A Generalized Convex Stochastic Dominance Algorithm

Stochastic dominance plays a prominent role in the theory of decision making under risk since it is able to identify inferior choices. Its applications include portfolio management, agricultural economics, and natural resource manage-ment. Generalized convex stochastic dominance enables the identification of greater numbers of inferior decisions than possible using other stochastic dominance criteria and enlarges the classes of decision makers for which there are dominance criteria. However, the use of this more discriminating and general criterion has been restricted since no computational method to determine the inferior risky choices has heretofore been obtained. Such a computational method is presented in this study and the application of the algorithm to some existing decision making problems is discussed. 1