Improved Estimator of the Conditional Tail Expectation in the case of heavy-tailed losses

Abstract

In this paper, we investigate the extreme-value methodology, to propose an improved estimator of the conditional tail expectation (CT E) for a loss distribution with a finite mean but infinite variance. The present work introduces a new estimator of the CT E 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.