Haim Levy 
Stochastic Dominance 
Investment Decision Making under Uncertainty

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 uti Hty 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.

Table of Content

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.