Matrix Mittag-Leffler distributions and modeling heavy-tailed risks

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Serval ID
serval:BIB_04236C016619
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Matrix Mittag-Leffler distributions and modeling heavy-tailed risks
Journal
Extremes
Author(s)
Albrecher H., Bladt Martin, Bladt Mogens
Publication state
Published
Issued date
2020
Peer-reviewed
Oui
Volume
23
Number
3
Pages
425–450
Language
english
Abstract
In this paper we define the class of matrix Mittag-Leffler distributions and study some of its properties. We show that it can be interpreted as a particular case of an inhomogeneous phase-type distribution with random scaling factor. We then identify this class and its power transforms as a remarkably parsimonious and versatile family for the modelling of heavy-tailed risks, which overcomes some disadvantages of other approaches like the problem of threshold selection in extreme value theory. We illustrate this point both on simulated data as well as on a set of real-life MTPL insurance data that were modeled differently in the past.
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27/04/2020 10:33
Last modification date
04/08/2020 6:23
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