On some new dependence models derived from multivariate collective models in insurance applications
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Version: author
State: Public
Version: author
Serval ID
serval:BIB_1992185C07A9
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
On some new dependence models derived from multivariate collective models in insurance applications
Journal
Scandinavian Actuarial Journal
ISSN
0346-1238
1651-2030
1651-2030
Publication state
Published
Issued date
14/09/2017
Peer-reviewed
Oui
Volume
2017
Number
8
Pages
730-750
Language
english
Abstract
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.)
Keywords
Largest claims, copula, loss and ALAE, max-stable distribution, estimation, parametric family
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Create date
01/09/2016 7:39
Last modification date
20/08/2019 12:50