The asymptotic normality of the new estimator is established, and its performance illustrated by some results of simulation who shows the advantages of the new estimator over the estimator based on the classical extreme-value theory.
📌 3 Key Takeaways
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Objective & Hypothesis:The main aim of this paper is to propose an alternative estimate of the distortion risk measure for heavy-tailed claims.
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Key Findings & Data:Our approach is based on the result of Balkema and de Haan (1974) [3], and Pickands (1975) [22] for approximating the tail of the distribution by a generalized Pareto distribution.
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Conclusion & Impact:The asymptotic normality of the new estimator is established, and its performance illustrated by some results of simulation who shows the advantages of the new estimator over the estimator based on the classical extreme-value theory.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Premium principle · Distortion risk measure · POT method
Abstract
The main aim of this paper is to propose an alternative estimate of the distortion risk measure for heavy-tailed claims. Our approach is based on the result of Balkema and de Haan (1974) [3], and Pickands (1975) [22] for approximating the tail of the distribution by a generalized Pareto distribution. The asymptotic normality of the new estimator is established, and its performance illustrated by some results of simulation who shows the advantages of the new estimator over the estimator based on the classical extreme-value theory.
Abdelaziz, R. (2022). An improved estimator of the distortion risk measure for heavy-tailed claims. Hacettepe Journal of Mathematics and Statistics, Cilt: 44 - Sayı: 3, 735–746. https://ajindex.com/articles/530262