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Dividend Maximization Under a Set Ruin Probability Target in the Presence of Proportional and Excess-of-loss Reinsurance

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dc.creator Kasumo, Christian
dc.creator Kasozi, Juma
dc.creator Kuznetsov, Dmitry
dc.date 2020-07-10T06:16:49Z
dc.date 2020-07-10T06:16:49Z
dc.date 2020-06
dc.date.accessioned 2022-10-25T09:15:57Z
dc.date.available 2022-10-25T09:15:57Z
dc.identifier https://dspace.nm-aist.ac.tz/handle/20.500.12479/843
dc.identifier.uri http://hdl.handle.net/123456789/94715
dc.description This research article published by Applications and Applied Mathematics, Vol. 15, Issue 1 (June 2020)
dc.description We study dividend maximization with set ruin probability targets for an insurance company whose surplus is modelled by a diffusion perturbed classical risk process. The company is permitted to enter into proportional or excess-of-loss reinsurance arrangements. By applying stochastic control theory, we derive Volterra integral equations and solve numerically using block-by-block methods. In each of the models, we have established the optimal barrier to use for paying dividends provided the ruin probability does not exceed a predetermined target. Numerical examples involving the use of both light- and heavy-tailed distributions are given. The results show that ruin probability targets result in an improvement in the optimal barrier to be used for dividend payouts. This is the case for light- and heavy-tailed distributions and applies regardless of the risk model used.
dc.format application/pdf
dc.language en
dc.publisher Applications and Applied Mathematics
dc.subject Hamilton-Jacobi-Bellman equation
dc.subject Volterra equation
dc.subject Block-by-block method
dc.subject Ruin probability
dc.subject Ruin probability target
dc.title Dividend Maximization Under a Set Ruin Probability Target in the Presence of Proportional and Excess-of-loss Reinsurance
dc.type Article


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