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Daouia, Abdelaati
, Girard, Stéphane and Stupfler, Gilles Claude
(2021)
ExpectHill estimation, extreme risk and heavy tails.
Journal of Econometrics, vol. 221 (n° 1).
pp. 97-117.
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Abstract
Risk measures of a financial position are, from an empirical point of view, mainly based on quantiles. Replacing quantiles with their least squares analogues, called expectiles, has recently received increasing attention. The novel expectile-based risk measures satisfy all coherence requirements. We revisit their extreme value estimation for heavy-tailed distributions. First, we estimate the underlying tail index via weighted combinations of top order statistics and asymmetric least squares estimates. The resulting expectHill estimators are then used as the basis for estimating tail expectiles and Expected Shortfall. The asymptotic theory of the proposed estimators is provided, along with numerical simulations and applications to actuarial and financial data.
| Item Type: | Article |
|---|---|
| Language: | English |
| Date: | March 2021 |
| Refereed: | Yes |
| Uncontrolled Keywords: | Asymmetric least squares, Coherent risk measures, Expected shortfall, Expectile, Extrapolation, Extremes, Heavy tails, Tail index |
| JEL Classification: | C13 - Estimation C14 - Semiparametric and Nonparametric Methods |
| Subjects: | B- ECONOMIE ET FINANCE |
| Divisions: | TSE-R (Toulouse) |
| Site: | UT1 |
| Date Deposited: | 25 Mar 2020 08:29 |
| Last Modified: | 04 Sep 2023 07:18 |
| OAI Identifier: | oai:tse-fr.eu:124135 |
| URI: | https://publications.ut-capitole.fr/id/eprint/34206 |
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ExpectHill estimation, extreme risk and heavy tails. (deposited 19 Sep 2018 09:31)
- ExpectHill estimation, extreme risk and heavy tails. (deposited 25 Mar 2020 08:29) [Currently Displayed]
