Objective Bayesian modelling of insurance risks with the skewed Student-t distribution
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2017-03-01
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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.
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Leisen, F, JM Marin and C Villa (2017). Objective Bayesian modelling of insurance risks with the skewed Student-t distribution. Applied Stochastic Models in Business and Industry, 33(2). pp. 136–151. 10.1002/asmb.2227 Retrieved from https://hdl.handle.net/10161/33564.
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Cristiano Villa
Prof. Cristiano Villa main research area is in Bayesian statistics, with particular interest in objective methods. His output has been published in several peer-reviewed journals and presented at international conferences, such as the ISBA International Conference, the O-Bayes conference, and the ERCIM conference. In addition to his research, Prof. Villa is deeply committed to teaching and enjoys interacting with students. His teaching interests include probability, statistics, linear modelling, and risk management. Before joining Duke Kunshan University (DKU), Prof. Villa was a member of the Newcastle University (UK) and the University of Kent (UK). Prior to joining academia in 2014, he worked as an auditor and as an advisor for KPMG in several countries, including, Italy, UK, New Zealand, and Singapore. He holds an M.Sc. and a Ph.D. from the University of Kent, UK.
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