A1854
Title: Corrected inference about the extreme expected shortfall in the general max-domain of attraction
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 expected shortfall as a solution for various deficiencies of quantiles has gained substantial traction in 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 such as finance and environmental science, where the random variable of interest may have a much heavier tail or, conversely, 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 existing knowledge in the literature.
