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Bayesian estimation of ruin probabilities with heterogeneous and heavy-tailed insurance claim size distribution
| Content Provider | Semantic Scholar |
|---|---|
| Author | Hedibert, M. Lopes Olivera, María Concepción Ausín |
| Copyright Year | 2007 |
| Abstract | This paper describes a Bayesian approach to make inference for risk reserve processes with unknown claim size distribution. A exible model based on mix- tures of Erlang distributions is proposed to approximate the special features frequently observed in insurance claim sizes such as long tails and heteroge- neity. A Bayesian density estimation approach for the claim sizes is implemen- ted using reversible jump Markov Chain Monte Carlo methods. An advantage of the considered mixture model is that it belongs to the class of phase-type distributions and then, explicit evaluations of the ruin probabilities are possible. Furthermore, from a statistical point of view, the parametric structure of the mixtures of Erlang distribution o�ers some advantages compared with the who- le over-parameterized family of phase-type distributions. Given the observed claim arrivals and claim sizes, we show how to estimate the ruin probabilities, as a function of the initial capital, and predictive intervals which give a measure of the uncertainty in the estimations. |
| Starting Page | 20 |
| Ending Page | 20 |
| Page Count | 1 |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://ruc.udc.es/dspace/bitstream/handle/2183/869/Ausin.Lopes.revised.pdf;sequence=1 |
| Alternate Webpage(s) | http://hedibert.org/wp-content/uploads/2013/12/ausin-lopes-2007.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
