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Estimating the Optimal Stochastic Dominance Efficient Set with a Mean-Semivariance Algorithm

Published online by Cambridge University Press:  06 April 2009

Roger P. Bey
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Extract

The theoretical desirability of stochastic dominance (SD) as a decision rule is well established [1, 3, 4, 7, and 11]. However, implementation of SD as a decision rule has been hindered seriously by the lack of an optimal search algorithm [8]. An optimal search algorithm is desirable since it takes the distribution of returns for a group of assets and determines the optimal proportion of each asset which should be combined to provide efficient combinations. For example, for a given expected value (variance) the mean-variance (EV) algorithm builds the portfolio with the smallest (largest) variance (expected value). The EV algorithm determines which assets should be combined and the proportion of the total investment that should be invested in each asset. An analogous algorithm does not exist for SD.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 14 , Issue 5 , December 1979 , pp. 1059 - 1070
Copyright
Copyright © School of Business Administration, University of Washington 1979

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References

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