Abstract
A new approach to optimizing or hedging a portfolio of financial instruments to reduce risk is presented. Central to this approach are concepts and tools of set-optimization theory. It focuses on the problem of minimizing set-valued risk measures applied to portfolios. We present sufficient conditions for the existence of solutions of a set-valued risk minimization problem under some semi-continuity assumption. The methodology is applied to the optimization of set-valued Value at Risk and Average Value at Risk. Two examples at the end illustrate various features of the theoretical construction, among them the geometry of the image sets.
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