Daouia, Abdelaati, Girard, Stéphane and Stupfler, Gilles Claude (2020) Tail expectile process and risk assessment. Bernoulli journal, vol. 26 (n° 1). pp. 531-556.

This is the latest version of this item.

[thumbnail of dgs_xes.pdf]
Download (3MB) | Preview
Identification Number : 10.3150/19-BEJ1137


Expectiles dene a least squares analogue of quantiles. They are determined by tail expectations
rather than tail probabilities. For this reason and many other theoretical and practical merits,
expectiles have recently received a lot of attention, especially in actuarial and nancial risk management. Their estimation, however, typically requires to consider non-explicit asymmetric least squares estimates rather than the traditional order statistics used for quantile estimation. This makes the study of the tail expectile process a lot harder than that of the standard tail quantile process. Under the challenging model of heavy-tailed distributions, we derive joint weighted Gaussian approximations of the tail empirical expectile and quantile processes. We then use this powerful result to introduce and study new estimators of extreme expectiles and the standard quantile-based expected shortfall, as well as a novel expectile-based form of expected shortfall.
Our estimators are built on general weighted combinations of both top order statistics and
asymmetric least squares estimates. Some numerical simulations and applications to actuarial
and nancial data are provided.

Item Type: Article
Language: English
Date: January 2020
Refereed: Yes
Uncontrolled Keywords: Asymmetric least squares, Coherent risk measures, Expected shortfall, Expectile, Extrapolation, Extremes, Heavy tails, Tail index
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 02 Jul 2019 12:05
Last Modified: 04 Sep 2023 07:18
OAI Identifier: oai:tse-fr.eu:123155
URI: https://publications.ut-capitole.fr/id/eprint/32597

Available Versions of this Item

View Item


Downloads per month over past year