Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/2260
Title: Bias-corrected estimation in distortion risk premiums for heavy-tailed losses
Authors: Brahim Brahimi
Fatima Meddi
Abdelhakim Necir
Keywords: Bias reduction
High quantiles
Hill estimator
L-statistics
Order statistics
Risk Measure
Second order regular variation
Tail index
Issue Date: 11-Apr-2013
Abstract: Recently Necir and Meraghni (2009) proposed an asymptotically normal estimator for distortion risk premiums when losses follow heavy-tailed distributions. In this paper, we propose a bias-corrected estimator of this class of risk premiums and establish its asymptotic normality. Our considerations are based on the high quantile estimator given by Matthys and Beirlant 2003.Link http://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.as/1359744270
URI: http://dspace.univ-biskra.dz:8080/jspui/handle/123456789/2260
Appears in Collections:Publications Internationales

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