected return of 6%. What is its beta? 18. Two investment advisers are comparing performance. One averaged a 19% return and the other a 16% return. However, the beta of the first adviser was 1.5, while that of the second was 1.0. a. Can you tell which adviser was a better selector of individual stocks (aside from the issue of general movements in the market)? b. If the T-bill rate were 6%, and the market return during the period were 14%, which adviser would be the superior stock selector? c. What if the T-bill rate were 3% and the market return 15%? 19. In 2002, the yield on short-term government securities (perceived to be risk-free) was about 4%. Suppose the expected return required by the market for a portfolio with a beta of 1.0 is 12%. According to the capital asset pricing model: a. What is the expected return on the market portfolio? b. What would be the expected return on a zero-beta stock? c. Suppose you consider buying a share of stock at a price of $40. The stock is expected to pay a dividend of $3 next year and to sell then for $41. The stock risk has been evaluated at  ⫽ ⫺0.5. Is the stock overpriced or underpriced?

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In problems 15–17 below, assume the risk-free rate is 8% and the expected rate of return on the market is 18%.

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20. Based on current dividend yields and expected capital gains, the expected rates of return on portfolio A and B are 11% and 14%, respectively. The beta of A is 0.8 while that of B is 1.5. The T-bill rate is currently 6%, while the expected rate of return of the S&P 500 Index is 12%. The standard deviation of portfolio A is 10% annually, while that of B is 31%, and that of the index is 20%. a. If you currently hold a market index portfolio, would you choose to add either of these portfolios to your holdings? Explain. b. If instead you could invest only in bills and one of these portfolios, which would you choose? 21. Consider the following data for a one-factor economy. All portfolios are well diversified. Portfolio

E(r)

Beta

A F

10% 4

1.0 0

Suppose another portfolio E is well diversified with a beta of 2/3 and expected return of 9%. Would an arbitrage opportunity exist? If so, what would the arbitrage strategy be? 22. Following is a scenario for three stocks constructed by the security analysts of PF Inc.

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Scenario Rate of Return (%) Stock

Price ($)

Recession

Average

Boom

A B C

10 15 50

⫺15 25 12

20 10 15

30 ⫺10 12

a. Construct an arbitrage portfolio using these stocks. b. How might these prices change when equilibrium is restored? Give an example where a change in stock C’s price is sufficient to restore equilibrium, assuming the dollar payoffs to stock C remain the same. 23. Assume both portfolios A and B are well diversified, that E(rA) ⫽ 14% and E(rB) ⫽ 14.8%. If the economy has only one factor, and A ⫽ 1.0 while B ⫽ 1.1, what must be the risk-free rate? 24. Assume a market index represents the common factor, and all stocks in the economy have a beta of 1.0. Firm-specific returns all have a standard deviation of 30%. Suppose an analyst studies 20 stocks and finds that one-half have an alpha of 3%, and one-half have an alpha of ⫺3%. The analyst then buys $1 million of an equally weighted portfolio of the positive alpha stocks and sells short $1 million of an equally weighted portfolio of the negative alpha stocks. a. What is the expected profit (in dollars), and what is the standard deviation of the analyst’s profit? b. How does your answer change if the analyst examines 50 stocks instead of 20? 100 stocks? 25. If the APT is to be a useful theory, the number of systematic factors in the economy must be small. Why?

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Portfolio

Beta on M1

Beta on M2

Expected Return (%)

A B

1.8 2.0

2.1 ⫺0.5

40 10

What is the expected return–beta relationship in this economy? 29. The security market line depicts: a. A security’s expected return as a function of its systematic risk. b. The market portfolio as the optimal portfolio of risky securities. c. The relationship between a security’s return and the return on an index. d. The complete portfolio as a combination of the market portfolio and the risk-free asset. 30. Within the context of the capital asset pricing model (CAPM), assume: • Expected return on the market ⫽ 15%. • Risk-free rate ⫽ 8%. • Expected rate of return on XYZ security ⫽ 17%. • Beta of XYZ security ⫽ 1.25. Which one of the following is correct? a. XYZ is overpriced. b. XYZ is fairly priced. c. XYZ’s alpha is ⫺.25%. d. XYZ’s alpha is .25%. 31. What is the expected return of a zero-beta security? a. Market rate of return. b. Zero rate of return. d. Negative rate of return. d. Risk-free rate of return. 32. Capital asset pricing theory asserts that expected returns are best explained by: a. Economic factors b. Specific risk c. Systematic risk d. Diversification 33. According to CAPM, the expected rate of return of a portfolio with a beta of 1.0 and an alpha of 0 is: a. Between rM and rf . b. The risk-free rate, rf .

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26. The APT itself does not provide information on the factors that one might expect to determine risk premiums. How should researchers decide which factors to investigate? Is industrial production a reasonable factor to test for a risk premium? Why or why not? 27. Suppose two factors are identified for the U.S. economy: the growth rate of industrial production, IP, and the inflation rate, IR. IP is expected to be 4% and IR 6%. A stock with a beta of 1.0 on IP and 0.4 on IR currently is expected to provide a rate of return of 14%. If industrial production actually grows by 5%, while the inflation rate turns out to be 7%, what is your best guess for the rate of return on the stock? 28. Suppose there are two independent economic factors, M1 and M2. The risk-free rate is 7%, and all stocks have independent firm-specific components with a standard deviation of 50%. Portfolios A and B are both well diversified.

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c. (rM ⫺ rf). d. The expected return on the market, rM. The following table shows risk and return measures for two portfolios.

Portfolio

Average Annual Rate of Return

Standard Deviation

Beta

R S&P 500

11% 14%

10% 12%

0.5 1.0

34. When plotting portfolio R on the preceding table relative to the SML, portfolio R lies: a. On the SML. b. Below the SML. c. Above the SML. d. Insufficient data given. 35. When plotting portfolio R relative to the capital market line, portfolio R lies: a. On the CML. b. Below the CML. c. Above the CML. d. Insufficient data given. 36. Briefly explain whether investors should expect a higher return from holding portfolio A versus portfolio B under capital asset pricing theory (CAPM). Assume that both portfolios are fully diversified.

Systematic risk (beta) Specific risk for each individual security

Portfolio A

Portfolio B

1.0

1.0

High

Low

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37. Assume that both X and Y are well-diversified portfolios and the risk-free rate is 8%. Portfolio

Expected Return

Beta

X Y

16% 12%

1.00 0.25

In this situation you could conclude that portfolios X and Y: a. Are in equilibrium. b. Offer an arbitrage opportunity. c. Are both underpriced. d. Are both fairly priced. 38. According to the theory of arbitrage: a. High-beta stocks are consistently overpriced. b. Low-beta stocks are consistently overpriced. c. Positive alpha investment opportunities will quickly disappear. d. Rational investors will pursue arbitrage consistent with their risk tolerance.

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39. A zero-investment portfolio with a positive alpha could arise if: a. The expected return of the portfolio equals zero. b. The capital market line is tangent to the opportunity set. c. The law of one price remains unviolated. d. A risk-free arbitrage opportunity exists. 40. The APT differs from the single-factor CAPM because the APT: a. Places more emphasis on market risk. b. Minimizes the importance of diversification. c. Recognizes multiple unsystematic risk factors. d. Recognizes multiple systematic risk factors. 41. An investor takes as large a position as possible when an equilibrium price relationship is violated. This is an example of: a. A dominance argument. b. The mean-variance efficient frontier. c. Arbitrage activity. d. The capital asset pricing model. 42. The feature of APT that offers the greatest potential advantage over the simple CAPM is the: a. Identification of anticipated changes in production, inflation, and term structure of interest rates as key factors explaining the risk-return relationship. b. Superior measurement of the risk-free rate of return over historical time periods. c. Variability of coefficients of sensitivity to the APT factors for a given asset over time. d. Use of several factors instead of a single market index to explain the risk-return relationship. 43. In contrast to the capital asset pricing model, arbitrage pricing theory: a. Requires that markets be in equilibrium. b. Uses risk premiums based on micro variables. c. Specifies the number and identifies specific factors that determine expected returns. d. Does not require the restrictive assumptions concerning the market portfolio.

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STANDARD & POOR’S 1.

In the previous chapter, you used data from Market Insight to calculate the beta of Apple Computer (AAPL). Now let’s compute the alpha of the stock in two consecutive periods. Estimate the index model regression using the first two years of monthly data. (You can get monthly T-bill rates to calculate excess returns from the Federal Reserve website at http://www.federalreserve.gov/releases/h15/data. htm.) The intercept of the regression is Apple’s alpha over that 2-year period. Now repeat this exercise using the next two years of monthly data. This will give you alpha and beta estimates for two consecutive time periods. Finally, repeat this regression exercise for several (e.g., a dozen) other firms.

2.

Given your results for question 1, we can now investigate the extent to which beta in one period predicts beta in future periods and whether alpha in one period predicts alpha in future periods. Regress the beta of each firm in the second period against the beta in the first period. (If you estimated regressions for a dozen firms in question 1, you will have 12 observations in this regression.) Do the same for the alphas of each firm.

3.

We would expect that beta in the first period predicts beta in the next period, but that alpha in the first period has no power to predict alpha in the next period. (The regression coefficient on first-period beta will be statistically significant, but the coefficient on alpha will not be.) Why does this expectation make sense? Is it borne out by the data?

WEBMA STER Beta Coefficients

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Go to www.mhhe.com/edumarketinsight. Click on Monthly Valuation Data. The report summarizes seven months of data related to stock market activity and contains several comparison reports to the market indexes. Pull the monthly valuation data for General Electric, The Home Depot, Johnson and Johnson, Honeywell, and H.J. Heinz. After reviewing the reports, answer the following questions: 1.

Which of the firms are low-beta firms?

2.

Does the beta coefficient for these low-beta firms make sense given what type of firms they are? Briefly explain.

3.

Describe the variation in the reported beta coefficients over the seven months of data.

SOLUTIONS TO 1. The CML would still represent efficient investments. We can characterize the entire population by

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two representative investors. One is the “uninformed” investor, who does not engage in security analysis and holds the market portfolio, while the other optimizes using the Markowitz algorithm with input from security analysis. The uninformed investor does not know what input the informed investor uses to make portfolio purchases. The uninformed investor knows, however, that if the other investor is informed, the market portfolio proportions will be optimal. Therefore, to depart from these proportions would constitute an uninformed bet, which will, on average, reduce the efficiency of diversification with no compensating improvement in expected returns.

