A risk measurement approach from risk-averse stochastic optimization of score functions

Abstract

We propose a risk measurement approach for a risk-averse stochastic problem. We provide results that guarantee the existence of a solution to our problem. We characterize and explore the properties of the argmin as a risk measure and the minimum as a generalized deviation measure. We provide an example to demonstrate a specific application of our approach. Additionally, we present a numerical example of the problem's solution to illustrate the usefulness of our approach in risk management analysis.