Stochastic Dominance is devoted to investment decision-making under uncertainty. The book covers three basic approaches to this process: The stochastic dominance approach; the mean-variance approach; and the non-expected utility approach, focusing on prospect theory and its modified version, cumulative prospect theory. These approaches are discussed and compared in this book. In addition, this volume examines cases in which stochastic dominance rules coincide with the mean-variance rule and cases in which contradictions between these two approaches may occur. It then discusses the relationship between stochastic dominance rules and prospect theory, and establishes a new investment decision rule which combines the two and which we call prospect stochastic dominance. Although all three approaches are discussed, most of the book is devoted to the stochastic dominance paradigm.

Klappentext
Stochastic Dominance is devoted to investment decision-making under uncertainty. The book covers three basic approaches to this process: The stochastic dominance approach; the mean-variance approach; and the non-expected utility approach, focusing on prospect theory and its modified version, cumulative prospect theory.
These approaches are discussed and compared in this book. In addition, this volume examines cases in which stochastic dominance rules coincide with the mean-variance rule and cases in which contradictions between these two approaches may occur. It then discusses the relationship between stochastic dominance rules and prospect theory, and establishes a new investment decision rule which combines the two and which we call prospect stochastic dominance. Although all three approaches are discussed, most of the book is devoted to the stochastic dominance paradigm.

Zusammenfassung
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.

Inhalt
On the Measurement of Risk.- Expected Utility Theory.- Stochastic Dominance Decision Rules.- Stochastic Dominance: The Quantile.- Algorithms for Stochastic Dominance.- Stochastic Dominance with Specific Distributions.- The Empirical Studies.- Applications of Stochastic Dominance Rules.- Stochastic Dominance and Risk Measures.- Stochastic Dominance and Diversification.- Decision Making and the Investment Horizon.- The CAMP and Stochastic Dominance.- Almost Stochastic Dominance (ASD).- Non-Expected Utility and Stochastic Dominance.- Stochastic Dominance and Prospect Theory.- Future Research.