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Stress testing for VaR and CVaR

Author

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  • Jitka Dupacova
  • Jan PolIvka

Abstract

The 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.

Suggested Citation

  • Jitka Dupacova & Jan PolIvka, 2007. "Stress testing for VaR and CVaR," Quantitative Finance, Taylor & Francis Journals, vol. 7(4), pages 411-421.
    • Handle: RePEc:taf:quantf:v:7:y:2007:i:4:p:411-421
    DOI: 10.1080/14697680600973323
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    Cited by:

    1. Dupačová, Jitka & Kopa, Miloš, 2014. "Robustness of optimal portfolios under risk and stochastic dominance constraints," European Journal of Operational Research, Elsevier, vol. 234(2), pages 434-441.

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