《一般均衡期权定价方法(理论与实证研究)》主要介绍基于扇形偏好的一般均衡定价方法，阐述扇形偏好对期权定价的主要影响。与传统的预期效用理论相区别，扇形偏好认为人们对于极端事件（如金融危机导致的股票暴跌）的风险厌恶程度要大于普通的市场波动风险。从而该理论可以更加准确地描述市场中投资者的行为，并且成功解释期权市场的“波动率微笑”现象。
陈坚，毕业于英国埃塞克斯大学商学院，获得金融学博士学位。毕业后曾在北京大公国际资信评估有限公司工作，担任金融分析师，主要从事债券评级与结构融资产品风险分析，曾负责不良资产回收率建模等项目。2009年9月加入厦门大学经济学院金融系，任助理教授，主要研究领域包括：资产定价的理论与实证分析、金融衍生产品定价、信用风险研究等。目前，作者已在国内外顶级学术期刊发表论文若干篇，主持国家级和省部级课题各一项，参与国家级和省部级科研项目若干项。并且，曾多次在国内外学术研讨会上报告论文。2012年，其论文获得第十届系统工程与风险管理国际年会的最佳论文奖。
Introduction
1.1 Motivation for the Book
1.2 Overview and Structure for the Book
2 General Equilibrium Option Pricing Models
2.1 The Economy and Utility Functions
2.2 Market Risk Premium
2.3 Option Pricing Model
3 Simulation Comparison
3.1 Introduction
3.2 Methodology
3.3 Simulations
3.3.1 Risk-neutral and Physical Jumps
3.3.2 Recursive and Expected Utility Functions .
3.3.3 Lognormal and Uniform Jump Size Distribu
tions Introduction
1.1 Motivation for the Book
1.2 Overview and Structure for the Book
2 General Equilibrium Option Pricing Models
2.1 The Economy and Utility Functions
2.2 Market Risk Premium
2.3 Option Pricing Model
3 Simulation Comparison
3.1 Introduction
3.2 Methodology
3.3 Simulations
3.3.1 Risk-neutral and Physical Jumps
3.3.2 Recursive and Expected Utility Functions .
3.3.3 Lognormal and Uniform Jump Size Distribu
tions
3.4 Conclusions
4 Empirical Comparison
4.1 Introduction
4.2 Option Pricing Models
4.3 Data and Methodology
4.4 Empirical Results
4.4.1 Parameter Estimates and In-sample Fit
4.4.2 Out-of-sample Performance
4.4.3 Jump Risk Premium
4.5 Conclusions
5 Fanning Out Preference and Option Pricing
5.1 Introduction
5.2 Mcdel Setup
5.3 Numerical Studies
5.4 Empirical Analysis
5.4.1 Data and Methodology
5.4.2 Estimation
5.4.3 Implied Risk Premiums
5.4.4 Model Fit and Volatility Smirks
5.5 Concluding Remarks
6 Jump Size Distributions and Option Pricing
6.1 Introduction
6.2 Model Setup
6.3 Empirical Investigation
6.3.1 Data and Methodology
6.3.2 Empirical Results
6.4 Concluding Remarks
7 Risk Aversion Estimated from Volatility Spread
7.1 Introduction
7.2 Methodology
7.2.1 Realized Volatility
7.2.2 Model-free Implied Volatility
7.2.3 Volatility Spread
7.3 Data and Empirical Results
7.3.1 Risk Aversion Estimate
7.4 Conclusions
8 Predictability of VRP: Hongkong Evidence
8.1 Introduction
8.2 Model
8.2.1 Realized Volatility
8.2.2 Model-free Implied Volatility
8.2.3 Variance Risk Premium
8.2.4 Predictability of Stock Return
8.3 Data and Empirical Results
8.3.1 Data
8.3.2 Summary Statistics of Volatility Measures
8.3.3 Variance Risk Premium
8.3.4 Predictability of Stock Return
8.3.5 Evidences during the Financial Crisis Period
8.4 Conclusions
9 Predictability of VRP: Other International Evidence
9.1 Introduction
9.2 Empirical Methodology
9.2.1 Variance Risk Premium
9.2.2 In-sample Predictability Regression
9.3 Data and Summary Statistics
9.4 In-sample Predictability Results
9.5 Concluding Remarks
10 Predictability of VRP: A Comparison Study
10.1 Introduction
10.2 Methodology
10.2.1 Construction of Variance Risk Premium
10.2.2 Stock Return Predictability Regression
10.3 Data and Empirical Results
10.3.1 Data and Summary Statistics
10.3.2 Empirical Results from International Markets
10.4 Concluding Remarks
11 Conclusions
ll.1 Summary
11.2 Future Research
Appendix
A. Non-expected Recursive Utility
B. Jump Risk Premium
C. Variance Risk Premium
D. Covariance Risk Premium
E. Observational Non-equivalence
E Risk-neutral MGF
G. Jump Size Distribution
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