Objective Bayesian modelling of insurance risks with the skewed Student‐t distribution

Fabrizio Leisen, J. Miguel Marin and Cristiano Villa

Applied Stochastic Models in Business and Industry, 2017, vol. 33, issue 2, 136-151

Abstract: Insurance risks data typically exhibit skewed behaviour. In this paper, we propose a Bayesian approach to capture the main features of these data sets. This work extends a methodology recently introduced in the literature by considering an extra parameter that captures the skewness of the data. In particular, a skewed Student‐t distribution is considered. Two data sets are analysed: the Danish fire losses and the US indemnity loss. The analysis is carried with an objective Bayesian approach. For the discrete parameter representing the number of the degrees of freedom, we adopt a novel prior recently appeared in the literature. Copyright © 2017 John Wiley & Sons, Ltd.

Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/asmb.2227

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:apsmbi:v:33:y:2017:i:2:p:136-151

Access Statistics for this article

More articles in Applied Stochastic Models in Business and Industry from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().