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Model points and Tail-VaR in life insurance

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  • Denuit, Michel
  • Trufin, Julien

Abstract

Often, actuaries replace a group of heterogeneous life insurance contracts (different age at policy issue, contract duration, sum insured, etc.) with a representative one in order to speed the computations. The present paper aims to homogenize a group of policies by controlling the impact on Tail-VaR and related risk measures.

Suggested Citation

  • Denuit, Michel & Trufin, Julien, 2015. "Model points and Tail-VaR in life insurance," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 268-272.
    • Handle: RePEc:eee:insuma:v:64:y:2015:i:c:p:268-272
    DOI: 10.1016/j.insmatheco.2015.06.002
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    References listed on IDEAS

    as
    1. Kling, Bart & Wolthuis, Henk, 1992. "Ordering of risks in life insurance," Insurance: Mathematics and Economics, Elsevier, vol. 11(2), pages 139-152, August.
    2. Denuit, Michel & Vermandele, Catherine, 1998. "Optimal reinsurance and stop-loss order," Insurance: Mathematics and Economics, Elsevier, vol. 22(3), pages 229-233, July.
    3. Frostig, Esther, 2001. "A comparison between homogeneous and heterogeneous portfolios," Insurance: Mathematics and Economics, Elsevier, vol. 29(1), pages 59-71, August.
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    Cited by:

    1. Mark Kiermayer & Christian Wei{ss}, 2019. "Grouping of Contracts in Insurance using Neural Networks," Papers 1912.09964, arXiv.org.
    2. Ana M. Ferreiro & Enrico Ferri & José A. García & Carlos Vázquez, 2021. "Global Optimization for Automatic Model Points Selection in Life Insurance Portfolios," Mathematics, MDPI, vol. 9(5), pages 1-19, February.
    3. Ana Maria Ferreiro-Ferreiro & José Antonio García-Rodríguez & Luis A. Souto & Carlos Vázquez, 2020. "Efficient Model Points Selection in Insurance by Parallel Global Optimization Using Multi CPU and Multi GPU," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 62(1), pages 5-20, February.

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