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- Product code: 20491
- ISBN: 0126393710,
ISBN13: 9780126393712,
350 pages, hardback
Published by Academic Press on 2005
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Description of A Behavioral Approach to Asset Pricing |
A Behavioral Approach to Asset Pricing Theory examines the reigning assumptions of asset pricing theory and reconstructs them to incorporate findings from behavioral finance. It constructs a solid, intact structure that challenges classic assumptions and at the same time provides a strong theory and efficient empirical tools.
Building on the models developed by both traditional asset pricing theorists and behavioral asset pricing theorists, this book takes the discussion to the next step. The author provides a general behaviorally based intertemporal treatment of asset pricing theory that extends to the discussion of derivatives, fixed income securities, mean-variance efficient portfolios, and the market portfolio.
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Reviews"I highly recommend Shefrin's book to anyone who wants to probe into the implications of behavioral finance for asset pricing. Shefrin builds rigorous theoretical models that integrate investor heterogeneity and psychological biases into the traditional stochastic discount factor framework. The text contains a wealth of original ideas, and provides new modeling tools. The results are convincing and thought provoking. I believe Shefrin's book will help revolutionize our thinking about asset pricing and stimulate more work along its line."
- Bing Han, Assistant Professor of Finance, the Ohio State University
| Contents of A Behavioral Approach to Asset Pricing |
1. Introduction
1.1 Why Read This Book?
1.1.1 Value to Proponents of Traditional Asset Pricing
1.1.2 Value to Proponents of Behavioral Asset Pricing
1.2 Organization: How the Ideas in this Book Tie Together
1.2.1 Heuristics and Representativeness
1.2.2 Developing Behavioral Asset Pricing Models
1.2.3 Heterogeneity in Risk Tolerance and Time Discounting
1.2.4 Sentiment and Behavioral SDF
1.2.5 Applications of Behavioral SDF
1.2.6 Prospect Theory
1.2.7 Closure
2. Representativeness and Bayes Rule: Psychological Perspective
2.1 Explaining Representativeness
2.2 Implications for Bayes Rule
2.3 Experiment
2.3.1 Three Groups
2.3.2 Bayesian Hypothesis
2.3.3 Results
2.4 Representativeness and Prediction
2.4.1 Two Extreme Cases
2.4.2 Representativeness and Regression to the Mean
2.4.3 Results for the Prediction Study
2.4.4 Strength of Relationship Between Signal and Prediction
2.4.5 How Regressive?
2.5 Summary
3. Representativeness and Bayes Rule: Economics Perspective
3.1 The Grether Experiment
3.1.1 Design
3.1.2 Experimental Task: Bayesian Approach
3.2 Representativeness
3.3 Results
3.3.1 Underweighting Base Rate Information
3.4 Summary
4. A Simple Asset Pricing Model Featuring Representativeness
4.1 First Stage, Modified Experimental Structure
4.2 Expected Utility Model
4.2.1 Bayesian Solution
4.3 Equilibrium Prices
4.4 Representativeness
4.5 Second Stage: Signal Based Market Structure
4.6 Summary
5. Heterogeneous Judgments in Experiments
5.1 Grether Experiment
5.2 Heterogeneity in Predictions of GPA
5.3 The De Bondt Experiment
5.3.1 Betting on Trends and Gambler’s Fallacy: Experimental Evidence .
5.3.2 Forecasts of the S&P-Index
5.3.3 Replication of De Bondt Study
5.4 Summary
