Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/42955
Title: Modelling uncertainty in insurance Bonus-Malus premium principles by using a Bayesian robustness approach
Authors: Gómez Déniz, Emilio 
Vázquez Polo, Francisco José 
UNESCO Clasification: 1209 Estadística
Keywords: Métodos bayesianos
Seguros
Issue Date: 2005
Publisher: 0266-4763
Journal: Journal of Applied Statistics 
Abstract: In a standard Bayesian model, a prior distribution is elicited for the structure parameter in order to obtain an estimate of this unknown parameter. The hierarchical model is a two way Bayesian one which incorporates a hyperprior distribution for some of the hyperparameters of the prior. In this way and under the Poisson-Gamma-Gamma model, a new distribution is obtained by computing the unconditional distribution of the random variable of interest. This distribution seems to provide a better fit to the data, given a policyholders' portfolio. Furthermore, Bayes premiums are thus obtained under a bonus-malus system and solve some of the problems of surcharges which appear in these systems when they are applied in a simple manner.
URI: http://hdl.handle.net/10553/42955
ISSN: 0266-4763
DOI: 10.1080/02664760500079746
Source: Journal of Applied Statistics[ISSN 0266-4763],v. 32, p. 771-784
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