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

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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
Author(s)
Hashorva E., Ratovomirija G., Tamraz M.
ISSN
0346-1238
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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01/09/2016 8:39
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20/08/2019 13:50
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