Extreme versions of Wang risk measures and their estimation

Abstract : Among the many possible ways to study the right tail of a real-valued random variable, a particularly general one is given by considering the family of its Wang distortion risk measures. This class of risk measures encompasses various interesting indicators such as the widely used Value-at-Risk and Tail Value-at-Risk, which are especially popular in actuarial science, for instance. We start by building simple extreme analogues of Wang distortion risk measures. Special cases of the risk measures of interest include the extreme Value-at-Risk as well as the recently introduced extreme Conditional Tail Moment. Adapted estimators of the resulting extreme Wang distortion risk measures are then introduced when the random variable of interest has a heavy-tailed distribution and their asymptotic normality is shown. The finite sample performance of our estimators is assessed on a simulation study.
Type de document :
Communication dans un congrès
8th International Conference of the ERCIM WG on Computational and Methodological Statistics, Dec 2015, London, United Kingdom. 2015
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https://hal.archives-ouvertes.fr/hal-01258640
Contributeur : Jonathan El Methni <>
Soumis le : mardi 19 janvier 2016 - 12:11:02
Dernière modification le : mardi 31 janvier 2017 - 16:51:32

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  • HAL Id : hal-01258640, version 1

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Jonathan El Methni, Gilles Stupfler. Extreme versions of Wang risk measures and their estimation. 8th International Conference of the ERCIM WG on Computational and Methodological Statistics, Dec 2015, London, United Kingdom. 2015. <hal-01258640>

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