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2. Substituting the historical mean and standard deviation in Equation 7.1 yields a coefficient of risk aversion of A* ⫽

E(rM) ⫺ rf M2

⫽

.085 0.202

⫽ 2.1

This relationship also tells us that for the historical standard deviation and a coefficient of risk aversion of 3.5, the risk premium would be E(rM) ⫺ rf ⫽ A*M2 ⫽ 3.5 ⫻ 0.202 ⫽ 0.14 ⫽ 14% 3. Ford ⫽ 1.25, GM ⫽ 1.15. Therefore, given the investment proportions, the portfolio beta is P ⫽ wFordFord ⫹ wGMGM ⫽ (0.75 ⫻ 1.25) ⫹ (0.25 ⫻ 1.15) ⫽ 1.225 and the risk premium of the portfolio will be E(rP) ⫺ rf ⫽ P[E(rM) ⫺ rf] ⫽ 1.225 ⫻ 8% ⫽ 9.8% 4. a. The alpha of a stock is its expected return in excess of that required by the CAPM. ␣ ⫽ E(r) ⫺ {rf ⫹ [E(rM) ⫺ rf]} ␣XYZ ⫽ 12 ⫺ [5 ⫹ 1.0(11 ⫺ 5)] ⫽ 1 ␣ABC ⫽ 13 ⫺ [5 ⫹ 1.5(11 ⫺ 5)] ⫽ ⫺ 1% b. The project-specific required rate of return is determined by the project beta coupled with the market risk premium and the risk-free rate. The CAPM tells us that an acceptable expected rate of return for the project is rf ⫹ [E(rM) ⫺ rf] ⫽ 8 ⫹ 1.3(16 ⫺ 8) ⫽ 18.4% which becomes the project’s hurdle rate. If the IRR of the project is 19%, then it is desirable. Any project (of similar beta) with an IRR less than 18.4% should be rejected.

Stock

Dollar Investment

Apex Bull Crush Dreck

$

985,714 985,714 985,714 ⫺2,957,142

Total

$

Rate of Return (%)

Dollar Return

20 70 ⫺20 NA*

$ 197,143 690,000 ⫺197,143 ⫺690,000

0

$

0

*The dollar return on Dreck is assumed to be held fixed as its price falls. Therefore, Dreck’s rate of return will depend on the price to which its stock price falls, but in any case the rate of return is not necessary to answer the question.

At any price for Dreck stock below $10 ⫻ (1 ⫺ 1/70) ⫽ $9.857, profits will be negative, which means the arbitrage opportunity is eliminated. Note: $9.857 is not the equilibrium price of Dreck. It is simply the upper bound on Dreck’s price that rules out the simple arbitrage opportunity. 6. Using Equation 7.8, the expected return is 4 ⫹ (0.2 ⫻ 6) ⫹ (1.4 ⫻ 8) ⫽ 16.4%

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5. The least profitable scenario currently yields a profit of $10,000 and gross proceeds from the equally weighted portfolio of $700,000. As the price of Dreck falls, less of the equally weighted portfolio can be purchased from the proceeds of the short sale. When Dreck’s price falls by more than a factor of 10,000/700,000, arbitrage no longer will be feasible, because the profits in the worst state will be driven below zero. To see this, suppose Dreck’s price falls to $10 ⫻ (1 ⫺ 1/70). The short sale of 300,000 shares now yields $2,957,142, which allows dollar investments of only $985,714 in each of the other shares. In the high real interest rate, low inflation scenario, profits will be driven to zero.

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8 THE EFFICIENT MARKET HYPOTHESIS

AFTER STUDYING THIS CHAPTER YOU SHOULD BE ABLE TO:

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260

Demonstrate why security price movements should be essentially unpredictable. Cite evidence that supports and contradicts the efficient market hypothesis. Formulate investment strategies that make sense in informationally efficient markets.

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Related Websites http://www.efficientfrontier.com This site has an online journal entitled Efficient Frontier: An Online Journal of Practical Asset Allocation. The journal contains short articles related to assessment of strategies.

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http://my.zacks.com http://www.wsrn.com http://www.corporateinformation.com http://www.businessweek.com/investor

http://www.superstarinvestor.com/index.html

These sites contain information related to market efficiency issues surrounding individual stocks as well as mutual funds.

This site contains many references to other sites that have data on technical and fundamental analysis as well as sites containing information on earnings and investor conference calls.

http://www.newyorkfed.org http://www.frbsf.org http://www.bos.frb.org These sites contain research reports and shorter summaries of articles with information on various aspects of market efficiency.

ne of the early applications of computers in economics in the 1950s was to analyze economic time series. Business cycle theorists believed tracing the evolution of several economic variables over time would clarify and predict the progress of the economy through boom and bust periods. A natural candidate for analysis was the behavior of stock market prices over time. Assuming stock prices reflect the prospects of the firm, recurring patterns of peaks and troughs in economic performance ought to show up in those prices. Maurice Kendall (1953) was one of the first to examine this proposition. He found to his great surprise that he could identify no predictable patterns in stock prices. Prices seemed to evolve randomly. They were as likely to go up as they were to go down on any particular day regardless of past performance. The data provided no way to predict price movements. At first blush, Kendall’s results disturbed some financial economists. They seemed to imply that the stock market is dominated by erratic market psychology, or “animal spirits,” and that it follows no logical rules. In short, the results appeared to confirm the irrationality of the market. On further reflection, however, economists reversed their interpretation of Kendall’s study. It soon became apparent that random price movements indicated a wellfunctioning or efficient market, not an irrational one. In this chapter, we will explore the reasoning behind what may seem to be a surprising conclusion. We show how competition among analysts leads naturally to market efficiency, and we examine the implications of the efficient market hypothesis for investment policy. We also consider empirical evidence that supports and contradicts the notion of market efficiency.

O

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The notion that stock price changes are random and unpredictable.

efficient market hypothesis The hypothesis that prices of securities fully reflect available information about securities.

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8.1

random walk

II. Portfolio Theory

RANDOM WALKS AND THE EFFICIENT MARKET HYPOTHESIS

Suppose Kendall had discovered that stock prices are predictable. Imagine the gold mine for investors! If they could use Kendall’s equations to predict stock prices, investors would reap unending profits simply by purchasing stocks the computer model implied were about to increase in price and selling those stocks about to fall in price. A moment’s reflection should be enough to convince you that this situation could not persist for long. For example, suppose the model predicts with great confidence that XYZ’s stock price, currently at $100 per share, will rise dramatically in three days to $110. All investors with access to the model’s prediction would place a great wave of immediate buy orders to cash in on the prospective increase in stock price. No one in the know holding XYZ, however, would be willing to sell, and the net effect would be an immediate jump in the stock price to $110. The forecast of a future price increase leads instead to an immediate price increase. Another way of putting this is that the stock price will immediately reflect the “good news” implicit in the model’s forecast. This simple example illustrates why Kendall’s attempts to find recurring patterns in stock price movements were in vain. A forecast about favorable future performance leads instead to favorable current performance, as market participants all try to get in on the action before the price jump. More generally, one could say that any publicly available information that might be used to predict stock performance, including information on the macroeconomy, the firm’s industry, and its operations, plans, and management, should already be reflected in stock prices. As soon as there is any information indicating a stock is underpriced and offers a profit opportunity, investors flock to buy the stock and immediately bid up its price to a fair level, where again only ordinary rates of return can be expected. These “ordinary rates” are simply rates of return commensurate with the risk of the stock. But if prices are bid immediately to fair levels, given all available information, it must be that prices increase or decrease only in response to new information. New information, by definition, must be unpredictable; if it could be predicted, then that prediction would be part of today’s information! Thus, stock prices that change in response to new (unpredictable) information also must move unpredictably. This is the essence of the argument that stock prices should follow a random walk, that is, that price changes should be random and unpredictable. Far from being a proof of market irrationality, randomly evolving stock prices are the necessary consequence of intelligent investors competing to discover relevant information before the rest of the market becomes aware of that information. Don’t confuse randomness in price changes with irrationality in the level of prices. If prices are determined rationally, then only new information will cause them to change. Therefore, a random walk would be the natural consequence of prices that always reflect all current knowledge. Indeed, if stock price movements were predictable, that would be damning evidence of stock market inefficiency, because the ability to predict prices would indicate that all available information was not already impounded in stock prices. Therefore, the notion that stocks already reflect all available information is referred to as the efficient market hypothesis (EMH). Figure 8.1 illustrates the response of stock prices to new information in an efficient market. The graph plots the price response of a sample of 194 firms that were targets of takeover attempts. In most takeovers, the acquiring firm pays a substantial premium over current market prices. Therefore, announcement of a takeover attempt should cause the stock price to jump.

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The Efficient Market Hypothesis

F I G U R E 8.1

Cumulative abnormal return, % 36

Cumulative abnormal returns surrounding takeover attempts: Target companies. Returns are adjusted to net out effects of broad market movements.

32 28 24 20 16

Source: Arthur Keown and John Pinkerton, “Merger Announcements and Insider Trading Activity,” Journal of Finance 36 (September 1981).

12 8 4 0 ⫺4 ⫺8 ⫺12 ⫺16 ⫺135 ⫺120 ⫺105

263

⫺90 ⫺75 ⫺60 ⫺45 ⫺30 ⫺15 Days relative to announcement date

0

15

30

The figure shows that stock prices jump dramatically on the day the news becomes public. However, there is no further drift in prices after the announcement date, suggesting that prices reflect the new information, including the likely magnitude of the takeover premium, by the end of the trading day. An even more dramatic demonstration of the speed of price response appears in Figure 8.2. Suppose that you bought shares of firms announcing positive earnings surprises and sold short shares of firms with negative earnings surprises. (A positive surprise is defined as earnings that exceed the prior forecast published by the Value Line Investment Survey.) The figure tracks the average profits to this strategy for each half-hour period following the public announcement. The figure demonstrates that the vast majority of the profits to this strategy would be realized in the first half-hour following the announcement. Only 30 minutes after the public announcement, it is virtually too late to profitably trade on the information, suggesting that the market responds to the news within that short time period.

Competition as the Source of Efficiency Why should we expect stock prices to reflect all available information? After all, if you were to spend time and money gathering information, you would hope to turn up something that had been overlooked by the rest of the investment community. When information costs you money to uncover and analyze, you expect your investment analysis to result in an increased expected return. Investors will have an incentive to spend time and resources to analyze and uncover new information only if such activity is likely to generate higher investment returns. Therefore, in

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F I G U R E 8.2

25

Returns following earnings announcements

20

Note: Only the return in the first 30 minutes was statistically significantly different from that of a control sample at 5 or 10% confidence levels. Source: James M. Patell and Mark A. Wolfson, “The Intraday Speed of Stock Prices to Earnings and Dividend Announcements,” Journal of Financial Economics, June 1984, pp. 223–52.

