Proceedings of the Brawijaya International Conference on Multidisciplinary Sciences and Technology (BICMST 2020)

Assessing Optimal Retention With Quantile and Expectile Risk Measure

Authors
Novi Permata Indah, Arif Fadilla
Corresponding Author
Novi Permata Indah
Available Online 22 October 2020.
DOI
10.2991/assehr.k.201021.003How to use a DOI?
Keywords
Pareto Distribution, Reinsurance Contract, Quantile, Expectile, Coherent Risk Measures
Abstract

The form of claim severity from the reinsurance contracts is skewed to the right and heavy tail. The aims of this research are to determine the optimal risk measure on a reinsurance contracts. This risk measure is the coverage limit between an insurance company and a reinsurance company called optimal retention. Optimal retention in this research is estimated with 2 risk measures methods, which are the quantile-based Value-at-Risk (QVaR) and the expectile-based Value-at-Risk (EVaR). The Comparison results of the both methods by analytically and numerically show that EVaR is coherent and has a more optimal value than QVaR. As an illustration, we will use data of claim severity on a reinsurance contracts to determine the value of QVaR and EVaR.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the Brawijaya International Conference on Multidisciplinary Sciences and Technology (BICMST 2020)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
22 October 2020
ISBN
10.2991/assehr.k.201021.003
ISSN
2352-5398
DOI
10.2991/assehr.k.201021.003How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Novi Permata Indah
AU  - Arif Fadilla
PY  - 2020
DA  - 2020/10/22
TI  - Assessing Optimal Retention With Quantile and Expectile Risk Measure
BT  - Proceedings of the Brawijaya International Conference on Multidisciplinary Sciences and Technology (BICMST 2020)
PB  - Atlantis Press
SP  - 11
EP  - 14
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.201021.003
DO  - 10.2991/assehr.k.201021.003
ID  - Indah2020
ER  -