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Henryk Zaehle, Saarland University Print
Thursday, 14 November 2013, 12:15 - 13:15

Henryk Zaehle, Saarland University

Comparative and qualitative robustness for law-invariant risk measures
 
Abstract: When estimating the risk of a P&L from historical data or Monte Carlo simulation, the robustness of the estimate is important. However, the classical notion of qualitative robustness as introduced by Hampel and Huber is not entirely suitable for risk measurement. In this talk, we propose and analyze a refined notion of robustness that applies to tail-dependent law-invariant convex risk measures on Orlicz spaces. This concept of robustness captures the tradeoff between robustness and sensitivity and can be quantified by an index of qualitative robustness. By means of this index, we can compare various risk measures, such as distortion risk measures, in regard to their degree of robustness.

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