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• Front Matter
• About the Authors
• New to the 9th Edition
• Preface
• Final Thoughts
• Part 1: INTRODUCTION
• 1: Introduction
• OUTLINE OF THE BOOK
• THE ECONOMIC THEORY OF CHOICE: AN ILLUSTRATION UNDER CERTAINTY
• The Opportunity Set
• Figure 1.1: The investor’s opportunity set.
• The Indifference Curves
• Figure 1.2: Indifference curves.
• The Solution
• Figure 1.3: Investor equilibrium.
• An Example: Determining Equilibrium Interest Rates
• CONCLUSION
• MULTIPLE ASSETS AND RISK
• Figure 1.4: Investor’s opportunity set with several alternatives.
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• 2: Financial Securities
• TYPES OF MARKETABLE FINANCIAL SECURITIES
• Money Market Securities
• Table 2.1: Money Market Instruments
• Treasury Bills
• Repurchase Agreements (Repos)
• Other Short-Term Instruments
• The London Interbank Offered Rate (LIBOR)
• Capital Market Securities
• Fixed Income Securities
• Treasury Notes and Bonds
• Federal Agency Securities
• Municipal Bonds
• Corporate Bonds
• Not-So-Fixed Income Securities
• Preferred Stock
• Asset-Backed Securities
• Mortgage-Backed Securities
• Common Stock (Equity)
• Derivative Instruments
• Indirect Investing
• THE RETURN CHARACTERISTICS OF ALTERNATIVE SECURITY TYPES
• Table 2.2: Return and Risk for Selected Types of Securities in Percent per Year (1926–2011)
• STOCK MARKET INDEXES
• BOND MARKET INDEXES
• CONCLUSION
• 3: Financial Markets
• TRADING MECHANICS
• Market Orders
• Limit Orders
• Short Sale
• Stop Orders
• Length of Time an Order Is Outstanding
• MARGIN
• Margin Long Purchase
• Initial Margin Long Purchase
• Maintenance Margin Long Purchase
• Effect of Margin on Return
• Margin Requirements for Short Sales
• MARKETS
• Characteristics of Markets
• Major Markets
• Stock Markets
• Bond Markets
• Primary Markets
• Government Bonds
• Corporate Issues
• Clearing Procedures
• TRADE TYPES AND COSTS
• Types of Trades
• Trading Costs
• CONCLUSION
• Part 2: PORTFOLIO ANALYSIS
• Section 1: Mean Variance Portfolio Theory
• 4: The Characteristics of the Opportunity Set under Risk
• Table 4.1: Data on Three Hypothetical Events
• DETERMINING THE AVERAGE OUTCOME
• Table 4.2: Return on Various Assets
• A MEASURE OF DISPERSION
• Table 4.3: Returns on Various Investmentsa
• VARIANCE OF COMBINATIONS OF ASSETS
• Table 4.4: Dollars at Period 2 Given Alternative Investments
• Figure 4.1: Securities and predetermined portfolios.
• CHARACTERISTICS OF PORTFOLIOS IN GENERAL
• Table 4.5: Monthly Returns on Microsoft, Dell, and G.E. (in percent, 2011)
• Table 4.6: Calculating Covariances
• Table 4.7: Covariance and Correlation Coefficients (in Parentheses) between Assets
• Table 4.8: Effect of Diversification
• Figure 4.2: The effect of number of securities on risk of the portfolio in the United States (1975).
• Figure 4.3: The effect of securities on risk in the United Kingdom (1975).
• Table 4.9: Percentage of the Risk on an Individual Security That Can Be Eliminated by Holding a Random Portfolio of Stocks within Selected National Markets and among National Markets (1975)
• TWO CONCLUDING EXAMPLES
• Bond Stock Allocation
• Table 4.10: Mean Return and Standard Deviation for Combinations of Stocks and Bonds
• Figure 4.4: Combinations of bonds and stocks.
• Table 4.11: Mean Return and Standard Deviation for Combinations of Domestic and International Stocks
• Domestic Foreign Allocation
• Figure 4.5: Combinations of U.S. stocks and international stocks.
• CONCLUSION
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• 5: Delineating Efficient Portfolios
• COMBINATIONS OF TWO RISKY ASSETS REVISITED: SHORT SALES NOT ALLOWED
• Case 1—Perfect Positive Correlation (ρ = +1)
• Table 5.1: The Expected Return and Standard Deviation of a Portfolio of Colonel Motors and Separated Edison When ρ = +1
• Figure 5.1: Relationship between expected return and standard deviation when ρ=+1.
• Case 2—Perfect Negative Correlation (ρ = −1.0)
• Table 5.2: The Expected Return and Standard Deviation of a Portfolio of Colonel Motors and Separated Edison When ρ = −1
• Figure 5.2: Relationship between expected return and standard deviation when ρ=−1.
• Figure 5.3: Relationship between expected return and standard deviation for various correlation coefficients.
• Case 3—No Relationship between Returns on the Assets (ρ = 0)
• Table 5.3: The Expected Return and Standard Deviation for a Portfolio of Colonel Motors and Separated Edison When ρ = 0
• Figure 5.4: Relationship between expected return and standard deviation when ρ=0.
• Case 4—Intermediate Risk (ρ = 0.5)
• Table 5.4: The Expected Return and Standard Deviation of a Portfolio of Colonel Motors and Separated Edison When ρ = 0.5
• Figure 5.5: Relationship between expected return and standard deviation of return for various correlation coefficients.
