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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

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