## A Behavioral Approach to Asset PricingA 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 |

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### Contents

1 | |

13 | |

Investor Expectations | 59 |

Part III Developing Behavioral Asset Pricing Models | 97 |

Part IV Heterogeneity in Risk Tolerance and Time Discounting | 159 |

Part V Sentiment and Behavioral SDF | 201 |

Part VI Applications of Behavioral SDF | 239 |

Part VII Prospect Theory | 363 |

Part VIII Closure | 447 |

457 | |

473 | |

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analysts arbitrage asset pricing theorists associated behavioral asset pricing behavioral finance beta Black–Scholes Bondt call option Chapter choice coefficient of relative Consider consumption growth convex combination date–event pair discussed Dow Jones Industrial down-move equation equity premium equity premium puzzle example expected returns expected utility Figure forecasts gains gambler’s fallacy heterogeneous beliefs implied volatility index options indifference curves individual investors initial wealth interest rate investor errors Jones Industrial Average log-utility loss market efficiency market portfolio mean mean-variance efficient mental account negative option prices overconfidence percent predictions probability density functions professional investors prospect theory prospect theory investors put options ratio regime process relative risk aversion representative investor return expectations risk aversion risk neutral risk premium risk-free security risk-neutral risky security sentiment function standard deviation stochastic survey Theorem traditional asset pricing trend followers up-move utility function variable Wall treet Week weight zero

### Popular passages

Page 17 - Tom W. is of high intelligence, although lacking in true creativity. He has a need for order and clarity, and for neat and tidy systems in which every detail finds its appropriate place. His writing is rather dull and mechanical, occasionally enlivened by somewhat corny puns and by flashes of imagination of the sci-fi type. He has a strong drive for competence. He seems to have little feel and little sympathy for other people and does not enjoy interacting with others. Self-centered, he nonetheless...

Page 16 - A person who follows this heuristic evaluates the probability of an uncertain event, or a sample, by the degree to which it is: (i) similar in essential properties to its parent population; and (ii) reflects the salient features of the process by which it is generated.

Page 17 - The preceding personality sketch of Tom W. was written during Tom's senior year in high school by a psychologist on the basis of personality tests. Tom W. is currently a graduate student. Please rank the following nine fields of graduate specialization in order of the likelihood that Tom W. is now a graduate student in each of these fields. Write "1" next to the most probable choice, etc.

Page 457 - An empirical investigation of continuous-time equity return models". Journal of Finance 57, 1239-1284. Andersen, TG, Bollerslev, T. (1998a). "Answering the skeptics: Yes, standard volatility models do provide accurate forecasts".