Return (%)

15 10 5 0

0–30

30–60

60–90

90–120 120–150 150–180

⫺5 ⫺10 Minutes since public announcement

market equilibrium, efficient informational gathering activity should be fruitful.1 Moreover, it would not be surprising to find that the degree of efficiency across various markets may differ. For example, emerging markets, which are less intensively analyzed than U.S. markets and in which information is harder to come by, may be less efficient than U.S. markets. Small stocks, which receive less coverage by Wall Street analysts, may be less efficiently priced than large ones. Still, while we would not go so far as to say you absolutely cannot come up with new information, it makes sense to consider and respect your competition. Assume an investment management firm is managing a $5 billion portfolio. Suppose the fund manager can devise a research program that could increase the portfolio rate of return by one-tenth of 1% per year, a seemingly modest amount. This program would increase the dollar return to the portfolio by $5 billion ⫻ .001, or $5 million. Therefore, the fund is presumably willing to spend up to $5 million per year on research to increase stock returns by a mere one-tenth of 1% per year. With such large rewards for such small increases in investment performance, is it any surprise that professional portfolio managers are willing to spend large sums on industry analysts, computer support, and research effort? With so many well-backed analysts willing to spend considerable resources on research, there cannot be many easy pickings in the market. Moreover, the incremental rates of return on research activity are likely to be so small that only managers of the largest portfolios will find them worth pursuing. While it may not literally be true that all relevant information will be uncovered, it is virtually certain there are many investigators hot on the trail of any leads that seem likely to improve investment performance. Competition among these many well-backed, highly paid, aggressive analysts ensures that, as a general rule, stock prices ought to reflect available information regarding their proper levels.

1

A challenging and insightful discussion of this point may be found in Sanford J. Grossman and Joseph E. Stiglitz, “On the Impossibility of Informationally Efficient Markets,” American Economic Review 70 (June 1980).

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The Efficient Market Hypothesis

Versions of the Efficient Market Hypothesis It is common to distinguish among three versions of the EMH: the weak, the semistrong, and the strong forms of the hypothesis. These versions differ according to their notions of what is meant by the term all available information. The weak-form EMH asserts that stock prices already reflect all information that can be derived by examining market trading data such as the history of past prices, trading volume, or short interest. This version of the hypothesis implies that trend analysis is fruitless. Past stock price data are publicly available and virtually costless to obtain. The weak-form hypothesis holds that if such data ever conveyed reliable signals about future performance, all investors would have learned long since to exploit the signals. Ultimately, the signals lose their value as they become widely known, because a buy signal, for instance, would result in an immediate price increase. The semistrong-form EMH states that all publicly available information regarding the prospects of a firm must be already reflected in the stock price. Such information includes, in addition to past prices, fundamental data on the firm’s product line, quality of management, balance sheet composition, patents held, earnings forecasts, accounting practices, and so forth. Again, if any investor has access to such information from publicly available sources, one would expect it to be reflected in stock prices. Finally, the strong-form EMH states that stock prices reflect all information relevant to the firm, even including information available only to company insiders. This version of the hypothesis is quite extreme. Few would argue with the proposition that corporate officers have access to pertinent information long enough before public release to enable them to profit from trading on that information. Indeed, much of the activity of the Securities and Exchange Commission (SEC) is directed toward preventing insiders from profiting by exploiting their privileged situation. Rule 10b-5 of the Security Exchange Act of 1934 limits trading by corporate officers, directors, and substantial owners, requiring them to report trades to the SEC. Anyone trading on information supplied by insiders is considered in violation of the law. Defining insider trading is not always easy, however. After all, stock analysts are in the business of uncovering information not already widely known to market participants. As we saw in Chapter 3, the distinction between private and inside information is sometimes murky. 1. a. Suppose you observed that high-level managers were making superior returns on investments in their company’s stock. Would this be a violation of weakform market efficiency? Would it be a violation of strong-form market efficiency? b. If the weak form of the efficient market hypothesis is valid, must the strong form also hold? Conversely, does strong-form efficiency imply weak-form efficiency?

8.2

IMPLICATIONS OF THE EMH

Technical Analysis Technical analysis is essentially the search for recurring and predictable patterns in stock prices. Although technicians recognize the value of information that has to do with future economic prospects of the firm, they believe such information is not necessary for a successful trading

weak-form EMH The assertion that stock prices already reflect all information contained in the history of past trading.

semistrongform EMH The assertion that stock prices already reflect all publicly available information.

strong-form EMH The assertion that stock prices reflect all relevant information, including inside information.

2. What would happen to market efficiency if all investors attempted to follow a passive strategy?

The Role of Portfolio Management in an Efficient Market If the market is efficient, why not throw darts at The Wall Street Journal instead of trying to choose a stock portfolio rationally? It’s tempting to draw this sort of conclusion from the notion that security prices are fairly set, but it’s a far too simple one. There is a role for rational portfolio management, even in perfectly efficient markets. A basic principle in portfolio selection is diversification. Even if all stocks are priced fairly, each still poses firm-specific risk that can be eliminated through diversification. Therefore, rational security selection, even in an efficient market, calls for the selection of a carefully diversified portfolio. Moreover, that portfolio should provide the systematic risk level the investor wants. Even in an efficient market, investors must choose the risk-return profiles they deem appropriate. Rational investment policy also requires that investors take tax considerations into account in security choice. If you are in a high tax bracket, you generally will not want the same securities that low-bracket investors find favorable. At an obvious level, high-bracket investors find it advantageous to buy tax-exempt municipal bonds despite their relatively low pretax yields, while those same bonds are unattractive to low-bracket investors. At a more subtle level, high-bracket investors might want to tilt or specialize their portfolios toward securities that provide capital gains as opposed to dividend or interest income, because capital gains are taxed less heavily, and the option to defer the realization of capital gains income is more valuable, the higher the investor’s current tax bracket. High tax bracket investors also will be more attracted to investment opportunities where returns are sensitive to tax benefits, such as real estate ventures. A third argument for rational portfolio management relates to the particular risk profile of the investor. For example, a General Motors executive whose annual bonus depends on GM’s profits generally should not invest additional amounts in auto stocks. To the extent that his or her compensation already depends on GM’s well-being, the executive is overinvested in GM now and should not exacerbate the lack of diversification. Investors of varying ages also might warrant different portfolio policies with regard to risk bearing. For example, older investors who are essentially living off savings might avoid longterm bonds, whose market values fluctuate dramatically with changes in interest rates. Because these investors rely on accumulated savings, they require conservation of principal. In contrast, younger investors might be more inclined toward long-term inflation-indexed bonds. The steady flow of real income over long periods that is locked in with these bonds can be more important than preservation of principal to those with long life expectancies. In short, there is a role for portfolio management even in an efficient market. Investors’ optimal positions will vary according to factors such as age, tax bracket, risk aversion, and employment. The role of the portfolio manager in an efficient market is to tailor the portfolio to these needs, rather than to attempt to beat the market.

Resource Allocation We’ve focused so far on the investment implications of the efficient market hypothesis. Deviations from efficiency may offer profit opportunities to better-informed traders at the expense of less-informed traders.

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The Efficient Market Hypothesis

However, deviations from informational efficiency would also result in a large cost that will be borne by all citizens, namely, inefficient resource allocation. Recall that in a capitalist economy, investments in real assets such as plant, equipment, and know-how are guided in large part by the prices of financial assets. For example, if the values of biotech assets as reflected in the stock market prices of biotech firms exceed the cost of acquiring those assets, the managers of such firms have a strong signal that further investments in the firm will be regarded by the market as a positive net present value venture. In this manner, capital market prices guide resource allocation. Security mispricing thus could entail severe social costs by fostering inappropriate investments on the real side of the economy. Section 7.1 demonstrates how security analysis impounds information into security prices. To the extend that only part of this information is reflected in prices, corporations with overpriced securities will be able to obtain capital too cheaply and corporations with undervalued securities might forego investment opportunities because the cost of raising capital will be too high. Therefore, inefficient capital markets will diminish one of the most potent benefits of a market economy.

8.3

ARE MARKETS EFFICIENT?

The Issues Not surprisingly, the efficient market hypothesis is not enthusiastically hailed by professional portfolio managers. It implies that a great deal of the activity of portfolio managers—the search for undervalued securities—is at best wasted effort and possibly harmful to clients because it costs money and leads to imperfectly diversified portfolios. Consequently, the EMH has never been widely accepted on Wall Street, and debate continues today on the degree to which security analysis can improve investment performance. Before discussing empirical tests of the hypothesis, we want to note three factors that together imply the debate probably never will be settled: the magnitude issue, the selection bias issue, and the lucky event issue.

The magnitude issue We noted that an investment manager overseeing a $5 billion portfolio who can improve performance by only one-tenth of 1% per year will increase investment earnings by .001 ⫻ $5 billion ⫽ $5 million annually. This manager clearly would be worth her salary! Yet we, as observers, probably cannot statistically measure her contribution. A onetenth of 1% contribution would be swamped by the yearly volatility of the market. Remember, the annual standard deviation of the well-diversified S&P 500 index has been approximately 20% per year. Against these fluctuations, a small increase in performance would be hard to detect. Nevertheless, $5 million remains an extremely valuable improvement in performance. All might agree that stock prices are very close to fair values, and that only managers of large portfolios can earn enough trading profits to make the exploitation of minor mispricing worth the effort. According to this view, the actions of intelligent investment managers are the driving force behind the constant evolution of market prices to fair levels. Rather than ask the qualitative question, Are markets efficient? we ought instead to ask the quantitative question, How efficient are markets? The selection bias issue Suppose you discover an investment scheme that could really make money. You have two choices: Either publish your technique in The Wall Street Journal to win fleeting fame or keep your technique secret and use it to earn millions of dollars. Most investors would choose the latter option, which presents us with a conundrum. Only investors who find that an investment scheme cannot generate abnormal returns will be willing to report their findings to the whole world. Hence, opponents of the efficient market’s view of the world always can use evidence that various techniques do not provide investment

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rewards as proof that the techniques that do work simply are not being reported to the public. This is a problem in selection bias; the outcomes we are able to observe have been preselected in favor of failed attempts. Therefore, we cannot fairly evaluate the true ability of portfolio managers to generate winning stock market strategies.

The lucky event issue In virtually any month, it seems we read an article in The Wall Street Journal about some investor or investment company with a fantastic investment performance over the recent past. Surely the superior records of such investors disprove the efficient market hypothesis. This conclusion is far from obvious, however. As an analogy to the “contest” among portfolio managers, consider a contest to flip the most heads out of 50 trials using a fair coin. The expected outcome for any person is 50% heads and 50% tails. If 10,000 people, however, compete in this contest, it would not be surprising if at least one or two contestants flipped more than 75% heads. In fact, elementary statistics tells us that the expected number of contestants flipping 75% or more heads would be two. It would be silly, though, to crown these people the head-flipping champions of the world. They are simply the contestants who happened to get lucky on the day of the event (see the nearby box). The analogy to efficient markets is clear. Under the hypothesis that any stock is fairly priced given all available information, any bet on a stock is simply a coin toss. There is equal likelihood of winning or losing the bet. Yet, if many investors using a variety of schemes make fair bets, statistically speaking, some of those investors will be lucky and win a great majority of bets. For every big winner, there may be many big losers, but we never hear of these managers. The winners, though, turn up in The Wall Street Journal as the latest stock market gurus; then they can make a fortune publishing market newsletters. Our point is that after the fact there will have been at least one successful investment scheme. A doubter will call the results luck; the successful investor will call it skill. The proper test would be to see whether the successful investors can repeat their performance in another period, yet this approach is rarely taken. With these caveats in mind, we now turn to some of the empirical tests of the efficient market hypothesis.

