Stress Testing for VaR an CVaR
Dupacová, Jitka
Polivka, Jan
Practical use of the contamination technique in stress testing for risk measures Value at Risk (VaR) and Conditional Value at Risk (CVaR) and for optimization problems with these risk criteria is discussed. Whereas for CVaR its application is straightforward, the presence of the simple chance constraint in the definition of VaR requires that various distributional and structural properties are fulfilled, namely, for the unperturbed problem. These requirements rule out direct applications of the contamination technique in the case of discrete distributions, which includes the empirical VaR. On the other hand, in the case of a normal distribution and parametric VaR one may exploit stability results valid for quadratic programs.
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Is Part Of Series: Stochastic Programming E-Print Series - 3, SPEPS
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