Kernel-type estimator of the reinsurance premium for heavy-tailed loss distributions
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Date
2014
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Publisher
Elsevier
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 biasreduced 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.
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Keywords
Proportional hazard premium, Reinsurance treaty, Bias reduction, Kernel estimator, Hill estimator, Extreme quantile, Heavy tails