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Minimizing the penalized goal-reaching probability with multiple dependent risks

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  • Huang, Ying
  • Peng, Jun

Abstract

We consider a robust optimal investment and reinsurance problem with multiple dependent risks for an Ambiguity-Averse Insurer (AAI), who wishes to minimize the probability that the value of the wealth process reaches a low barrier before a high goal. We assume that the insurer can purchase per-loss reinsurance for every class of insurance business and invest its surplus in a risk-free asset and a risky asset. Using the technique of stochastic control theory and solving the associated Hamilton-Jacobi-Bellman (HJB) equation, we derive the robust optimal investment-reinsurance strategy and the associated value function. We conclude that the robust optimal investment-reinsurance strategy coincides with the one without model ambiguity, but the value function differs. We also illustrate our results by numerical examples.

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  • Huang, Ying & Peng, Jun, 2025. "Minimizing the penalized goal-reaching probability with multiple dependent risks," Statistics & Probability Letters, Elsevier, vol. 217(C).
    • Handle: RePEc:eee:stapro:v:217:y:2025:i:c:s0167715224002566
    DOI: 10.1016/j.spl.2024.110287
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    References listed on IDEAS

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