Robust estimator of distortion risk premiums for heavy-tailed losses
classification
🧮 math.ST
stat.TH
keywords
estimatorrobustdistortionriskasymptoticconditionderiveestablish
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We use the so-called t-Hill tail index estimator proposed by Fabi\'an(2001), rather than Hill's one, to derive a robust estimator for the distortion risk premium of loss. Under the second-order condition of regular variation, we establish its asymptotic normality. By simulation study, we show that this new estimator is more robust than of Necir and Meraghni 2009 both for small and large samples.
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