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| Title: | Constrained monotone mean-variance investment-reinsurance under the Cramér-Lundberg model with random coefficients | Authors: | Shi, X Xu, ZQ |
Issue Date: | Jun-2024 | Source: | Systems and control letters, June 2024, v. 188, 105796 | Abstract: | This paper studies an optimal investment-reinsurance problem for an insurer (she) under the Cramér–Lundberg model with monotone mean–variance (MMV) criterion. At any time, the insurer can purchase reinsurance (or acquire new business) and invest in a security market consisting of a risk-free asset and multiple risky assets whose excess return rate and volatility rate are allowed to be random. The trading strategy is subject to a general convex cone constraint, encompassing no-shorting constraint as a special case. The optimal investment-reinsurance strategy and optimal value for the MMV problem are deduced by solving certain backward stochastic differential equations with jumps. In the literature, it is known that models with MMV criterion and mean–variance criterion lead to the same optimal strategy and optimal value when the wealth process is continuous. Our result shows that the conclusion remains true even if the wealth process has compensated Poisson jumps and the market coefficients are random. | Keywords: | BSDE with jumps Cone constraints Monotone mean–variance Random coefficients The Cramér–Lundberg model |
Publisher: | Elsevier BV | Journal: | Systems and control letters | ISSN: | 0167-6911 | EISSN: | 1872-7956 | DOI: | 10.1016/j.sysconle.2024.105796 | Rights: | © 2024 Elsevier B.V. All rights reserved. This is the preprint version of the following article: Shi, X., & Xu, Z. Q. (2024). Constrained monotone mean–variance investment-reinsurance under the Cramér–Lundberg model with random coefficients. Systems & Control Letters, 188, 105796, which is available at https://doi.org/10.1016/j.sysconle.2024.105796. |
| Appears in Collections: | Journal/Magazine Article |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| Shi_Constrained_Monotone_Mean–variance.pdf | Preprint version | 860.6 kB | Adobe PDF | View/Open |
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