Bayesian Methods in Finance provides a detailed overview of the theory of Bayesian methods and explains their real-world applications to financial modeling. While the principles and concepts explained throughout the book can be used in financial modeling and decision making in general, the authors focus on portfolio management and market risk management—since these are the areas in finance where Bayesian methods have had the greatest penetration to date.
Preface xv
About the Authors xvii
CHAPTER 1 Introduction 1
CHAPTER 2 The Bayesian Paradigm 6
CHAPTER 3 Prior and Posterior Information, Predictive Inference 22
CHAPTER 4 Bayesian Linear Regression Model 43
CHAPTER 5 Bayesian Numerical Computation 61
CHAPTER 6 Bayesian Framework For Portfolio Allocation 92
CHAPTER 7 Prior Beliefs and Asset Pricing Models 118
CHAPTER 8 The Black-Litterman Portfolio Selection Framework 141
CHAPTER 9 Market Efficiency and Return Predictability 162
CHAPTER 10 Volatility Models 185
CHAPTER 11 Bayesian Estimation of ARCH-Type Volatility Models 202
CHAPTER 12 Bayesian Estimation of Stochastic Volatility Models 229
CHAPTER 13 Advanced Techniques for Bayesian Portfolio Selection 247
CHAPTER 14 Multifactor Equity Risk Models 280
References 298
Index 311
Svetlozar T. Rachev, PhD, Doctor of Science, is Chair-Professor at the University of Karlsruhe in the School of Economics and Business Engineering; Professor Emeritus at the University of California, Santa Barbara; and Chief-Scientist of FinAnalytica Inc.
John S. J. Hsu, PhD, is Professor of Statistics and Applied Probability at the University of CalifornlÃ
![Bayesian Methods in Finance [Hardcover]](/itemImage/2/1/1/3/2_760720.jpg)