Kernel-type estimator of the conditional tail expectation for a heavy-tailed distribution

Abdelaziz Rassoul

Insurance: Mathematics and Economics, 2013, vol. 53, issue 3, 698-703

Abstract: In this paper, we are interested in the generalization and improvement of the estimator of the conditional tail expectation (CTE) for a heavy-tailed distribution when the second moment is infinite. It is well known that classical estimators of the CTE are seriously biased under the second-order regular variation framework. To reduce the bias, many authors proposed the use of so-called second-order reduced bias estimators for both first-order and second-order tail parameters. In this work, we have generalized a kernel-type estimator, and we present a number of results on its distributional behavior and compare its performance with the performance of other estimators.

Keywords: Risk measure; CTE; Heavy tails; Kernel; Hill estimator; Extreme quantile; Reduced bias (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:53:y:2013:i:3:p:698-703

DOI: 10.1016/j.insmatheco.2013.09.004

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