Stochastic Optimization Models in Finance.
Title:
Stochastic Optimization Models in Finance.
Author:
Ziemba, William T.
ISBN:
9789812773654
Personal Author:
Edition:
2006th ed.
Physical Description:
1 online resource (756 pages)
Series:
World Scientific Handbook in Financial Economics Series ; v.1
World Scientific Handbook in Financial Economics Series
Contents:
CONTENTS -- Preface and Brief Notes to the 2006 Edition -- Preface in 1975 Edition -- Acknowledgments -- PART I. MATHEMATICAL TOOLS -- Introduction -- 1. Expected Utility Theory -- 2. Convexity and the Kuhn Tucker Conditions -- 3. Dynamic Programming -- Computational and Review Exercises -- Mind-Expanding Exercises -- PART II. QUALITATIVE ECONOMIC RESULTS -- Introduction -- 1. Stochastic Dominance -- 2. Measures of Risk Aversion -- 3. Separation Theorems -- Computational and Review Exercises -- Mind-Expanding Exercises -- PART III. STATIC PORTFOLIO SELECTION MODELS -- Introduction -- 1. Mean-Variance and Safety First Approaches and Their Extensions -- 2. Existence and Diversification of Optimal Portfolio Policies -- 3. Effects of Taxes on Risk Taking -- Computational and Review Exercises -- Mind-Expanding Exercises -- PART IV. DYNAMIC MODELS REDUCIBLE TO STATIC MODELS -- Introduction -- 1. Models That Have a Single Decision Point -- 2. Risk Aversion over Time Implies Static Risk Aversion -- 3. Myopic Portfolio Policies -- Computational and Review Exercises -- Mind-Expanding Exercises -- PART V. DYNAMIC MODELS -- Introduction -- 1. Two-Period Consumption Models and Portfolio Revision -- 2. Models of Optimal Capital Accumulation and Portfolio Selection -- 3. Models of Option Strategy -- 4. The Capital Growth Criterion and Continuous-Time Models -- Computational and Review Exercises -- Mind-Expanding Exercises -- Bibliography -- Index.
Abstract:
A reprint of one of the classic volumes on portfolio theory and investment, this book has been used by the leading professors at universities such as Stanford, Berkeley, and Carnegie-Mellon. It contains five parts, each with a review of the literature and about 150 pages of computational and review exercises and further in-depth, challenging problems. Frequently referenced and highly usable, the material remains as fresh and relevant for a portfolio theory course as ever. Sample Chapter(s). Chapter 1: Expected Utility Theory (373 KB). Contents: Mathematical Tools: Expected Utility Theory; Convexity and the Kuhn-Tucker Conditions; Dynamic Programming; Qualitative Economic Results: Stochastic Dominance; Measures of Risk Aversion; Separation Theorems; Static Portfolio Selection Models: Mean-Variance and Safety First Approaches and Their Extensions; Existence and Diversification of Optimal Portfolio Policies: Effects of Taxes on Risk Taking; Dynamic Models Reducible to Static Models: Models That Have a Single Decision Point; Risk Aversion over Time Implies Static Risk Aversion; Myopic Portfolio Policies; Dynamic Models: Two-Period Consumption Models and Portfolio Revision; Models of Optimal Capital Accumulation and Portfolio Selection; Models of Option Strategy; The Capital Growth Criterion and Continuous-Time Models. Readership: Postdoctoral and graduate students, researchers, academics, and professionals interested in portfolio theory and stochastic optimization.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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