• THE SHAPE OF THE PORTFOLIO POSSIBILITIES CURVE
• Figure 5.6: Various possible relationships for expected return and standard deviation when the minimum variance portfolio and Colonel Motors are combined.
• Figure 5.7: Various possible relationships between expected return and standard deviation of return when the minimum variance portfolio is combined with portfolio S.
• The Efficient Frontier with No Short Sales
• Figure 5.8: Risk and return possibilities for various assets and portfolios.
• Figure 5.9: The efficient frontier.
• Figure 5.10: An impossible shape for the efficient frontier.
• The Efficient Frontier with Short Sales Allowed
• Table 5.5: The Expected Return and Standard Deviation When Short Sales Are Allowed
• Figure 5.11: Expected return standard deviation combinations of Colonel Motors and Separated Edison when short sales are allowed.
• THE EFFICIENT FRONTIER WITH RISKLESS LENDING AND BORROWING
• Figure 5.12: The efficient set when short sales are allowed.
• Figure 5.13: Expected return and risk when the risk–free rate is mixed with portfolio A.
• Figure 5.14: Combinations of the riskless asset and various risky portfolios.
• Figure 5.15: The efficient frontier with lending but not borrowing at the riskless rate.
• Figure 5.16: The efficient frontier with riskless lending and borrowing at different rates.
• EXAMPLES AND APPLICATIONS
• Considerations in Determining Inputs
• Inflation-Adjusted Inputs to Optimization
• Table 5.6: Returns with No Inflation Adjustment
• Table 5.7: Returns after Adjusting for Inflation
• Input Estimation Uncertainty
• Table 5.8: Returns over Different Decades
• Short-Horizon Inputs and Long-Horizon Portfolio Choice
• THREE EXAMPLES
• Figure 5.17: The efficient frontier of stocks and bonds.
• Figure 5.18: The efficient frontier of domestic and international stocks.
• Figure 5.19: Combinations of bonds, U.S. stocks, and international stocks.
• CONCLUSION
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• 6: Techniques for Calculating the Efficient Frontier
• Figure 6.1: Combinations of the riskless asset in a risky portfolio.
• SHORT SALES ALLOWED WITH RISKLESS LENDING AND BORROWING
• Figure 6.2: The efficient set with riskless lending and borrowing.
• SHORT SALES ALLOWED: NO RISKLESS LENDING AND BORROWING
• RISKLESS LENDING AND BORROWING WITH SHORT SALES NOT ALLOWED
• Figure 6.3: Tangency portfolios for different riskless rates.
• NO SHORT SELLING AND NO RISKLESS LENDING AND BORROWING
• THE INCORPORATION OF ADDITIONAL CONSTRAINTS
• Table 6.1: Input Data for Asset Allocation
• AN EXAMPLE
• Figure 6.4: The efficient frontier with riskless lending and borrowing and short sales allowed.
• Figure 6.5: The efficient frontier with no riskless lending and borrowing and no short sales.
• Table 6.2: Proportions Invested When Short Sales Are Not Allowed
• CONCLUSION
• APPENDIX A: AN ALTERNATIVE DEFINITION OF SHORT SALES
• APPENDIX B: DETERMINING THE DERIVATIVE
• APPENDIX C: SOLVING SYSTEMS OF SIMULTANEOUS EQUATIONS
• APPENDIX D: A GENERAL SOLUTION
• Determining the General Coefficient from Two Portfolios
• Tracing Out the Efficient Frontier
• The Number of Securities Included
• Figure 6.6: The minimum variance frontier.
• APPENDIX E: QUADRATIC PROGRAMMING AND KUHN–TUCKER CONDITIONS
• Figure 6.7: Portfolio proportion as a function of the riskless rate.
• Figure 6.8: Value of the function as X changes.
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• Section 2: Simplifying the Portfolio Selection Process
• 7: The Correlation Structure of Security Returns—the Single-Index Model
• THE INPUTS TO PORTFOLIO ANALYSIS
• SINGLE-INDEX MODELS: AN OVERVIEW
• Table 7.1: Decomposition of Returns for the Single-Index Model
• CHARACTERISTICS OF THE SINGLE-INDEX MODEL
• Table 7.2: Residual Risk and Portfolio Size
• ESTIMATING BETA
• Estimating Historical Betas
• Figure 7.1: Plot of security return versus market return.
• Accuracy of Historical Betas
• Table 7.3: Association of Betas over Time
• Adjusting Historical Estimates
• Table 7.4: Betas on Ranked Portfolios for Two Successive Periods
• Measuring the Tendency of Betas to Regress toward 1—Blume’s Technique
• Figure 7.2: Plot of beta in two adjacent periods.
• Measuring the Tendency of Betas to Regress toward 1—Vasicek’s Technique
• Accuracy of Adjusted Beta
• Betas as Forecasters of Correlation Coefficients
• Fundamental Betas
• Table 7.5: Correlation between Accounting Measures of Risk and Market Beta
• THE MARKET MODEL
• AN EXAMPLE
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• 8: The Correlation Structure of Security Returns—Multi-Index Models and Grouping Techniques
• MULTI-INDEX MODELS
• General Multi-index Models
• Industry Index Models
• How Well Do Multi-index Models Work?
