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

  • Mohamed Laidi National High School of Technology, Algiers, Algeria.LRDSI laboratory, Blida 1 university, Blida, Algeria
  • Abdelaziz Rassoul High School of Hydraulics, Blida, Algeria
  • Hamid Ould Rouis University of Blida 1, Blida, Algeria
Keywords: Risk measure, Conditional tail expectation, Bias reduction, extreme quantile, order statistic, heavy-tailed distribution.


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.

Author Biographies

Mohamed Laidi, National High School of Technology, Algiers, Algeria.LRDSI laboratory, Blida 1 university, Blida, Algeria
National High School of Technology, Algiers, Algeria; LRDSI laboratory, Blida 1 university, Blida, Algeria  
Abdelaziz Rassoul, High School of Hydraulics, Blida, Algeria
High School of Hydraulics, Blida, Algeria
Hamid Ould Rouis, University of Blida 1, Blida, Algeria
University of Blida 1, Blida, Algeria


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How to Cite
Laidi, M., Rassoul, A., & Ould Rouis, H. (2020). Improved Estimator of the Conditional Tail Expectation in the case of heavy-tailed losses. Statistics, Optimization & Information Computing, 8(1), 98-109.
Research Articles