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A New Type of Conditional value-at-risk Model with Its Application

Xudong Wang

Abstract


This paper studies a new type of model and robust risk management in multi-confidence levels. Under the assumption of box discrete distribution of random variables, the paper build a optimization model of multi-confidence-level worst-case Conditional Value-at-Risk(WCVaR), use multi-objective decision and duality theory to transform it into traditional single-target linear program. As an application, MATAB is used to test the real Shanghai Stock Indices with 2898 observations and to illustrate the proposed approach by the method of Monte Carlo Simulation.

Keywords


Conditional Value-at-Risk; Multi-confidence levels; Box uncertainty; Monte Carlo Simulation

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