Description

Book Synopsis
Bayesian Methods in Finance explains and illustrates the foundations of the Bayesian methodology in clear and accessible terms. It provides a unified examination of the use of the Bayesian theory and practice to analyze and evaluate asset management.

Table of Contents

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

Bayesian Methods in Finance

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    A Hardback by Svetlozar T. Rachev, John S. J. Hsu, Biliana S. Bagasheva

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      Publisher: John Wiley & Sons Inc
      Publication Date: 11/03/2008
      ISBN13: 9780471920830, 978-0471920830
      ISBN10: 0471920835
      Also in:
      Finance and the finance industry

      Description

      Book Synopsis
      Bayesian Methods in Finance explains and illustrates the foundations of the Bayesian methodology in clear and accessible terms. It provides a unified examination of the use of the Bayesian theory and practice to analyze and evaluate asset management.

      Table of Contents

      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

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