6. Heterogeneous Beliefs Among Individual Investors and Academics
6.1 Individual Investors
6.1.1 Bullish Sentiment and Heterogeneity
6.1.2 The UBS/Gallup Survey
6.1.3 Trend Following
6.1.4 Heterogeneous Beliefs
6.1.5 The Impact of Demographic Variables
6.1.6 Own Experience: Availability Bias
6.1.7 Do Individual Investors Bet on Trends? Perceptions and Reactions to
Mispricing
6.2 The Expectations of Academic Economists
6.2.1 Heterogeneous Beliefs
6.2.2 Welch’s 1999 and 2001 Surveys
6.3 Summary
7. Heterogeneity in the Judgments of Professional Investors
7.1 Contrasting Predictions: How Valid?
7.2 Update to Livingston Survey
7.2.1 Heterogeneity
7.3 Individual Forecasting Records
7.3.1 Frank Cappiello
7.3.2 Ralph Acampora7.4 Gambler’s Fallacy
7.4.1 Forecast Accuracy
7.4.2 Excessive Pessimism
7.4.3 Predictions of Volatility
7.5 Why Heterogeneity is Time Varying
7.6 Summary
8. A Simple Asset Pricing Model With Heterogeneous Beliefs
8.1 A Simple Model With Two Investors
8.1.1 Probabilities
8.1.2 Utility Functions
8.1.3 State Prices
8.1.4 Budget Constraint
8.1.5 Expected Utility Maximization
8.2 Equilibrium Prices
8.2.1 Formal Argument
8.2.2 Representative Investor
8.3 Fixed Optimism and Pessimism
8.3.1 Impact of Heterogeneity
8.4 Incorporating Representativeness
8.5 Summary
9. Heterogeneous Beliefs and Ine_cient Markets
9.0.1 Riskless Arbitrage
9.0.2 Risky Arbitrage
9.0.3 Fundamental Value
9.1 Market E_ciency and Logarithmic Utility
9.1.1 Example of Market Ine_ciency
9.2 Equilibrium Prices as Aggregators
9.3 Market E_ciency: Necessary and Su_cient Condition
9.4 Interpreting the E_ciency Condition
9.4.1 When the Market is Naturally E_cient
9.4.2 Knife-edge E_ciency
9.4.3 When the Market is Naturally Ine_cient
9.5 Summary
10. A Simple Market Model of Prices and Trading Volume
10.1 The Model
10.1.1 Stochastic Processes
10.1.2 Available Securities
10.1.3 Initial Portfolios
10.1.4 Expected Utility Maximization
10.1.5 Equilibrium Portfolio Strategies
10.2 Arbitrage
10.2.1 State Prices
10.3 Analysis of Returns
10.3.1 Market Portfolio
10.3.2 Risk-free Security
10.4 Analysis of Trading Volume
10.4.1 Theory
10.4.2 Empirical Evidence
10.5 Summary 11 E_ciency and Entropy: Long-run Dynamics
11.1 The Market
11.2 Budget Share Equations
11.3 Portfolio Relationships
11.4 Wealth Share Equations
11.5 Entropy
11.6 Numerical Illustration
11.7 Markov Beliefs
11.8 Heterogeneous Time Preference, Entropy and E_ciency
11.8.1 Modeling Heterogeneous Rates of Time Preference
11.8.2 Market Portfolio
11.8.3 Digression: Hyperbolic Discounting
11.8.4 Long-run Dynamics When Time Preference is Heterogeneous
11.9 Entropy and Market E_ciency
11.10 Summary
12. CRRA and CARA Utility Functions 127
12.1 Arrow-Pratt Measure
12.2 Proportional Risk
12.3 Constant Relative Risk Aversion
12.3.1 Graphical Illustration
12.3.2 Risk Premia
12.4 Logarithmic Utility
12.4.1 Risk Premium in a Discrete Gamble
12.5 CRRA Demand Function
12.6 Representative Investor
12.7 Example
12.8 CARA Utility
12.8.1 CARA Demand Function
12.8.2 Aggregate Demand and Equilibrium
12.9 Summary
13. Heterogeneous Risk Tolerance and Time Preference
13.1 Survey Evidence
13.1.1 Questions to Elicit Relative Risk Aversion
13.1.2 Two Waves
13.1.3 Status Quo Bias
13.1.4 Risky Choice
13.2 Extended Survey
13.3 Time Preference
13.4 Summary
14. Representative Investors in a Heterogeneous CRRA Model
14.1 Relationship to Representative Investor Literature
14.1.1 Additional Literature
