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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Identification Number : 10.1016/j.jeconom.2020.02.003


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
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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