• AVERAGE CORRELATION MODELS
• MIXED MODELS
• FUNDAMENTAL MULTI-INDEX MODELS
• Fama–French Models
• Chen, Roll, and Ross Model
• Table 8.1: Sector Sensitivities
• Improving Forecasts of Correlation
• CONCLUSION
• APPENDIX A: PROCEDURE FOR REDUCING ANY MULTI-INDEX MODEL TO A MULTI-INDEX MODEL WITH ORTHOGONAL INDEXES
• APPENDIX B: MEAN RETURN, VARIANCE, AND COVARIANCE OF A MULTI-INDEX MODEL
• Expected Return
• Variance of Return
• The Covariance
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• 9: Simple Techniques for Determining the Efficient Frontier
• THE SINGLE-INDEX MODEL
• The Formation of Optimal Portfolios
• Ranking Securities
• Table 9.1: Data Required to Determine Optimal Portfolio RF = 5%
• Table 9.2: Calculations for Determining Cutoff Rate with σm2=10
• Setting the Cutoff Rate (C*)
• Calculating the Cutoff Rate C*
• Constructing the Optimal Portfolio
• Another Example
• Table 9.3: Data Required to Determine Optimal Portfolio; RF = 5
• Table 9.4: Calculations for Determining Cutoff Rate with σm2=10
• Short Sales Allowed
• Table 9.5: Optimum Percentages
• SECURITY SELECTION WITH A PURCHASABLE INDEX
• Constructing an Efficient Frontier
• THE CONSTANT CORRELATION MODEL
• Ranking and Selecting from among Securities—Short Sales Not Allowed
• Setting the Cutoff Rate
• Table 9.6: Data to Determine Ranking RF = 5%
• Table 9.7: Determining the Cutoff Rate ρ = 0.5
• Short Sales Allowed
• OTHER RETURN STRUCTURES
• AN EXAMPLE
• CONCLUSION
• APPENDIX A: SINGLE-INDEX MODEL—SHORT SALES ALLOWED
• APPENDIX B: CONSTANT CORRELATION COEFFICIENT—SHORT SALES ALLOWED
• APPENDIX C: SINGLE-INDEX MODEL—SHORT SALES NOT ALLOWED
• APPENDIX D: CONSTANT CORRELATION COEFFICIENT—SHORT SALES NOT ALLOWED
• APPENDIX E: SINGLE-INDEX MODEL, SHORT SALES ALLOWED, AND A MARKET ASSET
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• Section 3: Selecting the Optimum Portfolio
• 10: Estimating Expected Returns
• AGGREGATE ASSET ALLOCATION
• Market Timing or Dynamic Asset Allocation
• Estimating Expected Returns
• Table 10.1
• History and the Equity Risk Premium
• Bayesian Models of Expected Returns
• Time Variation in Expected Returns
• Table 10.2: Summary Statistics for New York Stock Exchange Returns, U.S. Bond Yields, Call Money Rates, and Inflation 1792–1925
• A New Approach: The Recovery Theorem
• Table 10.3: Summary Statistics for U.S. Stocks, Bonds, Bills, and Inflation 1926–2011
• FORECASTING INDIVIDUAL SECURITY RETURNS
• Figure 10.1: Relationship between expected return and beta.
• PORTFOLIO ANALYSIS WITH DISCRETE DATA
• APPENDIX: THE ROSS RECOVERY THEOREM—A NEW APPROACH TO USING MARKET DATA TO CALCULATE EXPECTED RETURN
• BIBLIOGRAPHY
• 11: How to Select among the Portfolios in the Opportunity Set
• CHOOSING DIRECTLY
• Table 11.1: Return and Risk on Portfolios in the Efficient Set
• Figure 11.1: The distribution of returns for portfolios shown in Table 11.1
• AN INTRODUCTION TO PREFERENCE FUNCTIONS
• Table 11.2: Two Alternative Investments
• Table 11.3: Data for Ranking Hockey Teams
• Table 11.4: A Weighing Function
• Table 11.5: Outcomes and Associated Probabilities for Three Investments
• Table 11.6: Including Utility
• RISK TOLERANCE FUNCTIONS
• Table 11.7: Choices Using Risk Tolerance
• SAFETY FIRST
• Table 11.8: Mean Returns, Standard Deviations, and Lower Limits
• Figure 11.2: Lines of constant preference—Roy’s criterion.
• Figure 11.3: The portfolio choice problem with Kataoka’s safety-first rule.
• Figure 11.4: The investor’s choice problem—Telser’s criterion.
• Figure 11.5: No feasible portfolio—Telser’s criterion.
• MAXIMIZING THE GEOMETRIC MEAN RETURN
• Table 11.9: Geometric Mean Returns
• VALUE AT RISK (VaR)
• UTILITY AND THE EQUITY RISK PREMIUM
• Empirical Solutions
• Theoretical Solutions
• OPTIMAL INVESTMENT STRATEGIES WITH INVESTOR LIABILITIES
• Figure 11.6: Expected return versus variance considering liabilities.
• LIABILITIES AND SAFETY-FIRST PORTFOLIO SELECTION
• SIMULATIONS IN PORTFOLIO CHOICE
• Figure 11.7: Trade-off between maximum return and different probabilities.
• Figure 11.8: Simulated distribution of average returns.
• Figure 11.9: Simulated growth of $1 over 79 years.
