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Name: Benjamin Bobbia

Talk Title: Estimation of extreme conditional quantiles with coupling method

Abstract: The aim of this work is the estimation of extreme quantile of a real random variable conditionally to a covariate in dimension d. In the framework of proportional tails, inspired of the heteroscedatics extremes, we develop a coupling approach based on Wasserstein distance to provide asymptotic results about quantile and tail estimators. Those coupling arguments rely on the control of the Wasserstein distance between empirical measures and sharp bounds between the law of exceedances and the Pareto distribution. This approach also provide a validation procedure for proportional tails model.

This talk is a contributed talk at EVA 2021.