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Kernel-type estimator of the reinsurance premium for heavy-tailed loss distributions

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  • Benkhelifa, Lazhar

Abstract

In this paper, we generalize the classical estimator of the reinsurance premium for heavy-tailed loss distributions with a kernel-type estimator. Since this estimator exhibits a bias, we propose its bias-reduced version by using a least-squares method. The asymptotic normality of the proposed estimators is established under suitable assumptions. A small simulation study is carried out to prove the performance of our approach.

Suggested Citation

  • Benkhelifa, Lazhar, 2014. "Kernel-type estimator of the reinsurance premium for heavy-tailed loss distributions," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 65-70.
    • Handle: RePEc:eee:insuma:v:59:y:2014:i:c:p:65-70
    DOI: 10.1016/j.insmatheco.2014.08.006
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    References listed on IDEAS

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    1. Deme, El Hadji & Girard, Stéphane & Guillou, Armelle, 2013. "Reduced-bias estimator of the Proportional Hazard Premium for heavy-tailed distributions," Insurance: Mathematics and Economics, Elsevier, vol. 52(3), pages 550-559.
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    6. Vandewalle, B. & Beirlant, J., 2006. "On univariate extreme value statistics and the estimation of reinsurance premiums," Insurance: Mathematics and Economics, Elsevier, vol. 38(3), pages 441-459, June.
    7. Beirlant, J. & Matthys, G. & Dierckx, G., 2001. "Heavy-Tailed Distributions and Rating," ASTIN Bulletin, Cambridge University Press, vol. 31(1), pages 37-58, May.
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