Improved Estimator of the Conditional Tail Expectation in the case of heavy-tailed losses
Autor: | Laidi, Mohamed, Rassoul, Abdelaziz, Rouis, Hamid Ould |
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Rok vydání: | 2020 |
Předmět: | |
Druh dokumentu: | Working Paper |
DOI: | 10.19139/soic-2310-5070-665 |
Popis: | In this paper, we investigate the extreme-value methodology, to propose an improved estimator of the conditional tail expectation ($CTE$) for a loss distribution with a finite mean but infinite variance. The present work introduces a new estimator of the $CTE$ based on the bias-reduced estimators of high quantile for heavy-tailed distributions. The asymptotic normality of the proposed estimator is established and checked, in a simulation study. Moreover, we compare, in terms of bias and mean squared error, our estimator with the known old estimator. Comment: 17 pages, 4 figures |
Databáze: | arXiv |
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