Concept CHECK

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3. Fidelity’s Magellan Fund outperformed the S&P 500 in 11 of the 13 years that Peter Lynch managed the fund, resulting in an average annual return for this period more than 10% better than that of the index. Is Lynch’s performance sufficient to cause you to doubt the efficient markets theory? If not, would any performance record be sufficient to dissuade you?

Weak-Form Tests: Predictability in Stock Returns Returns over short horizons Early tests of efficient markets were tests of the weak form. Could speculators find trends in past prices that would enable them to earn abnormal profits? This is essentially a test of the efficacy of technical analysis. The already-cited work of Kendall and of Roberts (1959), both of whom analyzed the possible existence of patterns in stock prices, suggests that such patterns are not to be found. One way of discerning trends in stock prices is by measuring the serial correlation of stock market returns. Serial correlation refers to the tendency for stock returns to be related to past returns. Positive serial correlation means that positive returns tend to follow positive returns (a momentum type of property). Negative serial correlation means that positive returns tend to be followed by negative returns (a reversal or “correction” property). Both Conrad and Kaul (1988) and Lo and MacKinlay (1988) examine weekly returns of NYSE stocks and find positive serial correlation over short horizons. However, the correlation

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How to Guarantee Successful Market Timing Suppose you want to make your fortune publishing a market newsletter. You need first to convince potential subscribers that you have talent worth paying for. But what if you have no market prediction talent? The solution is simple: Start eight market newsletters. In year one, let four of your newsletters predict an up market and four a down market. In year two, let half of the originally optimistic group of newsletters continue to predict an up market and the other half a down market. Do the same for the originally pessimistic group. Continue in this manner to obtain the following pattern of predictions (U ⫽ prediction of an up market, D ⫽ prediction of a down market). After three years, no matter what has happened to the market, one of the newsletters would have had a perfect prediction record. This is because after three years, there are 23 ⫽ 8 outcomes for the market, and we’ve covered all eight possibilities with the eight letters. Now, we simply slough off the seven unsuccessful newsletters and market the eighth letter based on its perfect track record. If we want to establish a letter with a perfect track record over a four-year period, we need 24 ⫽ 16 newsletters. A five-year period requires 32 newsletters, and so on.

After the fact, the one newsletter that was always right will attract attention for your uncanny foresight and investors will rush to pay large fees for its advice. Your fortune is made, and you never even researched the market! WARNING: This scheme is illegal! The point, however, is that with hundreds of market newsletters, you can find one that has stumbled onto an apparently remarkable string of successful predictions without any real degree of skill. After the fact, someone’s prediction history can seem to imply great forecasting skill. This person is the one we will read about in The Wall Street Journal; the others will be forgotten. Newsletter Predictions Year

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coefficients of weekly returns tend to be fairly small, at least for large stocks for which price data are the most reliably up-to-date. Thus, while these studies demonstrate price trends over short periods, the evidence does not clearly suggest the existence of trading opportunities. A more sophisticated version of trend analysis is a filter rule. A filter technique gives a rule for buying or selling a stock depending on past price movements. One rule, for example, might be: “Buy if the last two trades each resulted in a stock price increase.” A more conventional one might be: “Buy a security if its price increased by 1%, and hold it until its price falls by more than 1% from the subsequent high.” Alexander (1964) and Fama and Blume (1966) found that such filter rules generally could not generate trading profits. These very short-horizon studies offer the suggestion of momentum in stock market prices, albeit of a magnitude that may be too small to exploit. However, in an investigation of intermediate horizon stock price behavior (using 3- to 12-month holding periods), Jegadeesh and Titman (1993) found that stocks exhibit a momentum property in which good or bad recent performance continues. They conclude that while the performance of individual stocks is highly unpredictable, portfolios of the best-performing stocks in the recent past appear to outperform other stocks with enough reliability to offer profit opportunities.

filter rule A rule for buying or selling stock according to recent price movements.

Returns over long horizons While studies of short-horizon returns have detected minor positive serial correlation in stock market prices, tests2 of long-horizon returns (that is, returns over multiyear periods) have found suggestions of pronounced negative long-term serial 2 Eugene F. Fama and Kenneth R. French, “Permanent and Temporary Components of Stock Prices,” Journal of Political Economy 96 (April 1988), pp. 246–73; James Poterba and Lawrence Summers, “Mean Reversion in Stock Prices: Evidence and Implications,” Journal of Financial Economics 22 (October 1988), pp. 27–59.

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correlation. The latter result has given rise to a “fads hypothesis,” which asserts that stock prices might overreact to relevant news. Such overreaction leads to positive serial correlation (momentum) over short time horizons. Subsequent correction of the overreaction leads to poor performance following good performance and vice versa. The corrections mean that a run of positive returns eventually will tend to be followed by negative returns, leading to negative serial correlation over longer horizons. These episodes of apparent overshooting followed by correction give stock prices the appearance of fluctuating around their fair values and suggest that market prices exhibit excessive volatility compared to intrinsic value.3 These long-horizon results are dramatic, but the studies offer far from conclusive evidence regarding efficient markets. First, the study results need not be interpreted as evidence for stock market fads. An alternative interpretation of these results holds that they indicate only that market risk premiums vary over time: The response of market prices to variation in the risk premium can lead one to incorrectly infer the presence of mean reversion and excess volatility in prices. For example, when the risk premium and the required return on the market rises, stock prices will fall. When the market then rises (on average) at this higher rate of return, the data convey the impression of a stock price recovery. The impression of overshooting and correction is in fact no more than a rational response of market prices to changes in discount rates. Second, these studies suffer from statistical problems. Because they rely on returns measured over long time periods, these tests of necessity are based on few observations of longhorizon returns.

reversal effect The tendency of poorly performing stocks and wellperforming stocks in one period to experience reversals in the following period.

Reversals While some of the studies just cited suggest momentum in stock market prices over short horizons (of less than one year), other studies suggest that over longer horizons, extreme stock market performance tends to reverse itself: The stocks that have performed best in the recent past seem to underperform the rest of the market in the following periods, while the worst past performers tend to offer above-average future performance. DeBondt and Thaler (1985) and Chopra, Lakonishok, and Ritter (1992) find strong tendencies for poorly performing stocks in one period to experience sizable reversals over the subsequent period, while the best-performing stocks in a given period tend to follow with poor performance in the following period. For example, the DeBondt and Thaler study found that if one were to rank order the performance of stocks over a five-year period and then group stocks into portfolios based on investment performance, the base-period “loser” portfolio (defined as the 35 stocks with the worst investment performance) would outperform the “winner” portfolio (the top 35 stocks) by an average of 25% (cumulative return) in the following three-year period. This reversal effect, in which losers rebound and winners fade back, seems to suggest that the stock market overreacts to relevant news. After the overreaction is recognized, extreme investment performance is reversed. This phenomenon would imply that a contrarian investment strategy— investing in recent losers and avoiding recent winners—should be profitable. Moreover, these returns seem pronounced enough to be exploited profitably. The reversal effect also seems to depend on the time horizon of the investment. While DeBondt and Thaler (1992) found reversals over long (multiyear) horizons, and studies by Jegadeesh (1990) and Lehmann (1990) documented reversals over short horizons of a month 3

The fads debate started as a controversy over whether stock prices exhibit excess volatility. See Robert J. Shiller, “Do Stock Prices Move Too Much to Be Justified by Subsequent Changes in Dividends?” American Economic Review 71 (June 1971), pp. 421–36. However, it is now apparent that excess volatility and fads are essentially different ways of describing the same phenomenon.

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or less, we note above that an investigation of intermediate-term stock price behavior (using 3- to 12-month holding periods) by Jegadeesh and Titman (1993) found that stocks exhibit a momentum property in which good or bad recent performance continues. This of course is the opposite of a reversal phenomenon. Thus it appears that there may be short-run momentum but long-run reversal patterns in price behavior. One interpretation of these patterns is that short-run overreaction (which causes momentum in prices) may lead to long-term reversals (when the market recognizes and corrects its past errors). This interpretation is emphasized by Haugen (1995).

Predictors of Broad Market Movements Several studies have documented the ability of easily observed variables to predict market returns. For example, Fama and French (1988) show that the return on the aggregate stock market tends to be higher when the dividend/price ratio, or the dividend yield, is high. Campbell and Shiller (1988) find that the earnings yield can predict market returns. Keim and Stambaugh (1986) show that bond market data such as the spread between yields on high- and lowgrade corporate bonds also help predict broad market returns. Again, the interpretation of these results is difficult. On the one hand, they may imply that stock returns can be predicted, in violation of the efficient market hypothesis. More probably, however, these variables are proxying for variation in the market risk premium. For example, given a level of dividends or earnings, stock prices will be lower and dividend and earnings yields will be higher when the risk premium (and therefore the expected market return) is larger. Thus, a high dividend or earnings yield will be associated with higher market returns. This does not indicate a violation of market efficiency. The predictability of market returns is due to predictability in the risk premium, not in risk-adjusted abnormal returns. Fama and French (1989) show that the yield spread between high- and low-grade bonds has greater predictive power for returns on low-grade bonds than for returns on high-grade bonds, and greater predictive power for stock returns than for bond returns, suggesting that the predictability in returns is in fact a risk premium rather than evidence of market inefficiency. Similarly, the fact that the dividend yield on stocks helps to predict bond market returns suggests that the yield captures a risk premium common to both markets rather than mispricing in the equity market.

Semistrong-Form Tests: Market Anomalies Fundamental analysis uses a much wider range of information to create portfolios than does technical analysis. Investigations of the efficacy of fundamental analysis ask whether publicly available information beyond the trading history of a security can be used to improve investment performance and, therefore, are tests of semistrong-form market efficiency. Surprisingly, several easily accessible statistics, for example a stock’s price–earnings ratio or its market capitalization, seem to predict abnormal risk-adjusted returns. Findings such as these, which we will review in the following pages, are inconsistent with the efficient market hypothesis and, therefore, are often referred to as market anomalies. A difficulty in interpreting these tests is that we usually need to adjust for portfolio risk before evaluating the success of an investment strategy. For example, many tests use the CAPM to adjust for risk. However, we know that even if beta is a relevant descriptor of stock risk, the empirically measured quantitative trade-off between risk as measured by beta and expected return differs from the predictions of the CAPM. If we use the CAPM to adjust portfolio returns for risk, inappropriate adjustments might lead to the incorrect conclusion that various portfolio strategies can generate superior returns.

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P/E effect Portfolios of low P/E stocks have exhibited higher average riskadjusted returns than high P/E stocks.

small-firm effect Stocks of small firms have earned abnormal returns, primarily in the month of January.

