Parameter estimation of a bivariate compound Poisson process
In this article, we review the concept of a Lévy copula to describe the dependence structure of a bivariate compound Poisson process. In this first statistical approach we consider a parametric model for the Lévy copula and estimate the parameters of the full dependent model based on a maximum likelihood approach. This approach ensures that the estimated model remains in the class of multivariate compound Poisson processes. A simulation study investigates the small sample behaviour of the MLEs, where we also suggest a new simulation algorithm. Finally, we apply our method to Danish fire insurance data.
Year of publication: |
2010
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Authors: | Esmaeili, Habib ; Klüppelberg, Claudia |
Published in: |
Insurance: Mathematics and Economics. - Elsevier, ISSN 0167-6687. - Vol. 47.2010, 2, p. 224-233
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Publisher: |
Elsevier |
Keywords: | Dependence modelling Levy copula Levy measure Levy process Maximum likelihood estimation Multivariate compound Poisson process |
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