Optimal reinsurance and dividends with transaction costs and taxes under thinning structure
Mi Chen, Kam Chuen Yuen, Wenyuan Wang

TL;DR
This paper develops an explicit solution for optimal dividend and reinsurance strategies in a risk model with thinning dependence, transaction costs, and taxes, using a diffusion approximation and quasi-variational inequalities.
Contribution
It introduces a tractable diffusion model for a complex risk process and derives explicit optimal strategies with closed-form value functions.
Findings
Optimal reinsurance is an excess-of-loss strategy.
Optimal dividends follow a barrier policy with upper and lower thresholds.
Explicit formulas for the value function are provided.
Abstract
In this paper, we investigate the problem of optimal strategies of dividend and reinsurance under the Cram\'{e}r-Lundberg risk model embedded with the thinning-dependence structure which was firstly introduced by Wang and Yuen (2005), subject to the optimality criteria of maximizing the expected accumulated discounted dividends paid until ruin. To enhance the practical relevance of the optimal dividend and reinsurance problem, non-cheap reinsurance is considered and transaction costs and taxes are imposed on dividends, which converts our optimization problem into a mixed classical-impulse control problem. For the purpose of better mathematical tractability and neat, explicit solutions of our control problem, instead of the Cram\'er-Lundberg framework we study its approximated diffusion model with two thinly dependent classes of insurance businesses. Using a method of quasi-variational…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsProbability and Risk Models · Insurance, Mortality, Demography, Risk Management · Stochastic processes and financial applications
