OPTIMALITY CONDITIONS FOR PORTFOLIO OPTIMIZATION PROBLEMS WITH CONVEX DEVIATION MEASURES AS OBJECTIVE FUNCTIONS

Abstract

In this paper we derive by means of the duality theory necessary and sufficient optimality conditions for convex optimization problems having as objective function the composition of a convex function with a linear mapping defined on a finite-dimensional space with values in a Hausdorff locally convex space. We use the general results for deriving optimality conditions for two portfolio optimization problems having as objective functions different convex deviation measures.