Risk aggregation with dependence and overdispersion based on the compound Poisson INAR(1) process

Mi Chen and Xiang Hu

Communications in Statistics - Theory and Methods, 2020, vol. 49, issue 16, 3985-4001

Abstract: This paper considers an extension of the classical discrete time risk model for which the claim numbers are assumed to be temporal dependence and overdispersion. The risk model proposed is based on the first-order integer-valued autoregressive (INAR(1)) process with discrete compound Poisson distributed innovations. The explicit expression for the moment generating function of the discounted aggregate claim amount is derived. Some numerical examples are provided to illustrate the impacts of dependence and overdispersion on related quantities such as the stop-loss premium, the value at risk and the tail value at risk.

Date: 2020
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DOI: 10.1080/03610926.2019.1594297

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