Bayesian optimal investment and reinsurance with dependent financial and insurance risks

Bäuerle Nicole () and Leimcke Gregor ()
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Bäuerle Nicole: Department of Mathematics, Karlsruhe Institute of Technology (KIT), 76128 Karlsruhe, Germany
Leimcke Gregor: Department of Mathematics, Karlsruhe Institute of Technology (KIT), 76128 Karlsruhe, Germany

Statistics & Risk Modeling, 2022, vol. 39, issue 1-2, 23-47

Abstract: Major events like the COVID-19 crisis have impact both on the financial market and on claim arrival intensities and claim sizes of insurers. Thus, when optimal investment and reinsurance strategies have to be determined, it is important to consider models which reflect this dependence. In this paper, we make a proposal on how to generate dependence between the financial market and claim sizes in times of crisis and determine via a stochastic control approach an optimal investment and reinsurance strategy which maximizes the expected exponential utility of terminal wealth. Moreover, we also allow that the claim size distribution may be learned in the model. We give comparisons and bounds on the optimal strategy using simple models. What turns out to be very surprising is that numerical results indicate that even a minimal dependence which is created in this model has a huge impact on the optimal investment strategy.

Keywords: Risk theory; stochastic control; dependence modeling; learning; Bayesian model (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:strimo:v:39:y:2022:i:1-2:p:23-47:n:2

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DOI: 10.1515/strm-2021-0029

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