Optimal risk mitigation by deep reinsurance
Fuente:
arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866912721455284224 |
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| author | Arandjelović, Aleksandar Eisenberg, Julia |
| author_facet | Arandjelović, Aleksandar Eisenberg, Julia |
| contents | We consider an insurance company which faces financial risk in the form of insurance claims and market-dependent surplus fluctuations. The company aims to simultaneously control its terminal wealth (e.g. at the end of an accounting period) and the ruin probability in a finite time interval by purchasing reinsurance. The target functional is given by the expected utility of terminal wealth perturbed by a modified Gerber-Shiu penalty function. We solve the problem of finding the optimal reinsurance strategy and the corresponding maximal target functional via neural networks. The procedure is illustrated by a numerical example, where the surplus process is given by a Cramér-Lundberg model perturbed by a mean-reverting Ornstein-Uhlenbeck process. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_06168 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Optimal risk mitigation by deep reinsurance Arandjelović, Aleksandar Eisenberg, Julia Risk Management Numerical Analysis Optimization and Control Probability Computational Finance 68T07, 91G05, 91G60 We consider an insurance company which faces financial risk in the form of insurance claims and market-dependent surplus fluctuations. The company aims to simultaneously control its terminal wealth (e.g. at the end of an accounting period) and the ruin probability in a finite time interval by purchasing reinsurance. The target functional is given by the expected utility of terminal wealth perturbed by a modified Gerber-Shiu penalty function. We solve the problem of finding the optimal reinsurance strategy and the corresponding maximal target functional via neural networks. The procedure is illustrated by a numerical example, where the surplus process is given by a Cramér-Lundberg model perturbed by a mean-reverting Ornstein-Uhlenbeck process. |
| title | Optimal risk mitigation by deep reinsurance |
| topic | Risk Management Numerical Analysis Optimization and Control Probability Computational Finance 68T07, 91G05, 91G60 |
| url | https://arxiv.org/abs/2408.06168 |