• Multiple-Asset Bootstrapping
• Biased Bootstrapping and Scenario Analysis
• Time Series Dependence
• Bootstrapping Applications
• Applications
• Value at Risk
• Dynamic choice
• Taxes
• Table 11.10: Simulated Total Return Distributions for the Period 1976–2000: Geometric Average Annual Rates (in %), Selected Percentiles, All Series
• CONCLUSION
• APPENDIX: THE ECONOMIC PROPERTIES OF UTILITY FUNCTIONS
• Table 11.11: An Example of a Fair Gamble
• Figure 11.10: Characteristics of functions with different risk-aversion coefficients. (1) Utility function of a risk-seeking investor. (2) Utility function of a risk-neutral investor. (3) Utility function of a risk-averse investor.
• Table 11.12: Implications of Attitude toward Risk
• RELATIVE RISK AVERSION AND WEALTH
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• Section 4: Widening the Selection Universe
• 12: International Diversification
• HISTORICAL BACKGROUND
• CALCULATING THE RETURN ON FOREIGN INVESTMENTS
• Figure 12.1a: Typical price movement of the representative stocks of Great Britain, France, United States of America, Argentina. Produced in 1907.
• Figure 12.1b: Individual price movements of 10 stocks covering different geographical divisions. Produced in 1907.
• THE RISK OF FOREIGN SECURITIES
• Table 12.1: Correlation Among Stock Indexes Measured in U.S. Dollars (2002–2011)
• Table 12.2: Risk for U.S. Investors in Stocks 2002–2011
• Figure 12.2: Average correlation of capital appreciation returns for all available markets. This figure shows the time series of the average off-diagonal correlation of dollar-valued capital appreciation returns for all available markets. A rolling window of 60 months is used. Source: Goetzmann, Li, and Rouwenhorst (2005)
• Figure 12.3: Risk reduction from international diversification: Selected periods. This figure shows the ratio of the average covariance of the equally weighted portfolio of country indexes scaled by the average variance of the country indexes, as a function of the number of countries in the portfolio. Source: Goetzmann, Li, and Rouwenhorst (2005)
• Figure 12.4: Average relative covariance versus investment opportunity set. Source: Goetzmann, Li, and Rouwenhorst (2005).
• Figure 12.5: Diversification with capital market weights. This figure shows the risk reduction for portfolios of 45 country indexes and the risk reduction of the four core countries. A rolling window of 120 months is used. Returns are exponentially weighted with a half time of 60 months. Source: Goetzmann, Li, and Rouwenhorst (2005).
• MARKET INTEGRATION
• RETURNS FROM INTERNATIONAL DIVERSIFICATION
• Table 12.3: Return to U.S. Investor in Stocks 2002–2011 (percent per annum)
• THE EFFECT OF EXCHANGE RISK
• Table 12.4: The Effect of Country of Domicile on Mean Returns and Risk 2002–2012
• RETURN EXPECTATIONS AND PORTFOLIO PERFORMANCE
• EMERGING MARKETS
• Figure 12.6: S&P/IFC Emerging Market Composite Index vs. S&P 500 Index, 1989–2011. (Courtesy Morningstar/Ibbotson Encorr)
• Figure 12.7: Sample of global markets from 1922 to 1994. Source: Goetzmann and Jorion (1991).
• International Diversification of Bonds
• Table 12.5: Correlations Among Bond Indicies Measured in U.S. Dollars (2002–2011)
• Table 12.6: Risk for U.S. Investors in Bonds 2002–2012
• OTHER EVIDENCE ON INTERNATIONALLY DIVERSIFIED PORTFOLIOS
• Table 12.7: Return to U.S. Investors in Bonds 2002–2012 (percent per annum)
• Table 12.8: Performance Data on Stock Funds (2002–2012)
• Table 12.9: Performance Data on Bond Funds (2002–2011)
• SOVEREIGN FUNDS
• MODELS FOR MANAGING INTERNATIONAL PORTFOLIOS
• Active Short-Term Bond Management
• CONCLUSION
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• Part 3: MODELS OF EQUILIBRIUM IN THE CAPITAL MARKETS
• 13: The Standard Capital Asset Pricing Model
• THE ASSUMPTIONS UNDERLYING THE STANDARD CAPITAL ASSET PRICING MODEL (CAPM)
• THE CAPM
• Deriving the CAPM—A Simple Approach
• Figure 13.1: The efficient frontier—no lending and borrowing.
• Figure 13.2: The efficient frontier with lending and borrowing.
• Figure 13.3: Combinations of portfolios.
• Figure 13.4: The security market line.
• Deriving the CAPM—A More Rigorous Approach
• PRICES AND THE CAPM
• CONCLUSION
• Figure 13.5: The efficient frontier.
• Figure 13.6: The security market line.
• APPENDIX: Appropriateness of the Single-Period Asset Pricing Model
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• 14: Nonstandard Forms of Capital Asset Pricing Models
• SHORT SALES DISALLOWED
• MODIFICATIONS OF RISKLESS LENDING AND BORROWING
• Figure 14.1: Portfolios in expected return beta space.
• No Riskless Lending or Borrowing
• Simple Proof
• Figure 14.2: The zero-beta capital asset pricing line.
• Rigorous Derivation
• Figure 14.3: The opportunity set with rate RF.
• Figure 14.4: The location of portfolios with return RF′.
• Proof
• Figure 14.5: The minimum-variance frontier.
• Riskless Lending but No Riskless Borrowing
• Figure 14.6: The opportunity set with riskless lending.