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Tests of risk-adjusted returns are joint tests of the efficient market hypothesis and the risk adjustment procedure. If it appears that a portfolio strategy can generate superior returns, we then must choose between rejecting the EMH or rejecting the risk adjustment technique. Usually, the risk adjustment technique is based on more questionable assumptions than the EMH; if we reject the procedure, we are left with no conclusion about market efficiency. An example of this problem is the discovery by Basu (1977, 1983) that portfolios of low price/earnings ratio stocks have higher average returns than high P/E portfolios. The P/E effect holds up even if returns are adjusted for portfolio beta. Is this a confirmation that the market systematically misprices stocks according to the P/E ratio? This would be a surprising and, to us, disturbing conclusion, because analysis of P/E ratios is such a simple procedure. While it may be possible to earn superior returns using hard work and much insight, it hardly seems likely that following such a basic technique is enough to generate abnormal returns. One possible interpretation of these results is that the model of capital market equilibrium is at fault in that the returns are not properly adjusted for risk. This makes sense, since if two firms have the same expected earnings, then the riskier stock will sell at a lower price and lower P/E ratio. Because of its higher risk, the low P/E stock also will have higher expected returns. Therefore, unless the CAPM beta fully adjusts for risk, P/E will act as a useful additional descriptor of risk and will be associated with abnormal returns if the CAPM is used to establish benchmark performance.

The small-firm-in-January effect One of the most frequently cited anomalies with respect to the efficient market hypothesis is the so-called size or small-firm effect, originally documented by Banz (1981). Figure 8.3 illustrates the size effect. It shows the historical performance of portfolios formed by dividing the NYSE stocks into 10 portfolios each year according to firm size (i.e., the total value of outstanding equity). Average annual returns are consistently higher on the small-firm portfolios. The difference in average annual return between portfolio 10 (with the largest firms) and portfolio 1 (with the smallest firms) is 8.59%. Of course, the smaller-firm portfolios tend to be riskier. But even when returns are adjusted for risk by using the CAPM, there is still a consistent premium for the smaller-sized portfolios. Even on a risk-adjusted basis, the smallest-size portfolio outperforms the largest-firm portfolio by an average of 4.3% annually. This is a huge premium; imagine earning an extra return of this amount on a billion-dollar portfolio. Yet it is remarkable that following a simple (even simplistic) rule such as “invest in

Source: Stocks, Bonds, Bills, and Inflation 2000 Yearbook, Ibbotson Associates, 2000.

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F I G U R E 8.3 Returns in excess of risk-free rate and in excess of the Security Market Line for 10 size-based portfolios

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low capitalization stocks” should enable an investor to earn excess returns. After all, any investor can measure firm size costlessly. One would not expect such minimal effort to yield such large rewards. Later studies (Keim, 1983; Reinganum, 1983; and Blume and Stambaugh, 1983) showed that the small-firm effect occurs virtually entirely in the first two weeks of January. The size effect is in fact a small-firm-in-January effect. Some researchers believe the January effect is tied to tax-loss selling at the end of the year. The hypothesis is that many people sell stocks that have declined in price during the previous months to realize their capital losses before the end of the tax year. Such investors do not put the proceeds from these sales back into the stock market until after the turn of the year. At that point, the rush of demand for stock places an upward pressure on prices that results in the January effect. Finally, the January effect is said to show up most dramatically for the smallest firms because the small-firm group includes, as an empirical matter, stocks with the greatest variability of prices during the year. The group, therefore, includes a relatively large number of firms that have declined sufficiently to induce tax-loss selling. Some empirical evidence supports the belief that the January effect is connected to tax-loss selling. For example, Ritter (1988) shows that the ratio of stock purchases to sales by individual investors is below normal in late December and above normal in early January. This is consistent with tax-loss rebalancing. The fundamental question is why market participants do not exploit the January effect and thereby ultimately eliminate it by bidding stock prices to appropriate levels. One possible explanation lies in segmentation of the market into two groups: institutional investors who invest primarily in large firms and individual investors who invest disproportionately in smaller firms. According to this view, managers of large institutional portfolios are the moving force behind efficient markets. It is professionals who seek out profit opportunities and bid prices to their appropriate levels. Institutional investors do not seem to buy at the small-size end of the market, perhaps because of limits on allowed portfolio positions, so the small-firm anomaly persists without the force of their participation. 4. Does this market segmentation theory get the efficient market hypothesis off the hook, or are there still market mechanisms that, in theory, ought to eliminate the small-firm anomaly?

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Compute a bond’s price given its yield to maturity, and compute its yield to maturity given its price. Calculate how bond prices will change over time for a given interest rate projection. Identify the determinants of bond safety and rating. Analyze how call, convertibility, and sinking fund provisions will affect a bond’s equilibrium yield to maturity. Analyze the factors likely to affect the shape of the yield curve at any time.

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Related Websites http://www.bankrate.com/brm/default.asp http://www.bloomberg.com/markets http://cnnfn.cnn.com/markets/bondcenter/ rates.html

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http://www.standardandpoors.com/ratings/ corporates/index.htm http://www.moodys.com http://www.fitchinv.com The above sites provide information on bond ratings.

These sites give general price information.

http://www.stls.frb.org/fred

http://www.bondresources.com http://www.investinginbonds.com/ http://www.bondsonline.com/docs/ bondprofessor-glossary.html

This site has extended information on various interest rates. These rates can be downloaded into a spreadsheet format for analysis.

These sites contain detailed information on bonds. They are comprehensive and have many related links.

n the previous chapters on risk and return relationships, we have treated securities at a high level of abstraction. We have assumed implicitly that a prior, detailed analysis of each security already has been performed, and that its risk and return features have been assessed. We turn now to specific analyses of particular security markets. We examine valuation principles, determinants of risk and return, and portfolio strategies commonly used within and across the various markets. We begin by analyzing debt securities. A debt security is a claim on a specified periodic stream of income. Debt securities are often called fixed-income securities, because they promise either a fixed stream of income or a stream of income that is determined according to a specified formula. These securities have the advantage of being relatively easy to understand because the payment formulas are specified in advance. Uncertainty surrounding cash flows paid to the security holder is minimal as long as the issuer of the security is sufficiently creditworthy. That makes these securities a convenient starting point for our analysis of the universe of potential investment vehicles. The bond is the basic debt security, and this chapter starts with an overview of bond markets, including Treasury, corporate, and international bonds. We turn next to bond pricing, showing how bond prices are set in accordance with market interest rates and why bond prices change with those rates. Given this background, we can compare the myriad measures of bond returns such as yield to maturity, yield to call, holding-period return, or realized compound yield to maturity. We show how bond prices evolve over time, discuss certain tax rules that apply to debt securities, and show how to calculate after-tax returns. Next, we consider the impact of default or

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credit risk on bond pricing and look at the determinants of credit risk and the default premium built into bond yields. Finally, we turn to the term structure of interest rates, the relationship between yield to maturity and time to maturity.

A security such as a bond that pays a specified cash flow over a specific period.

bond A security that obligates the issuer to make specified payments to the holder over a period of time.

face value, par value The payment to the bondholder at the maturity of the bond.

coupon rate A bond’s annual interest payment per dollar of par value.

zero-coupon bond A bond paying no coupons that sells at a discount and provides only a payment of par value at maturity.

callable bonds Bonds that may be repurchased by the issuer at a specified call price during the call period.

9.1

BOND CHARACTERISTICS

A bond is a security that is issued in connection with a borrowing arrangement. The borrower issues (i.e., sells) a bond to the lender for some amount of cash; the bond is in essence the “IOU” of the borrower. The arrangement obligates the issuer to make specified payments to the bondholder on specified dates. A typical coupon bond obligates the issuer to make semiannual payments of interest, called coupon payments, to the bondholder for the life of the bond. These are called coupon payments because, in precomputer days, most bonds had coupons that investors would clip off and mail to the issuer of the bond to claim the interest payment. When the bond matures, the issuer repays the debt by paying the bondholder the bond’s par value (or equivalently, its face value). The coupon rate of the bond serves to determine the interest payment: The annual payment equals the coupon rate times the bond’s par value. The coupon rate, maturity date, and par value of the bond are part of the bond indenture, which is the contract between the issuer and the bondholder. To illustrate, a bond with a par value of $1,000 and a coupon rate of 8% might be sold to a buyer for $1,000. The issuer then pays the bondholder 8% of $1,000, or $80 per year, for the stated life of the bond, say 30 years. The $80 payment typically comes in two semiannual installments of $40 each. At the end of the 30-year life of the bond, the issuer also pays the $1,000 par value to the bondholder. Bonds usually are issued with coupon rates set high enough to induce investors to pay par value to buy the bond. Sometimes, however, zero-coupon bonds are issued that make no coupon payments. In this case, investors receive par value at the maturity date, but receive no interest payments until then: The bond has a coupon rate of zero. These bonds are issued at prices considerably below par value, and the investor’s return comes solely from the difference between issue price and the payment of par value at maturity. We will return to these bonds below.

Treasury Bonds and Notes Figure 9.1 is an excerpt from the listing of Treasury issues in The Wall Street Journal. Treasury note maturities range up to 10 years, while Treasury bonds with maturities ranging from 10 to 30 years appear in the figure. In 2001, the Treasury suspended new issues of 30-year bonds, making the 10-year note the longest currently issued Treasury. As of 2002, there have been no announcements of any plans to resume issuing the 30-year bond. Both bonds and notes are issued in denominations of $1,000 or more. Both make semiannual coupon payments. Aside from their differing maturities at issue date, the only major distinction between T-notes and T-bonds is that in the past, some T-bonds were callable for a given period, usually during the last five years of the bond’s life. The call provision gives the Treasury the right to repurchase the bond at par value during the call period. The highlighted bond in Figure 9.1 matures in October 2006. Its coupon rate is 61⁄2%. Par value is $1,000; thus, the bond pays interest of $65 per year in two semiannual payments of $32.50. Payments are made in April and October of each year. The bid and ask prices1 are quoted 1

Recall that the bid price is the price at which you can sell the bond to a dealer. The ask price, which is slightly higher, is the price at which you can buy the bond from a dealer.

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F I G U R E 9.1 Listing of Treasury issues Source: The Wall Street Journal, November 29, 2001. Reprinted by permission of Dow Jones & Company, Inc. via Copyright Clearance Center, Inc. © 2001 Dow Jones & Company. All Rights Reserved Worldwide.

in points plus fractions of 1⁄32 of a point (the numbers after the colons are the fractions of a point). Although bonds are sold in denominations of $1,000 par value, the prices are quoted as a percentage of par value. Therefore, the bid price of the bond is 109:08 1098⁄32 109.25% of par value or $1,092.50, while the ask price is 10911⁄32 percent of par, or $1,093.44. The last column, labeled Ask Yld, is the bond’s yield to maturity based on the ask price. The yield to maturity is often interpreted as a measure of the average rate of return to an investor who purchases the bond for the ask price and holds it until its maturity date. We will have much to say about yield to maturity below.