14.2 Modeling Preliminaries
14.3 E_cient Prices
14.4 Representative Investor Characterization Theorem
14.4.1 Discussion
14.4.2 Nonuniqueness
14.5 Comparison Example
14.6 Summary
15. Sentiment
15.0.1 Relationship to Theorem 14.1
15.0.2 Defining Market E_ciency
15.1 Sentiment
15.1.1 Formal Definition
15.2 Example Featuring Heterogeneous Risk Tolerance
15.3 Example Featuring Log-utility
15.3.1 Errors in First Moments
15.3.2 Errors in Second Moments
15.3.3 Link to Empirical Evidence
15.4 Sentiment as a Stochastic Process
15.5 Summary
16. Behavioral SDF and the Sentiment Premium
16.1 The SDF
16.2 Sentiment and the SDF
16.2.1 Example
16.3 Sentiment and Expected Returns
16.3.1 Interpretation and Discussion
16.4 Contrasting Heterogeneity in Beliefs With Heterogeneity in Risk Tolerance
16.5 Entropy and Long-run E_ciency
16.5.1 Formal Argument
16.6 Learning: Bayesian and Non-Bayesian
16.7 Summary
17. Behavioral Betas and Mean-Variance Portfolios
17.1 Characterizing Mean-variance E_cient Portfolios
17.2 The Shape of Mean-variance Returns
17.3 The Market Portfolio
17.4 Behavioral Beta: Decomposition Result
17.5 Summary
18. Cross-section of Return Expectations
18.1 Literature Review
18.1.1 Winner-loser E_ect
18.1.2 Book-to-market Equity and the Winner-loser E_ect
18.1.3 January and Momentum
18.1.4 General Momentum Studies
18.1.5 Glamour and Value
18.2 Factor Models and Risk
18.3 Di_erentiating Fundamental Risk and Investor Error
18.3.1 Psychology of Risk and Return
18.3.2 Evidence about Judgments of Risk and Return
18.3.3 Psychology Underlying a Negative Relationship between Risk and Return
18.4 Implications for the Broad Debate
18.5 Analysts’ Return Expectations
18.6 How Consciously Aware are Investors When Forming Judgments?
18.7 How Reliable is the Evidence on Expected Returns?
18.8 Alternative Theories
18.8.1 The Dynamics of Expectations: Supporting Data
18.9 Summary
19. Testing for a Sentiment Premium
19.1 Diether-Malloy-Scherbina: Returns are Negatively Related to Dispersion
19.2 Ghysels-Juergens: Dispersion Factor
19.2.1 Basic Approach
19.2.2 Factor Structure
19.2.3 General Properties of the Data
19.2.4 Expected Returns
19.2.5 Findings
19.2.6 Volatility
19.2.7 Direction of Mispricing
19.2.8 Opposite Signs for Short and Long Horizons
19.3 Estimating a Structural SDF-based Model
19.3.1 Proxy for hZ,t
19.3.2 Findings
19.4 Summary
20. A Behavioral Approach to the Term Structure of Interest Rates
20.1 The Term Structure of Interest Rates
20.2 Volatility
20.2.1 Heterogeneous Risk Tolerance
20.3 Expectations Hypothesis
20.3.1 Example
20.4 Summary
21. Behavioral Black-Scholes
21.1 Risk-neutral Densities and Option Pricing
21.1.1 Option Pricing Equation 1
21.1.2 Option Pricing Equations 2 and 3
21.2 Option Pricing Examples
21.2.1 Discrete Time Example
21.2.2 Continuous Time Example
21.3 Smile Patterns
21.4 Heterogeneous Risk Tolerance
21.5 Summary
22. Option Smiles: Case Study
22.1 Irrational Exuberance: Brief History
22.1.1 Sentiment
22.2 Risk-neutral Densities and Index Option Prices
22.2.1 Butterfly Position Technique
22.3 Continuation, Reversal, and Option Prices
22.4 Price Pressure: Was Arbitrage Fully Carried Out
22.5 Explaining Heterogeneous Beliefs
22.6 Summary
23. Empirical Evidence In Support of Behavioral SDF
23.1 Bollen-Whaley: Price Pressure Drives Smiles
23.1.1 Data
23.1.2 Trading Patterns
23.1.3 Buying Pressure and Smile E_ects
23.1.4 Price Pressure or Learning?