• Figure 14.7: The location of investments in expected return beta space.
• Other Lending and Borrowing Assumptions
• Figure 14.8: The opportunity set with a differential lending and borrowing rate.
• PERSONAL TAXES
• NONMARKETABLE ASSETS
• HETEROGENEOUS EXPECTATIONS
• NON-PRICE-TAKING BEHAVIOR
• MULTIPERIOD CAPM
• THE MULTI-BETA CAPM
• CONSUMPTION CAPM
• CONCLUSION
• APPENDIX: DERIVATION OF THE GENERAL EQUILIBRIUM WITH TAXES
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• 15: Empirical Tests of Equilibrium Models
• THE MODELS—EX ANTE EXPECTATIONS AND EX POST TESTS
• EMPIRICAL TESTS OF THE CAPM
• Some Hypotheses of the CAPM
• A Simple Test of the CAPM
• Table 15.1: Average Returns and Betas on Portfolios Ranked by Betas
• Figure 15.1: Estimated security market line.
• Some Early Empirical Tests
• Tests of Black, Jensen, and Scholes
• Table 15.2: Tests of the CAPM as Reported by Black, Jensen, and Scholes (1972)
• Tests of Fama and McBeth
• Table 15.3: Tests of the Two-Parameter Model
• Extensions of Fama and MacBeth
• TESTING SOME ALTERNATIVE FORMS OF THE CAPM MODEL
• TESTING THE POSTTAX FORM OF THE CAPM MODEL
• Testing the Consumption-Based CAPM (CCAPM)
• SOME RESERVATIONS ABOUT TRADITIONAL TESTS OF GENERAL EQUILIBRIUM RELATIONSHIPS AND SOME NEW RESEARCH
• Proof
• CONCLUSION
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• 16: The Arbitrage Pricing Model APT—A Multifactor Approach to Explaining Asset Prices
• APT—WHAT IS IT?
• A Simple Proof of APT
• A More Rigorous Proof of APT
• ESTIMATING AND TESTING APT
• Simultaneous Determination of Factors and Characteristics
• An Alternative Approach to Testing the APT
• Specifying Attributes of Securities
• Table 16.1: Cross-Sectional Data on Sharpe’s Multifactor Model
• Specifying the Influences Affecting the Return-Generating Process
• Specifying a Set of Portfolios Affecting the Return-Generating Process
• Table 16.2: Empirical Tests of Multifactor Asset Pricing Models 1963–2004
• APT AND CAPM
• RECAPITULATION
• Multi-index Models, APT, and Portfolio Management
• Review of Multi-index Models and APT
• Passive Management
• Active Management
• Factor Investing: An Active-Passive Approach
• Figure 16.1: Fama, French, and Carhart Factor Performance, 1927–2012. Source: Data courtesy of Kenneth French.
• Annualized Summary Statistics for Fama, French, and Carhart Factors, 1927–2011
• TERM STRUCTURE FACTOR
• CREDIT RISK FACTOR
• FOREIGN EXCHANGE [FX] CARRY
• VALUE FACTOR
• SIZE FACTOR
• MOMENTUM FACTOR
• VOLATILITY FACTOR
• LIQUIDITY FACTOR
• INFLATION FACTOR
• GDP FACTOR
• EQUITY RISK PREMIUM
• LIMITATIONS OF FACTOR INVESTING
• FACTOR INVESTING SUMMARY
• Performance Measurement and Attribution
• CONCLUSION
• APPENDIX A: A SIMPLE EXAMPLE OF FACTOR ANALYSIS
• Table 16.2: Correlation Coefficient between Returns in Four Countries
• APPENDIX B: SPECIFICATION OF THE APT WITH AN UNOBSERVED MARKET FACTOR
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• Part 4: SECURITY ANALYSIS AND PORTFOLIO THEORY
• 17: Efficient Markets
• EARLY DEVELOPMENT
• THE NEXT STAGES OF THEORY
• RECENT THEORY5
• SOME BACKGROUND
• TESTING THE EMH6
• TESTS OF RETURN PREDICTABILITY
• TESTS ON PRICES AND RETURNS
• Intraday and Day-of-the-Week Patterns
• Table 17.1: January Effect: 1926–2012
• MONTHLY PATTERNS
• Predicting Return from Past Return
• Short-term Predictability
• Correlation Tests
• Table 17.2: Daily Correlation Coefficients (from Fama, 1970)
• Correlation for Portfolios of Securities
• Correlation over Long-Run Horizons
• Runs Tests
• Table 17.3: Total Actual and Expected Numbers of Runs for 1-, 4-, 9-, and 16-Day Differencing Intervals (from Fama, 1965)
• Filter Rules
• Figure 17.1: Security price and time.
• Returns and Firm Characteristics
• The “Size Effect”
• Market to Book
• Earnings Price
• Predicting Long-Run Returns from Firm and Market Characteristics
• ANNOUNCEMENT AND PRICE RETURN
• METHODOLOGY OF EVENT STUDIES
• Figure 17.2: Excess return around announcement day.
• Figure 17.3: Cumulative excess return around split rate.
• Results of Some Event Studies
• Figure 17.4: Cumulative excess return around announcement date.
• Figure 17.5: Excess return around publication date.
