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首页> 外文期刊>Journal of applied mathematics >On Minimizing the Ultimate Ruin Probability of an Insurer by Reinsurance
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On Minimizing the Ultimate Ruin Probability of an Insurer by Reinsurance

机译:通过再保险将保险人的最终破产概率减至最小

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We consider an insurance company whose reserves dynamics follow a diffusion-perturbed risk model. To reduce its risk, the company chooses to reinsure using proportional or excess-of-loss reinsurance. Using the Hamilton-Jacobi-Bellman (HJB) approach, we derive a second-order Volterra integrodifferential equation (VIDE) which we transform into a linear Volterra integral equation (VIE) of the second kind. We then proceed to solve this linear VIE numerically using the block-by-block method for the optimal reinsurance policy that minimizes the ultimate ruin probability for the chosen parameters. Numerical examples with both light- and heavy-tailed distributions are given. The results show that proportional reinsurance increases the survival of the company in both light- and heavy-tailed distributions for the Cramér-Lundberg and diffusion-perturbed models.
机译:我们考虑一家保险公司,其准备金动态遵循扩散扰动风险模型。为了降低风险,公司选择使用比例或超额损失再保险进行再保险。使用Hamilton-Jacobi-Bellman(HJB)方法,我们导出了二阶Volterra积分微分方程(VIDE),并将其转换为第二类线性Volterra积分方程(VIE)。然后,我们针对最佳再保险政策使用逐块方法数值求解此线性VIE,该策略将所选参数的最终破产概率降至最低。给出了具有轻尾分布和重尾分布的数值示例。结果表明,对于Cramér-Lundberg模型和扩散扰动模型,按比例再保险可以在轻尾和重尾分布中提高公司的生存率。

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