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Accrued interest and quoted bond prices The bond prices that you see quoted in the financial pages are not actually the prices that investors pay for the bond. This is because the quoted price does not include the interest that accrues between coupon payment dates. If a bond is purchased between coupon payments, the buyer must pay the seller for accrued interest, the prorated share of the upcoming semiannual coupon. For example, if 40 days have passed since the last coupon payment, and there are 182 days in the semiannual coupon period, the seller is entitled to a payment of accrued interest of 40/182 of the semiannual coupon. The sale, or invoice price of the bond, which is the amount the buyer actually pays, would equal the stated price plus the accrued interest. In general, the formula for the amount of accrued interest between two dates is Accrued interest

9.1 EXAMPLE Accrued Interest

Annual coupon payment Days since last coupon payment 2 Days separating coupon payments

Suppose that the coupon rate is 8%. Then the semiannual coupon payment is $40. Because 40 days have passed since the last coupon payment, the accrued interest on the bond is $40 (40/182) $8.79. If the quoted price of the bond is $990, then the invoice price will be $990 $8.79 $998.79.

The practice of quoting bond prices net of accrued interest explains why the price of a maturing bond is listed at $1,000 rather than $1,000 plus one coupon payment. A purchaser of an 8% coupon bond one day before the bond’s maturity would receive $1,040 on the following day and so should be willing to pay a total price of $1,040 for the bond. In fact, $40 of that total payment constitutes the accrued interest for the preceding half-year period. The bond price is quoted net of accrued interest in the financial pages and thus appears as $1,000.

Corporate Bonds Like the government, corporations borrow money by issuing bonds. Figure 9.2 is a sample of corporate bond listings in The Wall Street Journal. The data presented here differ only slightly from U.S. Treasury bond listings. For example, the highlighted AT&T bond pays a coupon rate of 81⁄8% and matures in 2022. Like Treasury bonds, corporate bonds trade in increments of 1⁄32 point. AT&T’s current yield is 8.1%, which is simply the annual coupon payment divided by the bond price ($81.25/$997.50). Note that current yield measures only the annual interest income the bondholder receives as a percentage of the price paid for the bond. It ignores the fact that an investor who buys the bond for $997.50 will be able to redeem it for $1,000 on the maturity date. Prospective price appreciation or depreciation does not enter the computation of the current yield. The trading volume column shows that 300 bonds traded on that day. The change from yesterday’s closing price is given in the last column. Like government bonds, corporate bonds sell in units of $1,000 par value but are quoted as a percentage of par value. Although the bonds listed in Figure 9.2 trade on a formal exchange operated by the New York Stock Exchange, most bonds are traded over-the-counter in a loosely organized network of bond dealers linked by a computer quotation system. (See Chapter 3 for a comparison of exchange versus OTC trading.) In practice, the bond market can be quite “thin,” in that there are few investors interested in trading a particular bond at any particular time. Figure 9.2 shows that trading volume of many bonds on the New York exchange is quite low. Bonds issued in the United States today are registered, meaning that the issuing firm keeps records of the owner of the bond and can mail interest checks to the owner. Registration of

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F I G U R E 9.2 Listing of corporate bonds Source: The Wall Street Journal, September 7, 2000. Reprinted by permission of Dow Jones & Company, Inc. via Copyright Clearance Center, Inc. © 2000 Dow Jones & Company, Inc. All Rights Reserved Worldwide.

bonds is helpful to tax authorities in the enforcement of tax collection. Bearer bonds are those traded without any record of ownership. The investor’s physical possession of the bond certificate is the only evidence of ownership. These are now rare in the United States, but less rare in Europe.

Call provisions on corporate bonds While the Treasury no longer issues callable bonds, some corporate bonds are issued with call provisions. The call provision allows the issuer to repurchase the bond at a specified call price before the maturity date. For example, if a company issues a bond with a high coupon rate when market interest rates are high, and interest rates later fall, the firm might like to retire the high-coupon debt and issue new bonds at a lower coupon rate to reduce interest payments. The proceeds from the new bond issue are used to pay for the repurchase of the existing higher coupon bonds at the call price. This is called refunding. Callable bonds typically come with a period of call protection, an initial time during which the bonds are not callable. Such bonds are referred to as deferred callable bonds. The option to call the bond is valuable to the firm, allowing it to buy back the bonds and refinance at lower interest rates when market rates fall. Of course, the firm’s benefit is the bondholder’s burden. Holders of called bonds forfeit their bonds for the call price, thereby giving up the prospect of an attractive rate of interest on their original investment. To compensate investors for this risk, callable bonds are issued with higher coupons and promised yields to maturity than noncallable bonds. 1. Suppose that General Motors issues two bonds with identical coupon rates and maturity dates. One bond is callable, however, while the other is not. Which bond will sell at a higher price?

Convertible bonds Convertible bonds give bondholders an option to exchange each bond for a specified number of shares of common stock of the firm. The conversion ratio gives the number of shares for which each bond may be exchanged. To see the value of this

2. Calculate the price of the bond for a market interest rate of 3% per half year. Compare the capital gains for the interest rate decline to the losses incurred when the rate increases to 5%. Corporate bonds typically are issued at par value. This means the underwriters of the bond issue (the firms that market the bonds to the public for the issuing corporation) must choose a coupon rate that very closely approximates market yields. In a primary issue of bonds, the underwriters attempt to sell the newly issued bonds directly to their customers. If the coupon rate is inadequate, investors will not pay par value for the bonds. After the bonds are issued, bondholders may buy or sell bonds in secondary markets, such as the one operated by the New York Stock Exchange or the over-the-counter market, where most bonds trade. In these secondary markets, bond prices move in accordance with market forces. The bond prices fluctuate inversely with the market interest rate. The inverse relationship between price and yield is a central feature of fixed-income securities. Interest rate fluctuations represent the main source of risk in the bond market, and we devote considerable attention in the next chapter to assessing the sensitivity of bond prices to market yields. For now, however, it is sufficient to highlight one key factor that determines that sensitivity, namely, the maturity of the bond. A general rule in evaluating bond price risk is that, keeping all other factors the same, the longer the maturity of the bond, the greater the sensitivity of its price to fluctuations in the interest rate. For example, consider Table 9.2, which presents the price of an 8% coupon bond at different market yields and times to maturity. For any departure of the interest rate from 8% (the rate at which the bond sells at par value), the change in the bond price is smaller for shorter times to maturity. This makes sense. If you buy the bond at par with an 8% coupon rate, and market rates subsequently rise, then you suffer a loss: You have tied up your money earning 8% when alternative investments offer higher returns. This is reflected in a capital loss on the bond—a fall in its market price. The longer the period for which your money is tied up, the greater the loss and, correspondingly, the greater the drop in the bond price. In Table 9.2, the row for one-year maturity bonds shows little price sensitivity—that is, with only one year’s earnings at stake, changes in interest rates are not too threatening. But for 30-year maturity bonds, interest rate swings have a large impact on bond prices. This is why short-term Treasury securities such as T-bills are considered to be the safest. They are free not only of default risk but also largely of price risk attributable to interest rate volatility.

9.3

yield to maturity (YTM) The discount rate that makes the present value of a bond’s payments equal to its price.

BOND YIELDS

We have noted that the current yield of a bond measures only the cash income provided by the bond as a percentage of bond price and ignores any prospective capital gains or losses. We would like a measure of rate of return that accounts for both current income as well as the price increase or decrease over the bond’s life. The yield to maturity is the standard measure of the total rate of return of the bond over its life. However, it is far from perfect, and we will explore several variations of this measure.

Yield to Maturity In practice, an investor considering the purchase of a bond is not quoted a promised rate of return. Instead, the investor must use the bond price, maturity date, and coupon payments to infer the return offered by the bond over its life. The yield to maturity (YTM) is defined as

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Bond Prices and Yields

the discount rate that makes the present value of a bond’s payments equal to its price. This rate is often viewed as a measure of the average rate of return that will be earned on a bond if it is bought now and held until maturity. To calculate the yield to maturity, we solve the bond price equation for the interest rate given the bond’s price. For example, suppose an 8% coupon, 30-year bond is selling at $1,276.76. What average rate of return would be earned by an investor purchasing the bond at this price? To answer this question, we find the interest rate at which the present value of the remaining 60 semiannual bond payments equals the bond price. This is the rate that is consistent with the observed price of the bond. Therefore, we solve for r in the following equation 60

$1,276.76

兺 t1

$40 $1,000 (1 r)t (1 r)60

or, equivalently, 1,276.76 40 Annuity factor(r, 60) 1,000 PV factor(r, 60) These equations have only one unknown variable, the interest rate, r. You can use a financial calculator to confirm that the solution to the equation is r .03, or 3% per half-year.6 This is considered the bond’s yield to maturity, as the bond would be fairly priced at $1,276.76 if the fair market rate of return on the bond over its entire life were 3% per half-year. The financial press reports yields on an annualized basis, however, and annualizes the bond’s semiannual yield using simple interest techniques, resulting in an annual percentage rate or APR. Yields annualized using simple interest are also called bond equivalent yields. Therefore, the semiannual yield would be doubled and reported in the newspaper as a bond equivalent yield of 6%. The effective annual yield of the bond, however, accounts for compound interest. If one earns 3% interest every six months, then after one year, each dollar invested grows with interest to $1 (1.03)2 1.0609, and the effective annual interest rate on the bond is 6.09%. The bond’s yield to maturity is the internal rate of return on an investment in the bond. The yield to maturity can be interpreted as the compound rate of return over the life of the bond under the assumption that all bond coupons can be reinvested at an interest rate equal to the bond’s yield to maturity.7 Yield to maturity therefore is widely accepted as a proxy for average return. Yield to maturity can be difficult to calculate without a financial calculator. However, it is easy to calculate with one. Financial calculators are designed with present value and future value formulas already programmed. The basic financial calculator uses five keys that correspond to the inputs for time value of money problems such as bond pricing: n

i

PV

FV

PMT

• n is the number of time periods. In the case of a bond, n equals the number of periods until the bond matures. If the bond makes semiannual payments, n is the number of half-year periods or, equivalently, the number of semiannual coupon payments. For example, if the bond has 10 years until maturity, you would enter 20 for n, since each payment period is one-half year. 6

Without a financial calculator, you still could solve the equation, but you would need to use a trial-and-error approach. 7 If the reinvestment rate does not equal the bond’s yield to maturity, the compound rate of return will differ from YTM. This is demonstrated in Examples 9.5 and 9.6.

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• i is the interest rate per period, expressed as a percentage (not a decimal). For example, if the interest rate is 6%, you would enter 6, not 0.06. • PV is the present value. Many calculators will require that PV be entered as a negative number, in recognition of the fact that purchase of the bond is a cash outflow, while the receipt of coupon payments and face value are cash inflows. • FV is the future value or face value of the bond. In general, FV is interpreted as a one-time future payment of a cash flow, which, for bonds, is the face (i.e., par) value. • PMT is the amount of any recurring payment. For coupon bonds, PMT is the coupon payment; for zero-coupon bonds, PMT will be zero. Given any four of these inputs, the calculator will solve for the fifth. We can illustrate with some examples.

