A0428
Title: Corrected inference about the extreme expected shortfall in the general max-domain of attraction (part I)
Authors: Abdelaati Daouia - Toulouse School of Economics (France)
Gilles Stupfler - University of Angers (France) [presenting]
Antoine Usseglio-Carleve - Avignon Université (France)
Abstract: The use of the expected shortfall as a solution for various deficiencies of quantiles has gained substantial traction in the field of risk assessment over the last 20 years. Existing approaches to its inference at extreme levels remain limited to distributions that are both heavy-tailed and have a finite second tail moment. This constitutes a strong restriction in areas like finance and environmental science, where the random variable of interest may have a much heavier tail or, at the opposite, may be light-tailed or short-tailed. Under a wider semiparametric extreme value framework, comprehensive asymptotic theory is developed for expected shortfall estimation above extreme quantiles in the class of distributions with finite first tail moment, regardless of whether the underlying extreme value index is positive, negative, or zero. The obtained asymptotic theory is contrasted with what is currently known in the literature.
