Stochastic Dominance vs. Mean-Variance Portfolio Analysis: An Empirical Evaluation
Most of the work in portfolio theory in the past decade has been based on the principle of utility maximization where either the investor's utility function is assumed to be a second degree polynomial with a positive first derivative and a negative second derivative, or the probability functions are assumed to be normal. If at least one of these conditions holds, it can be shown that choosing among risky assets on the basis of their mean and variance only is consistent with the von Neumann-Morgenstern utility maximization model.' Thus, given the above assumptions, the incorporation of higher moments of a distribution and the adoption of alternative approaches to portfolio selection have largely been ignored in favor of the more familiar mean-variance approaches.
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