Reinsurance with neural networks
<|reference_start|>Reinsurance with neural networks: 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 Cram\'er-Lundberg model perturbed by a mean-reverting Ornstein-Uhlenbeck process.<|reference_end|>
@article{arandjelović2024reinsurance,
    title={Reinsurance with neural networks},
    author={Aleksandar Arandjelovi'c and Julia Eisenberg},
    journal={arXiv preprint arXiv:2408.06168},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.06168},
    primaryClass={q-fin.RM cs.NA math.NA math.OC math.PR q-fin.CP}
}