Abstract
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.
Original language | English |
---|---|
Pages (from-to) | 224-233 |
Number of pages | 10 |
Journal | Insurance: Mathematics and Economics |
Volume | 47 |
Issue number | 2 |
DOIs | |
State | Published - Oct 2010 |
Keywords
- Dependence modelling
- Lévy copula
- Lévy measure
- Lévy process
- Maximum likelihood estimation
- Multivariate compound Poisson process