Please use this identifier to cite or link to this item: http://archives.univ-biskra.dz/handle/123456789/2281
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dc.contributor.authorAbdelhakim Necira-
dc.contributor.authorDjamel Meraghnia-
dc.contributor.authorFatima Meddia-
dc.date.accessioned2014-04-11T16:30:27Z-
dc.date.available2014-04-11T16:30:27Z-
dc.date.issued2014-04-11-
dc.identifier.urihttp://archives.univ-biskra.dz/handle/123456789/2281-
dc.description.abstractThe well known Proportional Hazard Premium Principle, introduced by Wang (1996), depends upon the survival function of the insured risk and a risk aversion index. Using this premium principle, we propose an asymptotically normal semi-parametric estimator for the net-premium of a high-excess loss layer of heavy-tailed claim amounts. An algorithm to compute confidence bounds is given. Moreover, a comparison between this estimator and the non-parametric estimator, proposed by Necir & Boukhetala (2004), is carried out. DOI:10.1080/03461230601162323 Link http://www.tandfonline.com/doi/abs/10.1080/03461230601162323#.U0T2Lqh5P78en_US
dc.subjectExtreme values, Heavy tails, Proportional Hazard Premium Principle, Risk theory, Reinsurance treaty.en_US
dc.titleStatistical estimate of the proportional hazard premium of lossen_US
dc.typeArticleen_US
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