B1186
Title: A de-randomization argument for estimating extreme value parameters of heavy tails
Authors: Joseph Hachem - Toulouse School of Economics (France) [presenting]
Abdelaati Daouia - Toulouse School of Economics (France)
Gilles Stupfler - University of Angers (France)
Abstract: In extreme value analysis, it has recently been shown that one can use a de-randomization trick, replacing a random threshold in the estimator of interest with its deterministic counterpart, in order to estimate several extreme risks simultaneously, but only in an i.i.d. context. The aim is to show how the method can be used to handle the estimation of several tail quantities (tail index, expected shortfall, distortion risk measures, etc.) in general dependence/heteroskedasticity/heterogeneity settings under a weighted $L^1$ assumption on the gap between the average distribution of the data and the prevailing distribution.
