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On a family of risk measures based on proportional hazards models and tail probabilities

Georgios Psarrakos and Miguel A. Sordo

Insurance: Mathematics and Economics, 2019, vol. 86, issue C, 232-240

Abstract: In this paper, we explore a class of tail variability measures based on distances among proportional hazards models. Tail versions of some well-known variability measures, such as the Gini mean difference, the Wang right tail deviation and the cumulative residual entropy are, up to a scale factor, in this class. These tail variability measures are combined with tail conditional expectation to generate premium principles that are especially useful to price heavy-tailed risks. We study their properties, including stochastic consistency and bounds, as well as the coherence of the associated premium principles.

Keywords: Proportional hazards model; Variability measures; Gini mean difference; Residual lifetime; Dispersive order; Premium principle; Cumulative residual entropy (search for similar items in EconPapers)
Date: 2019
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Insurance: Mathematics and Economics is currently edited by R. Kaas, Hansjoerg Albrecher, M. J. Goovaerts and E. S. W. Shiu

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