Bayesian Methods in Finance / Edition 1

Bayesian Methods in Finance / Edition 1

by Svetlozar T. Rachev, John S. J. Hsu, Biliana S. Bagasheva, Frank J. Fabozzi
     
 

ISBN-10: 0471920835

ISBN-13: 9780471920830

Pub. Date: 02/08/2008

Publisher: Wiley

Recent years have seen an impressive growth in the variety and complexity of quantitative models and modeling techniques used in finance, particularly in portfolio and risk management. While criticisms of the excessive reliance on quantitative models resurface with each turmoil in the financial markets, the focus should be on employing techniques such that the

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Overview

Recent years have seen an impressive growth in the variety and complexity of quantitative models and modeling techniques used in finance, particularly in portfolio and risk management. While criticisms of the excessive reliance on quantitative models resurface with each turmoil in the financial markets, the focus should be on employing techniques such that the likelihood of extreme events as well as the uncertainty of the decision-making environment are properly accounted for. Bayesian methods, coupled with heavy-tailed distributional assumptions, provide one theoretically sound avenue to achieve this goal.

Together with the ability to incorporate inform-ation from different sources and tackle complex estimation problems, dealing with estimation uncertainty has been a driving factor behind the increased popularity of Bayesian methods among academics and practitioners alike.

The aim of Bayesian Methods in Finance is to provide an overview of the theory of Bayesian methods and explain their real-world applications to financial modeling. While the principles and concepts explained in 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.

Bayesian Methods in Finance offers both students of finance and practitioners an invaluable resource in the form of a previously unavailable, highly accessible, unified look at the use of the Bayesian methodology—as well as numerical computational methods—in financial models and asset management.

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Product Details

ISBN-13:
9780471920830
Publisher:
Wiley
Publication date:
02/08/2008
Series:
Frank J. Fabozzi Series, #153
Pages:
329
Sales rank:
1,202,279
Product dimensions:
6.40(w) x 9.17(h) x 1.16(d)

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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