9.3 EXAMPLE Bond Valuation Using a Financial Calculator

Consider the yield to maturity problem that we just solved. We would enter the following inputs (in any order): n

60

The bond has a maturity of 30 years, so it makes 60 semiannual payments.

PMT

40

Each semiannual coupon payment is $40.

PV

()1,276.76 The bond can be purchased for $1,276.76, which on some calculators must be entered as a negative number as it is a cash outflow.

FV

1,000

The bond will provide a one-time cash flow of $1,000 when it matures.

Given these inputs, you now use the calculator to find the interest rate at which $1,276.76 actually equals the present value of the 60 payments of $40 each plus the one-time payment of $1,000 at maturity. On most calculators, you first punch the “compute” key (labeled COMP or CPT) and then enter i to have the interest rate computed. If you do so, you will find that i 3, or 3% semiannually, as we claimed. (Notice that just as the cash flows are paid semiannually, the computed interest rate is a rate per semiannual time period.) You can also find bond prices given a yield to maturity. For example, we saw in Example 9.2 that if the yield to maturity is 5% semiannually, the bond price will be $810.71. You can confirm this with the following inputs on your calculator: n 60; i 5; FV 1,000; PMT 40 and then computing PV to find that PV 810.71. Once again, your calculator may report the result as 810.71.

current yield Annual coupon divided by bond price.

premium bonds Bonds selling above par value.

Yield to maturity is different from the current yield of a bond, which is the bond’s annual coupon payment divided by the bond price. For example, for the 8%, 30-year bond currently selling at $1,276.76, the current yield would be $80/$1,276.76 0.0627, or 6.27% per year. In contrast, recall that the effective annual yield to maturity is 6.09%. For this bond, which is selling at a premium over par value ($1,276 rather than $1,000), the coupon rate (8%) exceeds the current yield (6.27%), which exceeds the yield to maturity (6.09%). The coupon rate exceeds current yield because the coupon rate divides the coupon payments by par value ($1,000) rather than by the bond price ($1,276). In turn, the current yield exceeds yield to maturity because the yield to maturity accounts for the built-in capital loss on the bond; the bond bought today for $1,276 will eventually fall in value to $1,000 at maturity. This example illustrates a general role: for premium bonds (bonds selling above par value), coupon rate is greater than current yield, which in turn is greater than yield to maturity.

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309

For discount bonds (bonds selling below par value), these relationships are reversed (see Concept Check 3). It is common to hear people talking loosely about the yield on a bond. In these cases, they almost always are referring to the yield to maturity.

discount bonds

9

3. What will be the relationship among coupon rate, current yield, and yield to maturity for bonds selling at discounts from par? Illustrate using the 8% (semiannual payment) coupon bond assuming it is selling at a yield to maturity of 10%.

Bonds selling below par value.

4. A 20-year maturity 9% coupon bond paying coupons semiannually is callable in five years at a call price of $1,050. The bond currently sells at a yield to maturity of 8% (bond equivalent yield). What is the yield to call?

Realized Compound Yield versus Yield to Maturity We have noted that yield to maturity will equal the rate of return realized over the life of the bond if all coupons are reinvested at an interest rate equal to the bond’s yield to maturity. Consider for example, a two-year bond selling at par value paying a 10% coupon once a year. The yield to maturity is 10%. If the $100 coupon payment is reinvested at an interest rate of 10%, the $1,000 investment in the bond will grow after two years to $1,210, as illustrated in Figure 9.5, Panel A. The coupon paid in the first year is reinvested and grows with interest to a second-year value of $110, which, together with the second coupon payment and payment of par value in the second year, results in a total value of $1,210. The compound growth rate of invested funds, therefore, is calculated from

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F I G U R E 9.5

A. Reinvestment rate = 10% $1,100

Cash flow: Time: 0

311

Growth of invested funds

$100 1

2 $1,100

Future value:

= $1,100

100 x 1.10 = $ 110 $1,210

B. Reinvestment rate = 8% $1,100

Cash flow: Time: 0

$100 1

2 $1,100

Future value:

= $1,100

100 x 1.08 = $ 108 $1,208

$1,000 (1 yrealized)2 $1,210 yrealized 0.10 10% With a reinvestment rate equal to the 10% yield to maturity, the realized compound yield equals yield to maturity. But what if the reinvestment rate is not 10%? If the coupon can be invested at more than 10%, funds will grow to more than $1,210, and the realized compound return will exceed 10%. If the reinvestment rate is less than 10%, so will be the realized compound return. Consider the following example. If the interest rate earned on the first coupon is less than 10%, the final value of the investment will be less than $1,210, and the realized compound yield will be less than 10%. Suppose the interest rate at which the coupon can be invested equals 8%. The following calculations are illustrated in Panel B of Figure 9.5. Future value of first coupon payment with interest earnings Cash payment in second year (final coupon plus par value) Total value of investment with reinvested coupons

$100 1.08 $ 108 1,100 $1,208

The realized compound yield is computed by calculating the compound rate of growth of invested funds, assuming that all coupon payments are reinvested. The investor purchased the bond for par at $1,000, and this investment grew to $1,208. $1,000(1 yrealized)2 $1,208 yrealized 0.0991 9.91%

EXAMPLE 9.5 Realized Compound Yield

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horizon analysis Analysis of bond returns over multiyear horizon, based on forecasts of bond’s yield to maturity and reinvestment rate of coupons.

9.6 EXAMPLE Horizon Analysis

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Example 9.5 highlights the problem with conventional yield to maturity when reinvestment rates can change over time. However, in an economy with future interest rate uncertainty, the rates at which interim coupons will be reinvested are not yet known. Therefore, while realized compound yield can be computed after the investment period ends, it cannot be computed in advance without a forecast of future reinvestment rates. This reduces much of the attraction of the realized yield measure. We also can calculate realized compound yield over holding periods greater than one period. This is called horizon analysis and is similar to the procedure in Example 9.5. The forecast of total return will depend on your forecasts of both the yield to maturity of the bond when you sell it and the rate at which you are able to reinvest coupon income. With a longer investment horizon, however, reinvested coupons will be a larger component of your final proceeds.

Suppose you buy a 30-year, 7.5% (annual payment) coupon bond for $980 (when its yield to maturity is 7.67%) and plan to hold it for 20 years. Your forecast is that the bond’s yield to maturity will be 8% when it is sold and that the reinvestment rate on the coupons will be 6%. At the end of your investment horizon, the bond will have 10 years remaining until expiration, so the forecast sales price (using a yield to maturity of 8%) will be $966.45. The 20 coupon payments will grow with compound interest to $2,758.92. (This is the future value of a 20-year $75 annuity with an interest rate of 6%. Based on these forecasts, your $980 investment will grow in 20 years to $966.45 $2,758.92 $3,725.37. This corresponds to an annualized compound return of 6.90%, calculated by solving for r in the equation $980 (1 r)20 $3,725.37.

9.4

BOND PRICES OVER TIME

As we noted earlier, a bond will sell at par value when its coupon rate equals the market interest rate. In these circumstances, the investor receives fair compensation for the time value of money in the form of the recurring interest payments. No further capital gain is necessary to provide fair compensation. When the coupon rate is lower than the market interest rate, the coupon payments alone will not provide investors as high a return as they could earn elsewhere in the market. To receive a fair return on such an investment, investors also need to earn price appreciation on their bonds. The bonds, therefore, would have to sell below par value to provide a “built-in” capital gain on the investment. To illustrate this point, suppose a bond was issued several years ago when the interest rate was 7%. The bond’s annual coupon rate was thus set at 7%. (We will suppose for simplicity that the bond pays its coupon annually.) Now, with three years left in the bond’s life, the interest rate is 8% per year. The bond’s fair market price is the present value of the remaining annual coupons plus payment of par value. That present value is $70 Annuity factor(8%, 3) $1,000 PV factor(8%, 3) $974.23 which is less than par value. In another year, after the next coupon is paid, the bond would sell at $70 Annuity factor(8%, 2) $1,000 PV factor(8%, 2) $982.17 thereby yielding a capital gain over the year of $7.94. If an investor had purchased the bond at $974.23, the total return over the year would equal the coupon payment plus capital gain, or $70 $7.94 $77.94. This represents a rate of return of $77.94/$974.23, or 8%, exactly the current rate of return available elsewhere in the market.

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F I G U R E 9.6

Price ($) Premium bond

Price paths of coupon bonds in the case of constant market interest rates

1,000

Discount bond

0

Maturity date

Time

5. What will the bond price be in yet another year, when only one year remains until maturity? What is the rate of return to an investor who purchases the bond at $982.17 and sells it one year hence? When bond prices are set according to the present value formula, any discount from par value provides an anticipated capital gain that will augment a below-market coupon rate just sufficiently to provide a fair total rate of return. Conversely, if the coupon rate exceeds the market interest rate, the interest income by itself is greater than that available elsewhere in the market. Investors will bid up the price of these bonds above their par values. As the bonds approach maturity, they will fall in value because fewer of these above-market coupon payments remain. The resulting capital losses offset the large coupon payments so that the bondholder again receives only a fair rate of return. Problem 9 at the end of the chapter asks you to work through the case of the high coupon bond. Figure 9.6 traces out the price paths of high and low coupon bonds (net of accrued interest) as time to maturity approaches, at least for the case in which the market interest rate is constant. The low coupon bond enjoys capital gains, while the high coupon bond suffers capital losses.8 We use these examples to show that each bond offers investors the same total rate of return. Although the capital gain versus income components differ, the price of each bond is set to provide competitive rates, as we should expect in well-functioning capital markets. Security returns all should be comparable on an after-tax risk-adjusted basis. If they are not, investors will try to sell low-return securities, thereby driving down the prices until the total return at the now lower price is competitive with other securities. Prices should continue to adjust until all securities are fairly priced in that expected returns are appropriate (given necessary risk and tax adjustments).

Yield to Maturity versus Holding-Period Return We just considered an example in which the holding-period return and the yield to maturity were equal: in our example, the bond yield started and ended the year at 8%, and the bond’s holding-period return also equaled 8%. This turns out to be a general result. When the yield to 8

If interest rates are volatile, the price path will be “jumpy,” vibrating around the price path in Figure 9.6, and reflecting capital gains or losses as interest rates fall or rise. Ultimately, however, the price must reach par value at the maturity date, so on average, the price of the premium bond will fall over time while that of the discount bond will rise.

