Return-Maximizing in Fuzzy Portfolio Processes under Average Value-at-Risk Constraints

A portfolio optimization is argued over in dynamic fuzzy asset management, using fuzzy random variables. Analytical solutions for a dynamic ret urn-maximizing problem under feasible average value-at-risk constraints are derived by dynamic/mathematical programming. A numerical example is investigated. It becomes clear that average value-at-risk is more useful for the portfolio optimization than value-at-risk.