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Stochastic Dominance

Investment Decision Making under Uncertainty

  • Book
  • © 2006

Overview

Authors:
  1. Haim Levy

    1. The Hebrew University of Jerusalem, Jerusalem

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Part of the book series: Studies in Risk and Uncertainty (SIRU, volume 12)

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Table of contents (16 chapters)

  1. Front Matter

    Pages i-6
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  2. On the Measurement of Risk

    Pages 7-24

  3. Expected Utility Theory

    Pages 25-48

  4. Stochastic Dominance Decision Rules

    Pages 49-141

  5. Stochastic Dominance: The Quantile

    Pages 143-172

  6. Algorithms for Stochastic Dominance

    Pages 173-195

  7. Stochastic Dominance with Specific Distributions

    Pages 197-222

  8. The Empirical Studies

    Pages 223-240

  9. Applications of Stochastic Dominance Rules

    Pages 241-256

  10. Stochastic Dominance and Risk Measures

    Pages 257-269

  11. Stochastic Dominance and Diversification

    Pages 271-291

  12. Decision Making and the Investment Horizon

    Pages 293-312

  13. The CAMP and Stochastic Dominance

    Pages 313-329

  14. Almost Stochastic Dominance (ASD)

    Pages 331-351

  15. Non-Expected Utility and Stochastic Dominance

    Pages 353-371

  16. Stochastic Dominance and Prospect Theory

    Pages 373-393

  17. Future Research

    Pages 395-405

  18. Back Matter

    Pages 407-439
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Keywords

About this book

This second edition of Stochastic Dominance is devoted to investment decision­ making under uncertainty. The book covers four basic approaches to this process: a) The stochastic dominance (SD) approach, developed on the foundation of von-Neumann and Morgenstem^ expected utiHty paradigm. b) The mean-variance approach developed by Markowitz^ on the foundation of von-Neumann and Morgenstern's expected utility or simply on the assumption of a utility function based on mean and variance. c) The "almost" stochastic dominance (ASD) rules and the "almost" me- variance rule (AMV). No matter whether one employs objective or subjective probabilities, the common stochastic dominance criteria and the mean variance rule may lead to paradoxes: they are unable to rank prospect A w^hich yields $1 with a probability of 0.01 and a million dollars with probability of 0.99, and prospect B which yields $2 with certainty. This is an absurdity as in any sample of subjects one takes, 100% of subjects choose A. The "almost" stochastic dominance criteria and "almost" mean variance rule, which have been recently been developed by Leshno and Levy in 2002^, suggest a remedy to such paradoxes.

Reviews

From the reviews of the second edition:

"This book is an economics book about stochastic dominance. … is certainly a valuable reference for graduate students interested in decision making under uncertainty. It investigates and compares different approaches and presents many examples. Moreover, empirical studies and experimental results play an important role in this book, which makes it interesting to read." (Nicole Bäuerle, Mathematical Reviews, Issue 2007 d)

Authors and Affiliations

  • The Hebrew University of Jerusalem, Jerusalem

    Haim Levy

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