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A0554
Title: Automatic threshold selection for extreme value regression models Authors:  Julien Hambuckers - University of Liege (Belgium) [presenting]
Marie Kratz - ESSEC Business School, CREAR (France)
Antoine Usseglio-Carleve - Avignon Université (France)
Abstract: The problem of threshold selection is investigated in the context of the extreme value regression model. In this regression context, the threshold choice is a non-trivial task since it should also depend on the covariates and can have important consequences on the final estimates. We propose an efficient and robust solution to automatically estimate these thresholds with the help of the distributional regression machinery. We illustrate its properties through several simulation studies. The method is later applied to the estimation of hedge funds tail risks.