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Minimizing Lundberg inequality for ruin probability under correlated risk model by investment and reinsurance

机译:通过投资和再保险在相关风险模型下最小化Lundberg不等式的破产概率

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This paper investigates optimal investment and reinsurance policies for an insurance company under a correlated risk model with common Poisson shocks. The goal of the insurance company is to minimize the ultimate ruin probability. By the dynamic programming principle, the Hamiltona??Jacobia??Bellman (HJB for short) equation associated with this control problem is obtained. Since there is no explicit solution to the HJB equation, this paper alternates to find the minimal exponential upper bound of the ruin probability. The exponential upper bound of ruin probability is also called Lundberg inequality. Minimizing Lundberg inequality is equal to finding the maximal Lundberg coefficient. It turns out that the optimal investment and reinsurance polices are constant policies. Some numerical examples are given to illustrate the impact of the dependent structure and the investment chance on the upper bound.
机译:本文研究了在具有常见泊松冲击的相关风险模型下,保险公司的最佳投资和再保险政策。保险公司的目标是最大程度地降低最终破产的可能性。根据动态规划原理,得到了与该控制问题有关的哈密顿·雅各比亚·贝尔曼方程(简称HJB)。由于对HJB方程没有明确的解决方案,因此本文轮流寻找破产概率的最小指数上限。破产概率的指数上限也称为Lundberg不等式。最小化Lundberg不等式等于找到最大Lundberg系数。事实证明,最佳投资和再保险政策是一贯的政策。给出了一些数值例子来说明依赖结构和投资机会对上限的影响。

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