On some new dependence models derived from multivariate collective models in insurance applications

Détails

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Etat: Public
Version: de l'auteur⸱e
ID Serval
serval:BIB_1992185C07A9
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
On some new dependence models derived from multivariate collective models in insurance applications
Périodique
Scandinavian Actuarial Journal
Auteur⸱e⸱s
Hashorva E., Ratovomirija G., Tamraz M.
ISSN
0346-1238
1651-2030
Statut éditorial
Publié
Date de publication
14/09/2017
Peer-reviewed
Oui
Volume
2017
Numéro
8
Pages
730-750
Langue
anglais
Résumé
Consider two different portfolios which have claims triggered by the same events. Their corresponding collective model over a fixed time period is given in terms of individual claim sizes and a claim counting random variable N. In this paper, we are concerned with the joint distribution function (df) F of the largest claim sizes . By allowing N to depend on some parameter, say , then is for various choices of N a tractable parametric family of bivariate dfs. We investigate both distributional and extremal properties of . Furthermore, we present several applications of the implied parametric models to some data from the literature and a new data-set from a Swiss insurance company (Data-set can be downloaded here http://dx.doi.org/10.13140/RG.2.1.3082.9203.)
Mots-clé
Largest claims, copula, loss and ALAE, max-stable distribution, estimation, parametric family
Web of science
Création de la notice
01/09/2016 7:39
Dernière modification de la notice
20/08/2019 12:50
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