• STRONG-FORM EFFICIENCY
• Insider Trading
• Information in Analysts’ Forecasts
• Mutual Fund Performance
• MARKET RATIONALITY
• Volatility Tests
• Winners—Losers
• Market Crash of 1987 and 2008
• CONCLUSION
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• 18: The Valuation Process
• DISCOUNTED CASH FLOW MODELS
• Constant Growth Model
• The Two-Period Growth Model
• Table 18.1: Price and Dividend Behavior under a Two-Period Growth Model
• The Three-Period Model
• Figure 18.1: Growth rate pattern for a three-period model.
• Finite Horizon Models
• CROSS-SECTIONAL REGRESSION ANALYSIS
• Figure 18.2: P/E ratios versus growth rates.
• Market Tastes
• Input Data
• Firm Effects
• AN ONGOING SYSTEM
• Table 18.2: Forecasts for Company 1
• Table 18.3: Determining Mispriced Assets
• An Evolving System of Security Selection
• Forecasting Ability
• Portfolios Customized for User Characteristics
• CONCLUSION
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• 19: Earnings Estimation
• THE ELUSIVE NUMBER CALLED EARNINGS
• Table 19.1: Accounting Magic Using Generally Accepted Accounting Principles
• THE IMPORTANCE OF EARNINGS
• Table 19.2: Excess Returns by Eliminating from Portfolio Those Firms That Had Earnings Estimates the Most Above (or Least Below) Realizations
• CHARACTERISTICS OF EARNINGS AND EARNINGS FORECASTS
• The Influence of the Economy and Industry
• Table 19.3: Proportion of Earnings Movement Attributable to Economy or Industry Influences
• Past Earnings and Future Earnings
• Table 19.4: Persistence of Growth
• Table 19.5: Possible Levels of Earnings
• Table 19.6: Possible Changes in Earnings
• Forecasting Earnings with Additional Types of Historical Data
• Analysts Forecasts
• CONCLUSION
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• 20: Behavioral Finance, Investor Decision Making, and Asset Prices
• PROSPECT THEORY AND DECISION MAKING UNDER UNCERTAINTY
• An Experiment
• Figure 20.1: Prospect Theory utility function concave in gains and convex in losses.
• The Disposition Effect
• BIASES FROM LABORATORY EXPERIMENTS
• Heuristics
• Other Biases
• Cognitive Dissonance
• Mental Accounting
• Mood and Emotion
• Local Bias
• The Path of Least Resistance
• Diversification Heuristic
• SUMMARY OF INVESTOR BEHAVIOR
• BEHAVIORAL FINANCE AND ASSET PRICING THEORY
• Opportunity
• Financing
• Asset Prices and Demand Curves
• Figure 20.2: Supply and demand curve for stocks.
• The Marginal Investor
• Stock Prices and Social Dynamics
• Figure 20.3: Time series of one year confidence intervals. Source: International Center for Finance (http://icf.som.yale.edu/stock-market-confidence-indices-united-states-yearindex).
• Media and Behavior and Contrarian Investors
• Explaining Anomalies
• BIBLIOGRAPHY
• 21: Interest Rate Theory and the Pricing of Bonds
• Table 21.1: Rates of Return on Selected Bond Portfolios
• AN INTRODUCTION TO DEBT SECURITIES
• Government Bonds
• Corporate Bonds
• Mortgage Bonds
• Municipal Bonds
• THE MANY DEFINITIONS OF RATES
• Table 21.2: Illustrating the Nonadditivity of Yields
• Figure 21.1: Graph of yield versus price.
• Table 21.3: Cash Flow with Pure Discount Bonds
• BOND PRICES AND SPOT RATES
• Table 21.4: Determination of Forward Rates
• Table 21.5: Cash Flows Associated with Three Different Bonds
• DETERMINING SPOT RATES
• THE DETERMINANTS OF BOND PRICES
• Term to Maturity and Term Structure Theory
• Segmented Market Theory
• Figure 21.2: Possible term structure.
• Figure 21.3: Possible term structure.
• Pure Expectations Theory
• Table 21.6: Two Hypothesized Sequences of Expected One-Period Rates
• Liquidity Premium Theory
• Table 21.7: Yield Curve with a Liquidity Premium (Expressed in Percentage)
• Figure 21.4: Yield curves with liquidity premiums.
• Preferred Habitat
• Term Structure and Coupon Bonds
• Figure 21.5: Possible term structure curves.
• Figure 21.6: Possible term structure curves.
• Summary of the Term Structure of Interest Rates
• Default Risk
• Table 21.8: Components of Interest Rates on Corporate Bonds
• Table 21.9: Key to Moody’s Corporate Ratings
• Tax Effects
• Table 21.10: Historical Default Rates—Straight Bonds Only, 1985–2011 (Dollars in Millions)
• Table 21.11: Mortality Rates by Original Rating—All Rated Corporate Bonds* (1971–2011)
• Option Features of Bonds
• Corporate Bonds
• Corporate Bond Spreads
• Table 21.12: Corporate Bond Spreads for Industrial Bonds and Various Ratings, 1987–1996
• Figure 21.7: Spot rates for A-rated industrial bonds and for Treasuries.
• Floating Rate Bonds
• COLLATERAL MORTGAGE OBLIGATIONS
• THE FINANCIAL CRISIS OF 2008
• Subprime Loans
• Transmittal to the Banks
• Credit Default Swaps
• CONCLUSION
• APPENDIX A: SPECIAL CONSIDERATIONS IN BOND PRICING
• APPENDIX B: ESTIMATING SPOT RATES
• Figure 21.8: Discrete versus continuous discount functions.
