Tempered Pareto-type modelling using Weibull distributions

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Etat: Public
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ID Serval
serval:BIB_5760502CB2B9
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Tempered Pareto-type modelling using Weibull distributions
Périodique
ASTIN Bulletin
Auteur(s)
Albrecher H., Araujo Acuna J., Beirlant J.
ISSN
0515-0361 (print)
1783-1350 (electronic)
Statut éditorial
Publié
Date de publication
2021
Peer-reviewed
Oui
Volume
51
Numéro
2
Pages
509-538
Langue
anglais
Résumé
In various applications of heavy-tail modelling, the assumed Pareto behavior is tempered ultimately in the range of the largest data. In insurance applications, claim payments are influenced by claim management and claims may for instance be subject to a higher level of inspection at highest damage levels leading to weaker tails than apparent from modal claims. Generalizing earlier results of Meerschaert et al. (2012) and Raschke (2019), in this paper we consider tempering of a Pareto-type distribution with a general Weibull distribution in a peaks-over-threshold approach. This requires to modulate the tempering parameters as a function of the chosen threshold. Modelling such a tempering effect is important in order to avoid overestimation of risk measures such as the Value-at-Risk (VaR) at high quantiles. We use a pseudo maximum likelihood approach to estimate the model parameters, and consider the estimation of extreme quantiles. We derive basic asymptotic results for the estimators, give illustrations with simulation experiments and apply the developed techniques to fire and liability insurance data, providing insight into the relevance of the tempering component in heavy-tail modelling.
Création de la notice
16/11/2020 17:48
Dernière modification de la notice
19/05/2021 7:54
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