A Weissman-type estimator of the conditional marginal expected shortfall

Yuri Goegebeur; Armelle Guillou; Nguyen Khanh Le Ho; Jing Qin

doi:10.1016/j.ecosta.2021.09.006

A Weissman-type estimator of the conditional marginal expected shortfall

Yuri Goegebeur^*, Armelle Guillou, Nguyen Khanh Le Ho, Jing Qin

^*Kontaktforfatter

Institut for Matematik og Datalogi

University of Strasbourg

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

Abstract

The marginal expected shortfall is an important risk measure in finance and actuarial science, which has been extended recently to the case where the random variables of main interest are observed together with a covariate. This leads to the concept of conditional marginal expected shortfall for which an estimator is proposed allowing extrapolation outside the data range. The main asymptotic properties of this estimator have been established, using empirical processes arguments combined with the multivariate extreme value theory. The finite sample behavior of the proposed estimator is evaluated with a simulation experiment, and the practical applicability is illustrated on vehicle insurance customer data.

Originalsprog	Engelsk
Tidsskrift	Econometrics and Statistics
Vol/bind	27
Sider (fra-til)	173-196
ISSN	2468-0389
DOI	https://doi.org/10.1016/j.ecosta.2021.09.006
Status	Udgivet - jul. 2023

Bibliografisk note

Funding Information:
The authors would like to thank the referees, the Associate Editor and editor for their helpful comments. The research of Armelle Guillou was supported by the French National Research Agency under the grant ANR-19-CE40-0013-01/ExtremReg project and an International Emerging Action (IEA-00179). Computation/simulation for the work described in this paper was supported by the DeIC National HPC Centre, SDU.

Publisher Copyright:
© 2021 EcoSta Econometrics and Statistics

Dokumenter og links

10.1016/j.ecosta.2021.09.006

https://hal.archives-ouvertes.fr/hal-02613135v4/file/CMES-Extra-Rev3.pdf

SDU link

Tjek adgangen til materialet i Syddansk Universitetsbiblioteks søgemaskine

1 Ph.d.-afhandling

Estimation of Dependence in Multivariate Extreme Value Statistics
Ho, N. K. L., 9. nov. 2022, Syddansk Universitet. Det Naturvidenskabelige Fakultet. 176 s.
Publikation: Afhandling › Ph.d.-afhandling

Citationsformater

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abstract = "The marginal expected shortfall is an important risk measure in finance and actuarial science, which has been extended recently to the case where the random variables of main interest are observed together with a covariate. This leads to the concept of conditional marginal expected shortfall for which an estimator is proposed allowing extrapolation outside the data range. The main asymptotic properties of this estimator have been established, using empirical processes arguments combined with the multivariate extreme value theory. The finite sample behavior of the proposed estimator is evaluated with a simulation experiment, and the practical applicability is illustrated on vehicle insurance customer data.",

keywords = "Conditional marginal expected shortfall, extrapolation, Pareto-type distribution",

author = "Yuri Goegebeur and Armelle Guillou and Ho, {Nguyen Khanh Le} and Jing Qin",

note = "Funding Information: The authors would like to thank the referees, the Associate Editor and editor for their helpful comments. The research of Armelle Guillou was supported by the French National Research Agency under the grant ANR-19-CE40-0013-01/ExtremReg project and an International Emerging Action (IEA-00179). Computation/simulation for the work described in this paper was supported by the DeIC National HPC Centre, SDU. Publisher Copyright: {\textcopyright} 2021 EcoSta Econometrics and Statistics",

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AU - Ho, Nguyen Khanh Le

AU - Qin, Jing

N1 - Funding Information: The authors would like to thank the referees, the Associate Editor and editor for their helpful comments. The research of Armelle Guillou was supported by the French National Research Agency under the grant ANR-19-CE40-0013-01/ExtremReg project and an International Emerging Action (IEA-00179). Computation/simulation for the work described in this paper was supported by the DeIC National HPC Centre, SDU. Publisher Copyright: © 2021 EcoSta Econometrics and Statistics

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N2 - The marginal expected shortfall is an important risk measure in finance and actuarial science, which has been extended recently to the case where the random variables of main interest are observed together with a covariate. This leads to the concept of conditional marginal expected shortfall for which an estimator is proposed allowing extrapolation outside the data range. The main asymptotic properties of this estimator have been established, using empirical processes arguments combined with the multivariate extreme value theory. The finite sample behavior of the proposed estimator is evaluated with a simulation experiment, and the practical applicability is illustrated on vehicle insurance customer data.

AB - The marginal expected shortfall is an important risk measure in finance and actuarial science, which has been extended recently to the case where the random variables of main interest are observed together with a covariate. This leads to the concept of conditional marginal expected shortfall for which an estimator is proposed allowing extrapolation outside the data range. The main asymptotic properties of this estimator have been established, using empirical processes arguments combined with the multivariate extreme value theory. The finite sample behavior of the proposed estimator is evaluated with a simulation experiment, and the practical applicability is illustrated on vehicle insurance customer data.

KW - Conditional marginal expected shortfall

KW - extrapolation

KW - Pareto-type distribution

U2 - 10.1016/j.ecosta.2021.09.006

DO - 10.1016/j.ecosta.2021.09.006

M3 - Journal article

AN - SCOPUS:85118890291

SN - 2468-0389

VL - 27

SP - 173

EP - 196

JO - Econometrics and Statistics

JF - Econometrics and Statistics

ER -

A Weissman-type estimator of the conditional marginal expected shortfall

Abstract

Bibliografisk note

Dokumenter og links

SDU link

Fingeraftryk

Relaterede publikationer

Estimation of Dependence in Multivariate Extreme Value Statistics

Citationsformater