23.2 Arbitrage Profits
23.3 Han: Smile E_ects and Indexes of Sentiment
23.3.1 Price Pressure
23.3.2 Impact of a Market Drop
23.3.3 Impact of Sentiment
23.3.4 Time Varying Uncertainty
23.4 David-Veronesi: Gambler’s Fallacy and Negative Skewness
23.5 Rosenberg-Engle: Signature of Sentiment in the SDF
23.5.1 Two Approaches to Estimating the EPK
23.5.2 Estimating Market Risk Aversion
23.5.3 Empirical Results
23.5.4 A Closer Look at the Behavioral SDF
23.6 Summary
24. Prospect Theory
24.1 Experimental Evidence
24.1.1 Common Ratio E_ect
24.1.2 Subcertainty and Expected Utility
24.1.3 Allais Paradox and the Independence Axiom
24.1.4 Isolation and Common Consequence E_ect
24.1.5 Isolation and the Independence Axiom
24.1.6 Loss Aversion
24.1.7 Ambiguity
24.2 Theory
24.2.1 The Weighting Function
24.2.2 Value Function
24.2.3 Framing
24.3 Subtle Aspects Associated with Risk Aversion
24.4 Words of Caution
24.5 Summary
25. Behavioral Portfolios
25.1 Theory
25.1.1 Prospect Theory: Uncertainty Weights
25.1.2 Utility Function
25.1.3 Prospect Theory Functional
25.2 Prospect Theory: Indi_erence Map
25.3 Portfolio Choice: Single Mental Account
25.3.1 Exposure to Loss: Single Mental Account
25.3.2 Portfolio Payo_ Return: Single Mental Account
25.4 Multiple Mental Accounts: Example
25.4.1 General Comments About Multiple Mental Accounts
25.5 SP/A Theory
25.5.1 SP/A E_cient Frontier
25.5.2 Additional Comments
25.6 Real World Portfolios and Securities
25.7 Summary
26. Prospect Theory Equilibrium
26.1 The Model
26.2 Simple Example
26.2.1 Neoclassical Case
26.2.2 Prospect Theory Investors
26.3 General Propositions
26.4 Equilibrium Pricing in the Case of Expected Utility
26.5 Portfolio Insurance
26.6 Risk and Return: Portfolio Insurance in a Mean-variance Example
26.7 Summary
27. Pricing and Prospect Theory
27.1 Disposition E_ect: The Empirical Evidence
27.2 Investor Beliefs
27.2.1 Odean’s Findings
27.2.2 A Size E_ect
27.2.3 A Volume E_ect
27.3 Momentum and the Disposition E_ect
27.3.1 Theoretical Hypotheses
27.3.2 Empirical Evidence
27.4 Summary
28. Reflections on the Equity Premium Puzzle
28.1 Basis for Puzzles in Traditional Framework
28.1.1 Brief Review
28.1.2 Attaching Numbers to Equations
28.2 Erroneous Beliefs
28.2.1 Livingston Data
28.2.2 The Market and the Economy: Upwardly Biased Covariance Estimate
28.3 Alternative Rationality-Based Models
28.3.1 Habit Formation
28.3.2 Habit Formation SDF
28.3.3 Habit Formation SDF vs the Empirical SDF
28.4 Behavioral Preferences and the Equity Premium
28.4.1 Myopic Loss Aversion
28.4.2 Transaction Utility
28.5 Summary
29. Traditional Criticisms and Logical Flaws
29.1 Contention: The Representative Investor Theorem is False
29.2 Contention: The Behavioral Framework Admits a Traditional SDF
29.3 Contention: The Bond Pricing Equation in Theorem 20.1 is False
29.4 Contention: The Behavioral Approach to Options Pricing is Flawed
29.4.1 Contention: Equation(21.12) is False
29.4.2 Contention: There is Little Value in Studying Heterogeneity in Beliefs .
29.4.3 Contention: Beliefs Do Not Matter in Black-Scholes
29.5 Contention: Is There Any Need to Assume Investor Errors?
29.5.1 Contention: Heterogeneity Need Not Imply Sentiment
29.5.2 Contention: Pricing in Terms of SDF Precludes Mispricing
29.6 Counterarguments
29.6.1 Identifying Flawed Arguments
29.6.2 Explaining Flawed Arguments
29.7 Summary
30. Conclusion
31. References
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