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Yasser, Abbas
, Daouia, Abdelaati, Nemouchi, Boutheina and Stupfler, Gilles
(2025)
Tail expectile-VaR estimation in the semiparametric Generalized Pareto model.
TSE Working Paper, n. 25-1607, Toulouse
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Abstract
Expectiles have received increasing attention as coherent and elicitable market risk measure. Their estimation from heavy-tailed data in an extreme value framework has been studied using solely the Weissman extrapolation method. We challenge this dominance by developing the theory of two classes of semiparametric Generalized Pareto estimators that make more efficient use of tail observations by incorporating the location, scale and shape extreme value parameters: the first class relies on asymmetric least squares estimation, while the second is based on extreme quantile estimation. A comparison with simulated and real data shows the superiority of our proposals for real-valued profit-loss distributions.
| Item Type: | Monograph (Working Paper) |
|---|---|
| Language: | English |
| Date: | January 2025 |
| Place of Publication: | Toulouse |
| Uncontrolled Keywords: | Expectile, Extreme risk, Generalized Pareto model, Heavy tails, Semiparametric, extrapolation |
| JEL Classification: | C13 - Estimation C14 - Semiparametric and Nonparametric Methods C53 - Forecasting and Other Model Applications |
| Subjects: | B- ECONOMIE ET FINANCE |
| Divisions: | TSE-R (Toulouse) |
| Institution: | Université Toulouse Capitole |
| Site: | UT1 |
| Date Deposited: | 17 Jan 2025 10:37 |
| Last Modified: | 17 Jan 2025 10:37 |
| OAI Identifier: | oai:tse-fr.eu:130105 |
| URI: | https://publications.ut-capitole.fr/id/eprint/50102 |