Consider a 30-year bond paying an annual coupon of $80 and selling at par value of $1,000. The bond’s initial yield to maturity is 8%. If the yield remains at 8% over the year, the bond price will remain at par, so the holding-period return also will be 8%. But if the yield falls below 8%, the bond price will increase. Suppose the price increases to $1,050. Then the holding-period return is greater than 8%: Holding-period return

$80 ($1,050 $1,000) $1,000

.13, or 13%

6. Show that if yield to maturity increases, then holding-period return is less than initial yield. For example, suppose that by the end of the first year, the bond’s yield to maturity is 8.5%. Find the one-year holding-period return and compare it to the bond’s initial 8% yield to maturity. Here is another way to think about the difference between yield to maturity and holdingperiod return. Yield to maturity depends only on the bond’s coupon, current price, and par value at maturity. All of these values are observable today, so yield to maturity can be easily calculated. Yield to maturity can be interpreted as a measure of the average rate of return if the investment in the bond is held until the bond matures. In contrast, holding-period return is the rate of return over a particular investment period and depends on the market price of the bond at the end of that holding period; of course this price is not known today. Since bond prices over the holding period will respond to unanticipated changes in interest rates, holding-period return can at most be forecast.

Zero-Coupon Bonds Original issue discount bonds are less common than coupon bonds issued at par. These are bonds that are issued intentionally with low coupon rates that cause the bond to sell at a discount from par value. An extreme example of this type of bond is the zero-coupon bond, which carries no coupons and must provide all its return in the form of price appreciation. Zeros provide only one cash flow to their owners, and that is on the maturity date of the bond. U.S. Treasury bills are examples of short-term zero-coupon instruments. The Treasury issues or sells a bill for some amount less than $10,000, agreeing to repay $10,000 at the bill’s maturity. All of the investor’s return comes in the form of price appreciation over time. Longer term zero-coupon bonds are commonly created from coupon-bearing notes and bonds with the help of the U.S. Treasury. A broker that purchases a Treasury coupon bond may ask the Treasury to break down the cash flows to be paid by the bond into a series of independent securities, where each security is a claim to one of the payments of the original bond. For example, a 10-year coupon bond would be “stripped” of its 20 semiannual coupons and

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F I G U R E 9.7

1,000 900 800 700 600 500 400 300 200 100 0 30

27

24

21

18

15

12

9

6

3

0

Price ($)

The price of a 30-year zero-coupon bond over time at a yield to maturity of 10%. Price equals 1000/(1.10)T where T is time until maturity.

Year Today

Maturity date

each coupon payment would be treated as a stand-alone zero-coupon bond. The maturities of these bonds would thus range from six months to 10 years. The final payment of principal would be treated as another stand-alone zero-coupon security. Each of the payments would then be treated as an independent security and assigned its own CUSIP number, the security identifier that allows for electronic trading over the Fedwire system. The payments are still considered obligations of the U.S. Treasury. The Treasury program under which coupon stripping is performed is called STRIPS (Separate Trading of Registered Interest and Principal of Securities), and these zero-coupon securities are called Treasury strips. Turn back to Figure 9.1 for a listing of these bonds appearing in The Wall Street Journal. What should happen to prices of zeros as time passes? On their maturity dates, zeros must sell for par value. Before maturity, however, they should sell at discounts from par, because of the time value of money. As time passes, price should approach par value. In fact, if the interest rate is constant, a zero’s price will increase at exactly the rate of interest. To illustrate this property, consider a zero with 30 years until maturity, and suppose the market interest rate is 10% per year. The price of the bond today will be $1,000/(1.10)30 $57.31. Next year, with only 29 years until maturity, if the yield to maturity is still 10%, the price will be $1,000/(1.10)29 $63.04, a 10% increase over its previous-year value. Because the par value of the bond is now discounted for one fewer year, its price has increased by the one-year discount factor. Figure 9.7 presents the price path of a 30-year zero-coupon bond until its maturity date for an annual market interest rate of 10%. The bond’s price rises exponentially, not linearly, until its maturity.

After-Tax Returns The tax authorities recognize that the “built-in” price appreciation on original-issue discount (OID) bonds such as zero-coupon bonds represents an implicit interest payment to the holder of the security. The Internal Revenue Service (IRS), therefore, calculates a price appreciation schedule to impute taxable interest income for the built-in appreciation during a tax year, even if the asset is not sold or does not mature until a future year. Any additional gains or losses that arise from changes in market interest rates are treated as capital gains or losses if the OID bond is sold during the tax year.

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9.8 EXAMPLE Taxation of OID Bonds

If the interest rate originally is 10%, the 30-year zero would be issued at a price of $1,000/(1.10)30 $57.31. The following year, the IRS calculates what the bond price would be if the yield remains at 10%. This is $1,000/(1.10)29 $63.04. Therefore, the IRS imputes interest income of $63.04 $57.31 $5.73. This amount is subject to tax. Notice that the imputed interest income is based on a “constant yield method” that ignores any changes in market interest rates. If interest rates actually fall, let’s say to 9.9%, the bond price actually will be $1,000/ (1.099)29 $64.72. If the bond is sold, then the difference between $64.72 and $63.04 will be treated as capital gains income and taxed at the capital gains tax rate. If the bond is not sold, then the price difference is an unrealized capital gain and does not result in taxes in that year. In either case, the investor must pay taxes on the $5.73 of imputed interest at the ordinary income tax rate.

The procedure illustrated in Example 9.8 is applied to the taxation of other original issue discount bonds, even if they are not zero-coupon bonds. Consider, as another example, a 30-year maturity bond that is issued with a coupon rate of 4% and a yield to maturity of 8%. For simplicity, we will assume that the bond pays coupons once annually. Because of the low coupon rate, the bond will be issued at a price far below par value, specifically at a price of $549.69. (Confirm this for yourself.) If the bond’s yield to maturity remains at 8%, then its price in one year will rise to $553.66. (Confirm this also.) This provides a pretax holdingperiod return of exactly 8%: HPR

$40 ($553.66 $549.69) 0.08 $549.69

The increase in the bond price based on a constant yield, however, is treated as interest income, so the investor is required to pay taxes on imputed interest income of $553.66 $549.69 $3.97, as well as on the explicit coupon income of $40. If the bond’s yield actually changes during the year, the difference between the bond’s price and the “constant yield value” of $553.66 would be treated as capital gains income if the bond were sold at year-end.

Concept CHECK

>

7. Suppose that the yield to maturity of the 4% coupon, 30-year maturity bond actually falls to 7% by the end of the first year, and that the investor sells the bond after the first year. If the investor’s tax rate on interest income is 36% and the tax rate on capital gains is 28%, what is the investor’s after-tax rate of return?

9.5 investment grade bond A bond rated BBB and above by Standard & Poor’s, or Baa and above by Moody’s.

speculative grade or junk bond A bond rated BB or lower by Standard & Poor’s, Ba or lower by Moody’s, or an unrated bond.

DEFAULT RISK AND BOND PRICING

Although bonds generally promise a fixed flow of income, that income stream is not riskless unless the investor can be sure the issuer will not default on the obligation. While U.S. government bonds may be treated as free of default risk, this is not true of corporate bonds. If the company goes bankrupt, the bondholders will not receive all the payments they have been promised. Therefore, the actual payments on these bonds are uncertain, for they depend to some degree on the ultimate financial status of the firm. Bond default risk is measured by Moody’s Investor Services, Standard & Poor’s Corporation, Duff and Phelps, and Fitch Investors Service, all of which provide financial information on firms as well as quality ratings of large corporate and municipal bond issues. Each firm assigns letter grades to the bonds of corporations and municipalities to reflect their assessment of the safety of the bond issue. The top rating is AAA or Aaa. Moody’s modifies each rating class with a 1, 2, or 3 suffix (e.g., Aaa1, Aaa2, Aaa3) to provide a finer gradation of ratings. The other agencies use a or modification. Those rated BBB or above (S&P, Duff and Phelps, Fitch) or Baa and above (Moody’s) are considered investment grade bonds, while lower-rated bonds are classified as speculative

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Bond Ratings

Standard & Poor’s Moody’s

317

Very High Quality

High Quality

Speculative

Very Poor

AAA AA Aaa Aa

A BBB A Baa

BB B Ba B

CCC D Caa C

At times both Moody’s and Standard & Poor’s use adjustments to these ratings. S&P uses plus and minus signs: A is the strongest A rating and A the weakest. Moody’s uses a 1, 2, or 3 designation—with 1 indicating the strongest. Moody’s S&P Aaa

AAA Debt rated Aaa and AAA has the highest rating. Capacity to pay interest and principal is extremely strong.

Aa

AA

Debt rated Aa and AA has a very strong capacity to pay interest and repay principal. Together with the highest rating, this group comprises the high-grade bond class.

A

A

Debt rated A has a strong capacity to pay interest and repay principal, although it is somewhat more susceptible to the adverse effects of changes in circumstances and economic conditions than debt in higherrated categories.

Baa

BBB

Debt rated Baa and BBB is regarded as having an adequate capacity to pay interest and repay principal. Whereas it normally exhibits adequate protection parameters, adverse economic conditions or changing circumstances are more likely to lead to a weakened capacity to pay interest and repay principal for debt in this category than in higher-rated categories. These bonds are medium grade obligations.

Ba

BB

Debt rated in these categories is regarded, on balance, as predomi-

B

B

antly speculative with respect to capacity to pay interest and repay

Caa

CCC

principal in accordance with the terms of the obligation. BB and Ba

Ca

CC

indicate the lowest degree of speculation, and CC and Ca the highest degree of speculation. Although such debt will likely have some quality and protective characteristics, these are outweighed by large uncertainties or major risk exposures to adverse conditions. Some issues may be in default.

C

C

This rating is reserved for income bonds on which no interest is being paid.

D

D

Debt rated D is in default, and payment of interest and/or repayment of principal is in arrears.

grade or junk bonds. Certain regulated institutional investors such as insurance companies have not always been allowed to invest in speculative grade bonds. Figure 9.8 provides the definitions of each bond rating classification.

Junk Bonds Junk bonds, also known as high-yield bonds, are nothing more than speculative grade (lowrated or unrated) bonds. Before 1977, almost all junk bonds were “fallen angels,” that is, bonds issued by firms that originally had investment grade ratings but that had since been downgraded. In 1977, however, firms began to issue “original-issue junk.”

Definitions of each bond rating class Sources: From Stephen A. Ross, Randolph W. Westerfield, and Jeffrey A. Jaffe, Corporate Finance, McGraw-Hill Publishing. Data from various editions of Standard & Poor’s Bond Guide and Moody’s Bond Guide.

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Much of the credit for this innovation is given to Drexel Burnham Lambert, and especially its trader, Michael Milken. Drexel had long enjoyed a niche as a junk bond trader and had established a network of potential investors in junk bonds. Firms not able to muster an investment grade rating were happy to have Drexel (and other investment bankers) market their bonds directly to the public, as this opened up a new source of financing. Junk issues were a lower-cost financing alternative than borrowing from banks. High-yield bonds gained considerable notoriety in the 1980s when they were used as financing vehicles in leveraged buyouts and hostile takeover attempts. Shortly ther