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Insurance risks data typically exhibit skewed behaviour. In this paper, wepropose a Bayesian approach to capture the main features of these datasets.This work extends the methodology introduced in Villa and Walker (2014a) byconsidering an extra parameter which captures the skewness of the data. Inparticular, a skewed Student-t distribution is considered. Two datasets areanalysed: the Danish fire losses and the US indemnity loss. The analysis iscarried with an objective Bayesian approach. For the discrete parameterrepresenting the number of the degrees of freedom, we adopt a novel priorrecently introduced in Villa and Walker (2014b).

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