Authors:
- Fully revised 3rd Edition investigates and compares different approaches and presents many examples for investment decision-making under uncertainty
- Establishes a new investment decision rule prospect stochastic dominance (PSD), exploring the relationship between stochastic dominance rules and prospect theory
- Ideal reference on portfolio selection and investment decision making under uncertainty
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Table of contents (18 chapters)
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Front Matter
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Back Matter
About this book
This fully updated third edition is devoted to the analysis of various Stochastic Dominance (SD) decision rules. It discusses the pros and cons of each of the alternate SD rules, the application of these rules to various research areas like statistics, agriculture, medicine, measuring income inequality and the poverty level in various countries, and of course, to investment decision-making under uncertainty. The book features changes and additions to the various chapters, and also includes two completely new chapters. One deals with asymptotic SD and the relation between FSD and the maximum geometric mean (MGM) rule (or the maximum growth portfolio). The other new chapter discusses bivariate SD rules where the individual’s utility is determined not only by his own wealth, but also by his standing relative to his peer group.
Stochastic Dominance: Investment Decision Making under Uncertainty, 3rd Ed. covers the following basic issues: the SD approach, asymptotic SD rules, the mean-variance (MV) approach, as well as the non-expected utility approach. The non-expected utility approach focuses on Regret Theory (RT) and mainly on prospect theory (PT) and its modified version, cumulative prospect theory (CPT) which assumes S-shape preferences. In addition to these issues the book suggests a new stochastic dominance rule called the Markowitz stochastic dominance (MSD) rule corresponding to all reverse-S-shape preferences. It also discusses the concept of the multivariate expected utility and analyzed in more detail the bivariate expected utility case.
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
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School of Business Administration, The Hebrew University of Jerusalem, Jerusalem, Israel
Haim Levy
About the author
Prof. Levy was born in Jerusalem in 1939. He received his PhD from the Hebrew University in 1969 and in 1976 was promoted to full professorship. He developed a new field of financial economics called Stochastic Dominance, and developed economic models for risk-management, especially risk-reduction in investment, by means of international diversification and mergers and acquisitions. He served as economic advisor to the Bank of Israel; the Israeli Ministry of Finance; Ministry of Industry, Trade and Labor; and Ministry of National Infrastructures, among other government offices. His many awards include the Hebrew University's Prize for Excellence in Research for 1996. The two 1990 Nobel Prize winners in Economics stated that to a large extent their work draws on Prof. Levy's pioneering writings.
Bibliographic Information
Book Title: Stochastic Dominance
Book Subtitle: Investment Decision Making under Uncertainty
Authors: Haim Levy
DOI: https://doi.org/10.1007/978-3-319-21708-6
Publisher: Springer Cham
eBook Packages: Economics and Finance, Economics and Finance (R0)
Copyright Information: Springer International Publishing Switzerland 2016
Hardcover ISBN: 978-3-319-21707-9Published: 12 November 2015
Softcover ISBN: 978-3-319-33059-4Published: 23 August 2016
eBook ISBN: 978-3-319-21708-6Published: 31 October 2015
Edition Number: 3
Number of Pages: XXII, 505
Topics: Finance, general, Microeconomics, Operations Research/Decision Theory