A Behavioral Approach to Asset Pricing
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Table of contents
- Contentsv
- 1 Introduction1
- 1.1 Why Read This Book?2
- 1.2 Organization: How the Ideas in This Book Tie Together6
- 1.3 Summary12
- Part I - Heuristics and Representativeness: Experimental Evidence13
- 2 Representativeness and Bayes Rule: Psychological Perspective15
- 2.1 Explaining Representativeness16
- 2.2 Implications for Bayes Rule16
- 2.3 Experiment16
- 2.4 Representativeness and Prediction19
- 2.5 Summary23
- 3 Representativeness and Bayes Rule: Economics Perspective25
- 3.1 The Grether Experiment25
- 3.2 Representativeness28
- 3.3 Results28
- 3.4 Summary32
- 4 A Simple Asset Pricing Model Featuring Representativeness33
- 4.1 First Stage, Modified Experimental Structure34
- 4.2 Expected Utility Model34
- 4.3 Equilibrium Prices37
- 4.4 Representativeness38
- 4.5 Second Stage: Signal-Based Market Structure39
- 4.6 Summary41
- 5 Heterogeneous Judgments in Experiments43
- 5.1 Grether Experiment43
- 5.2 Heterogeneity in Predictions of GPA44
- 5.3 The De Bondt Experiment46
- 5.4 Why Some Bet on Trends and Others Commit Gambler’s Fallacy55
- 5.5 Summary57
- Part II - Heuristics and Representativeness: Investor Expectations59
- 6 Representativeness and Heterogeneous Beliefs Among Individual Investors, Financial Executives, and61
- 6.1 Individual Investors61
- 6.2 The Expectations of Academic Economists69
- 6.3 Financial Executives73
- 6.4 Summary74
- 7 Representativeness and Heterogeneity in the Judgments of Professional Investors75
- 7.1 Contrasting Predictions: How Valid?75
- 7.2 Update to Livingston Survey76
- 7.3 Individual Forecasting Records80
- 7.4 Gambler’s Fallacy88
- 7.5 Why Heterogeneity Is Time Varying93
- 7.6 Summary94
- Part III - Developing Behavioral Asset Pricing Models97
- 8 A Simple Asset Pricing Model with Heterogeneous Beliefs99
- 8.1 A Simple Model with Two Investors99
- 8.2 Equilibrium Prices102
- 8.3 Fixed Optimism and Pessimism104
- 8.4 Incorporating Representativeness107
- 8.5 Summary109
- 9 Heterogeneous Beliefs and Inefficient Markets111
- 9.1 Defining Market Efficiency111
- 9.2 Market Efficiency and Logarithmic Utility115
- 9.3 Equilibrium Prices as Aggregators116
- 9.4 Market Efficiency: Necessary and Sufficient Condition117
- 9.5 Interpreting the Efficiency Condition119
- 9.6 Summary122
- 10 A Simple Market Model of Prices and Trading Volume123
- 10.1 The Model123
- 10.2 Analysis of Returns126
- 10.3 Analysis of Trading Volume127
- 10.4 Example131
- 10.5 Arbitrage139
- 10.6 Summary140
- 11 Efficiency and Entropy: Long-Run Dynamics141
- 11.1 Introductory Example142
- 11.2 Entropy147
- 11.3 Numerical Illustration148
- 11.4 Markov Beliefs149
- 11.5 Heterogeneous Time Preference, Entropy, and Efficiency150
- 11.6 Entropy and Market Efficiency154
- 11.7 Summary157
- Part IV - Heterogeneity in Risk Tolerance and Time Discounting159
- 12 CRRA and CARA Utility Functions161
- 12.1 Arrow–Pratt Measure161
- 12.2 Proportional Risk162
- 12.3 Constant Relative Risk Aversion162
- 12.4 Logarithmic Utility164
- 12.5 CRRA Demand Function165
- 12.6 Representative Investor166
- 12.7 Example167
- 12.8 CARA Utility170
- 12.9 Summary174
- 13 Heterogeneous Risk Tolerance and Time Preference175
- 13.1 Survey Evidence175
- 13.2 Extended Survey179
- 13.3 Time Preference182
- 13.4 Summary183
- 14 Representative Investors in a Heterogeneous CRRA Model185
- 14.1 Relationship to Representative Investor Literature186
- 14.2 Modeling Preliminaries189
- 14.3 Efficient Prices190
- 14.4 Representative Investor Characterization Theorem191
- 14.5 Comparison Example195
- 14.6 Pitfall: The Representative Investor Theorem Is False198
- 14.7 Summary200
- Part V - Sentiment and Behavioral SDF201
- 15 Sentiment203
- 15.1 Intuition: Kahneman’s Perspective203
- 15.2 Sentiment206
- 15.3 Example Featuring Heterogeneous Risk Tolerance207
- 15.4 Example Featuring Log-Utility209
- 15.5 Sentiment as a Stochastic Process218
- 15.6 Summary219
- 16 Behavioral SDF and the Sentiment Premium221
- 16.1 The SDF222
- 16.2 Sentiment and the SDF223
- 16.3 Pitfalls226
- 16.4 Sentiment and Expected Returns230
- 16.5 Entropy and Long-Run Efficiency234
- 16.6 Learning: Bayesian and Non-Bayesian236
- 16.7 Summary237
- Part VI - Applications of Behavioral SDF239
- 17 Behavioral Betas and Mean-Variance Portfolios241
- 17.1 Mean-Variance Efficiency and Market Efficiency241
- 17.2 Characterizing Mean-variance Efficient Portfolios242
- 17.3 The Shape of Mean-Variance Returns244
- 17.4 The Market Portfolio247
- 17.5 Behavioral Beta: Decomposition Result249
- 17.6 Summary253
- 18 Cross-section of Return Expectations255
- 18.1 Literature Review256
- 18.2 Factor Models and Risk261
