The Journal of Finance

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On Determination of Stochastic Dominance Optimal Sets

Published: 06/01/1985   |   DOI: 10.1111/j.1540-6261.1985.tb04965.x

VIJAY S. BAWA, JAMES N. BODURTHA, M. R. RAO, HIRA L. SURI

Applying Fishburn's [4] conditions for convex stochastic dominance, exact linear programming algorithms are proposed and implemented for assigning discrete return distributions into the first‐ and second‐order stochastic dominance optimal sets. For third‐order stochastic dominance, a superconvex stochastic dominance approach is defined which allows classification of choice elements into superdominated, mixed, and superoptimal sets. For a choice set of 896 security returns treated previously in the literature, 454, 25, and 13 distributions are in the first‐, second‐, and third‐order convex stochastic dominance optimal sets, respectively. These optimal sets compare with admissible first‐, second‐, and third‐order stochastic dominance sets of 682, 35, and 19 distributions, respectively.

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