• APPENDIX C: CALCULATING BOND EQUIVALENT YIELD AND EFFECTIVE ANNUAL YIELD
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• 22: The Management of Bond Portfolios
• DURATION
• Price Change due to Passage of Time
• Unanticipated Price Change
• Sensitivity to Shifts in the Yield Curve
• Table 22.1: The Effect of a Change in Interest Rates on the Price of a Pure Discount Bond
• Table 22.2: Duration of Bonds with Different Maturities and Couponsa
• Convexity
• Figure 22.1: Actual price change and estimated price change.
• Figure 22.2: The relationship between yield and price for a callable bond.
• PROTECTING AGAINST TERM STRUCTURE SHIFTS
• Exact Matching or Dedication
• Table 22.3: Cash Flow Matched Portfolios
• Immunization
• Table 22.4: The Value of a Bond with Changing Interest Rates
• BOND PORTFOLIO MANAGEMENT OF YEARLY RETURNS
• Indexation
• Active Bond Management
• Aggregate Interest Rate Forecasting
• Sector Selection
• Sector Rotation
• Mispriced Bonds
• Active Bond Selection Using Modern Portfolio Theory
• Estimating Expected Return
• Table 22.5: Hypothetical Set of Rates
• Table 22.6: Assumed Forward Rates (in Percentages)
• Index Models
• Single-Index Models
• Multi-index Models
• SWAPS
• Bond Swaps
• Substitution Swap
• Yield Pickup Swaps
• Tax Swaps
• Interest Rate Swaps
• Table 22.7: Cash Flows of a Fixed-for-Floating Swap Assuming a $10 Million Notational Principal
• APPENDIX A: DURATION MEASURES
• 1. Macaulay’s Second Measure
• 2. Nonproportional Shift in Spot Rates
• 3. Numerical Estimation of Duration
• Table 22.8: Assumed Term Structures
• 4. Duration Measures with Semiannual or Monthly Cash Flows
• APPENDIX B: EXACT MATCHING PROGRAMS
• APPENDIX C: BOND-SWAPPING TECHNIQUES
• APPENDIX D: CONVEXITY
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• 23: Option Pricing Theory
• TYPES OF OPTIONS
• Calls
• Figure 23.1: Profit from call.
• Puts
• Figure 23.2: Profit from put.
• Warrants
• Combinations
• Figure 23.3: Profit from straddle.
• Figure 23.4: The value of a combination of common stock and a call.
• Figure 23.5: Profit from put and stock.
• SOME BASIC CHARACTERISTICS OF OPTION VALUES 5
• Relative Prices of Calls with Alternative Characteristics
• Minimum Value of a European Call
• Table 23.1: Payoffs from Alternative Holdings
• Early Exercise of an American Call
• Put Call Parity
• Table 23.2: Payoffs of Portfolios Involving Puts
• VALUATION MODELS
• Binomial Option Pricing Formula
• Table 23.3: Cash Flows on a Zero-Payoff Portfolio
• Table 23.4: Cash Flows on a Zero-Payoff Portfolio
• Table 23.5: Cash Flows on a Zero-Payoff Portfolio
• Table 23.6: Cash Flows from a Portfolio of Calls and Stock
• Table 23.7: Cash Flows on a Zero-Payoff Portfolio of Stock and Calls
• Figure 23.6: The movement of stock prices through time.
• The Black–Scholes Option Valuation Formula
• Using the Black–Scholes Model
• Implicit Estimates of Stock’s Own Variance from Option Formulas
• ARTIFICIAL OR HOMEMADE OPTIONS
• Table 23.8: Illustration of Homemade Put
• USES OF OPTIONS
• Modifying the Return Pattern
• Figure 23.7: The efficient frontier.
• Figure 23.8: Distribution of returns with various amounts in the risky portfolio.
• Figure 23.9: The effect of puts on the return distribution.
• Betting on Information
• Advanced Uses
• CONCLUSION
• APPENDIX A: DERIVATION OF THE BINOMIAL FORMULA
• Figure 23.10: Stock price paths.
• APPENDIX B: DERIVATION OF THE BLACK–SCHOLES FORMULA
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• 24: The Valuation and Uses of Financial Futures
• DESCRIPTION OF FINANCIAL FUTURES
• Table 24.1: Some Underlying Instruments with Financial Futures
• Profits and Losses from Futures Contracts
• Table 24.2: Cash Flows on a Forward and Futures Contract
• Some Important Attributes of Futures Contracts
• Margin
• Limits
• Delivery
• VALUATION OF FINANCIAL FUTURES
• Treasury Bill Futures
• Table 24.3: Cash Flows on T-bill and Homemade T-bill Contract
• Buy the Cheapest Instrument
• Swap
• Pure Arbitrage
• Treasury Bond Futures
• Stock Index Futures
• Foreign Currency Futures
• THE USES OF FINANCIAL FUTURES
• Hedging
• Changing Investment Policy
• Changing the Market Exposure of a Stock Portfolio
• Changing Interest Rate Exposure on Bonds
• Changing the Bond–Stock Mix
• Creating New Products
• NONFINANCIAL FUTURES AND COMMODITY FUNDS
• Table 24.4: Returns and Risk of Different Investments, 1980–88
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• Part 5: EVALUATING THE INVESTMENT PROCESS
• 25: Mutual Funds
• Table 25.1: Total Net Assets by Type
• OPEN-END MUTUAL FUNDS
• Table 25.2: Number of Mutual Funds by Type
• Table 25.3: Expense Ratio in Annual Percentagea
• Table 25.4: Total Net Assets of Mutual Funds (in Billions)
• CLOSED-END MUTUAL FUNDS
• Explaining the Discount
• Why Closed-End Funds Exist
• EXCHANGE-TRADED FUNDS (ETFS)
• Tracking error
• The Relationships of Price to NAV
• Performance Relative to Other Instruments
• Their Use of Price Formation
• The Effect of Leverage
• Active ETFs
• CONCLUSION
• BIBLIOGRAPHY
• 26: Evaluation of Portfolio Performance
• EVALUATION TECHNIQUES
• Measures of Return
• Table 26.1: Hypothetical Inflows and Outflows
• Table 26.2: Cash Flows and Returns for Two Funds
• Measures of Risk
• Table 26.3: Comparison of Investment Performance of Mutual Funds and Random Portfolios (Jan. 1960–June 1968)
• Direct Comparisons
• Table 26.4a: Return
• Table 26.4b: Risk (Standard Deviation)
• One-Parameter Performance Measures
• The Excess Return to Variability Measure
• Figure 26.1: Combinations of a riskless asset and a risky portfolio.