- 18.3 Differentiating Fundamental Risk and Investor Error262
- 18.4 Implications for the Broad Debate267
- 18.5 Analysts’ Return Expectations268
- 18.6 How Consciously Aware Are Investors When Forming Judgments?269
- 18.7 How Reliable Is the Evidence on Expected Returns?270
- 18.8 Alternative Theories272
- 18.9 Summary277
- 19 Testing for a Sentiment Premium279
- 19.1 Diether–Malloy–Scherbina: Returns Are Negatively Related to Dispersion280
- 19.2 Ghysels–Juergens: Dispersion Factor282
- 19.3 Estimating a Structural SDF-Based Model286
- 19.4 Summary288
- 20 A Behavioral Approach to the Term Structure of Interest Rates289
- 20.1 The Term Structure of Interest Rates289
- 20.2 Pitfall: The Bond Pricing Equation in Theorem 20.1 Is False290
- 20.3 Volatility292
- 20.4 Expectations Hypothesis296
- 20.5 Summary299
- 21 Behavioral Black–Scholes301
- 21.1 Call and Put Options301
- 21.2 Risk-Neutral Densities and Option Pricing302
- 21.3 Option Pricing Examples305
- 21.4 Smile Patterns311
- 21.5 Heterogeneous Risk Tolerance316
- 21.6 Pitfall: Equation (21.12) Is False317
- 21.7 Pitfall: Beliefs Do Not Matter in Black – Scholes318
- 21.8 Summary319
- 22 Irrational Exuberance and Option Smiles321
- 22.1 Irrational Exuberance: Brief History322
- 22.2 Risk-Neutral Densities and Index Option Prices326
- 22.3 Continuation, Reversal, and Option Prices330
- 22.4 Price Pressure: Was Arbitrage Fully Carried Out?335
- 22.5 Heterogeneous Beliefs337
- 22.6 Summary337
- 23 Empirical Evidence in Support of Behavioral SDF339
- 23.1 Bollen–Whaley: Price Pressure Drives Smiles340
- 23.2 Han: Smile Effects, Sentiment, and Gambler’s Fallacy344
- 23.3 David–Veronesi: Gambler’s Fallacy and Negative Skewness346
- 23.4 Jackwerth: Estimating Market Risk Aversion348
- 23.5 Rosenberg–Engle: Signature of Sentiment in the SDF350
- 23.6 Comparing the Behavioral SDF and Empirical SDF352
- 23.7 Heterogeneous Perspectives359
- 23.8 Summary362
- Part VII - Prospect Theory363
- 24 Prospect Theory: Introduction365
- 24.1 Experimental Evidence366
- 24.2 Theory374
- 24.3 Subtle Aspects Associated with Risk Aversion379
- 24.4 Generalized Utility Theories381
- 24.5 Summary382
- 25 Behavioral Portfolios383
- 25.1 Theory384
- 25.2 Prospect Theory: Indi.erence Map385
- 25.3 Portfolio Choice: Single Mental Account386
- 25.4 Multiple Mental Accounts: Example389
- 25.5 SP/A Theory392
- 25.6 Real World Portfolios and Securities398
- 25.7 Summary400
- 26 Prospect Theory Equilibrium401
- 26.1 The Model402
- 26.2 Simple Example403
- 26.3 On the Boundary407
- 26.4 Equilibrium Pricing408
- 26.5 Portfolio Insurance410
- 26.6 Risk and Return: Portfolio Insurance in a Mean-Variance Example413
- 26.7 Summary417
- 27 Pricing and Prospect Theory: Empirical Studies419
- 27.1 Combining Behavioral Preferences and Beliefs419
- 27.2 Disposition Effect: The Empirical Evidence420
- 27.3 Investor Beliefs422
- 27.4 Momentum and the Disposition Effect426
- 27.5 Summary428
- 28 Reflections on the Equity Premium Puzzle429
- 28.1 Basis for Puzzles in Traditional Framework429
- 28.2 Erroneous Beliefs433
- 28.3 Alternative Rationality-Based Models437
- 28.4 Behavioral Preferences and the Equity Premium440
- 28.5 Risks, Small and Large444
- 28.6 Summary445
- Part VIII - Closure447
- 29 Conclusion449
- 29.1 Recapitulating the Main Points449
- 29.2 Testable Predictions452
- 29.3 Future Directions453
- References457
- Index473
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.
The book develops a series of examples to illustrate the theoretical results. The CD-ROM contains most of the examples, worked out as Excel spreadsheets, so that a diligent reader can follow them through.
Instructors might also want to use the examples to assign class exercises, asking students to modify the numbers and see what happens.
* The first book to focus completely on how behavioral finance principles affect asset pricing
* Hersh Shefrin is a recognized expert in behavioral finance
* Behavioral finance is a growth area in finance scholarship and moving more and more into practice
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.
The book develops a series of examples to illustrate the theoretical results. The CD-ROM contains most of the examples, worked out as Excel spreadsheets, so that a diligent reader can follow them through.
Instructors might also want to use the examples to assign class exercises, asking students to modify the numbers and see what happens.
* The first book to focus completely on how behavioral finance principles affect asset pricing
* Hersh Shefrin is a recognized expert in behavioral finance
* Behavioral finance is a growth area in finance scholarship and moving more and more into practice