Abstract
L‐functionals summarize numerous statistical parameters and actuarial risk measures. Their sample estimators are linear combinations of order statistics (L‐statistics). There exists a class of heavy‐tailed distributions for which the asymptotic normality of these estimators cannot be obtained by classical results. In this paper we propose, by means of extreme value theory, alternative estimators for L‐functionals and establish their asymptotic normality. Our results may be applied to estimate the trimmed L‐moments and financial risk measures for heavy‐tailed distributions.
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