Abstract
In this paper, we study an optimal reinsurance strategy combining a proportional and an excess of loss reinsurance. We refer to a collective risk theory model with two classes of dependent risks; particularly, the claim number of the two classes of insurance business has a bivariate Poisson distribution. In this contest, our aim is to maximize the expected utility of the terminal wealth. Using the control technique, we write the Hamilton-Jacobi-Bellman equation and, in the special case of the only excess of loss reinsurance, we obtain the optimal strategy in a closed form, and the corresponding value function.
Highlights
In the last two decades the optimal reinsurance problem has had an important impact in the actuarial literature
This paper considers two classes of insurance business, dependent through the number of
We assume that the principal insurer can implement both a proportional and an excess of loss reinsurance referred to both classes of insurance risks, with the respective retention levels ai (t ) ∈ (0,1),i = 1, 2 for the pro
Summary
In the last two decades the optimal reinsurance problem has had an important impact in the actuarial literature. A more realistic model has been often considered, with two or more dependent classes of insurance business. For example: in [3] where the excess of loss insurance is considered and the adjustment coefficient or the expected utility of the terminal wealth are maximized, in [4] and in [5] where the expected utility of the terminal weal this maximized, in [6] where the adjustment coefficient is maximized. This paper considers two classes of insurance business, dependent through the number of. (2016) Optimal Dynamic Proportional and Excess of Loss Reinsurance under Dependent Risks.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