• Figure 26.2: Combinations of a riskless asset and some mutual funds.
• Figure 26.3: Funds in expected return standard deviation space.
• Figure 26.4: Treynor measure.
• The Treynor Measure: Excess Return to Nondiversifiable Risk
• The Jensen Measure: Differential Return When Risk Is Measured by Beta
• Table 26.5: Performance Summary—All Funds with Complete Data for 1960–1969 Period
• A MANIPULATION-PROOF PERFORMANCE MEASURE
• TIMING
• Figure 26.5: Beta and security returns.
• Figure 26.6: Measuring timing.
• Figure 26.7: Returns for manager without timing.
• Figure 26.8: Returns for manager with timing.
• HOLDING MEASURES OF TIMING
• MULTI-INDEX MODELS AND PERFORMANCE MEASUREMENT
• Multi-index Benchmarks Estimated Using Returns Data
• Indexes based on the major types of securities held by a fund.
• Indexes based on influences that explain security characteristics.7
• Indexes extracted from historical returns.
• Performance Measurement Using Multi-index Models
• Using portfolio composition to estimate portfolio betas.
• USING HOLDINGS DATA TO MEASURE PERFORMANCE DIRECTLY
• TIME-VARYING BETAS
• CONDITIONAL MODELS OF PERFORMANCE MEASUREMENT, BAYESIAN ANALYSIS, AND STOCHASTIC DISCOUNT FACTORS
• BAYESIAN ANALYSIS12
• STOCHASTIC DISCOUNT FACTORS
• WHAT’S A RESEARCHER TO DO?
• MEASURING THE PERFORMANCE OF ACTIVE BOND FUNDS
• THE PERFORMANCE OF ACTIVELY MANAGED MUTUAL FUNDS
• HOW HAVE MUTUAL FUNDS DONE?
• Table 26.6: Mutual Fund Performance Results (Annualized)
• THE PERSISTENCE OF PERFORMANCE
• PERSISTENCE
• Table 26.7: Persistence
• Table 26.8: Realized Alphas with Forecast in Previous Year (Work Data)
• Performance in the Hedge and Commodity Fund Industries
• Special Issues with Hedge Funds
• Transparency
• APPENDIX: The Use of APT Models to Evaluate and Diagnose Performance
• Table 26A-1: Effect of Different Sensitivities on Performance
• Table 26A-2: Decomposition of Performance Using APT
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• 27: Evaluation of Security Analysis
• WHY THE EMPHASIS ON EARNINGS?
• THE EVALUATION OF EARNINGS FORECASTS
• Overall Forecast Accuracy
• Table 27.1: TIC over Time
• Diagnosis of Forecasting Errors
• Graphical Analysis
• Figure 27.1: Prediction Realization Diagram.
• Figure 27.2: Prediction Realization Diagram: Optimistic forecaster.
• Figure 27.3: Prediction Realization Diagram: The overreactor.
• Numerical Analysis
• Error Decomposed by Level of Aggregation
• Errors Decomposed by Forecast Characteristics
• Table 27.2: Percentage Error in Earnings Change by Level of Aggregation
• The Evaluation of Earnings Forecasts—Again
• EVALUATING THE VALUATION PROCESS
• Evaluating the Valuation Process with a Full Set of Outputs
• Evaluating the Output of the Valuation Process: Incomplete Information
• Figure 27.4: Examination of buy-hold-sell recommendations.
• CONCLUSION
• QUESTIONS AND PROBLEMS
• BIBLIOGRAPHY
• 28: Portfolio Management Revisited
• Figure 28.1: Modern version of traditional approach.
• MANAGING STOCK PORTFOLIOS
• Passive Management
• ACTIVE MANAGEMENT
• PASSIVE VERSUS ACTIVE
• INTERNATIONAL DIVERSIFICATION
• BOND MANAGEMENT
• Passive Strategies
• Active Strategies
• BOND AND STOCK INVESTMENT WITH A LIABILITY STREAM
• Fixed Liability Stream
• Stochastic Liability Stream
• Bond–Stock Mix
• BIBLIOGRAPHY
• Back Matter
• Index