Improved estimators of extreme Wang distortion risk measures for very heavy-tailed distributions

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Improved estimators of extreme Wang distortion risk measures for very heavy-tailed distributions

A general way to study the extremes of a random variable is to consider the family of its Wang distortion risk measures. This class of risk measures encompasses several indicators such as the classical quantile/Value-at-Risk, the Tail-Value-at-Risk and Conditional Tail Moments. Trimmed and winsorise...

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Bibliographic Details
Main Authors:	El Methni, Jonathan, Stupfler, Gilles
Format:	Article
Published:	Elsevier 2018
Subjects:	Asymptotic normality Extreme value statistics Heavy-tailed distribution Trimming Wang distortion risk measure Winsorising
Online Access:	https://eprints.nottingham.ac.uk/41195/

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