当前位置: X-MOL 学术Scand. Actuar. J. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Functional sensitivity analysis of ruin probability in the classical risk models
Scandinavian Actuarial Journal ( IF 1.8 ) Pub Date : 2021-04-14 , DOI: 10.1080/03461238.2021.1911840
Fatah Cheurfa 1, 2 , Baya Takhedmit 1 , Sofiane Ouazine 3 , Karim Abbas 1
Affiliation  

Sensitivity analysis investigates how the change in the output of a computational model can be attributed to changes of its input parameters. Identifying the input parameters that propagate more uncertainty on the ruin probability associated with insurance risk models is a challenging problem. In this paper, we consider the classical risk model, where an epistemic-uncertainty veils the true values of the claim size distribution rate and the Poisson arrival rate. Based on the available data for calibrating the probability distributions that model gaps of knowledge on these rates, and using the Taylor-series expansion methodology, we obtain the ruin probability under polynomial form in uncertain rates as a computational model. Specifically, we get a new sensitivity estimate of the ruin probability with respect to uncertain parameters. We provide a coherent framework within which we can accurately characterize statistically the uncertain ruin probability. In addition, we use the Markov's inequality to estimate the risk incurred by working with uncertain ruin probability rather than that evaluated at fixed parameters. A series of numerical experiments are presented to illustrate the potential of the proposed approach.



中文翻译:

经典风险模型中破产概率的函数敏感性分析

敏感性分析研究计算模型输出的变化如何归因于其输入参数的变化。识别在与保险风险模型相关的破产概率上传播更多不确定性的输入参数是一个具有挑战性的问题。在本文中,我们考虑经典风险模型,其中认知不确定性掩盖了索赔规模分布率和泊松到达率的真实值。基于可用于校准概率分布的可用数据,该概率分布对这些利率的知识差距进行建模,并使用泰勒级数展开方法,我们获得不确定利率的多项式形式下的破产概率作为计算模型。具体来说,我们得到了关于不确定参数的破产概率的新敏感性估计。我们提供了一个连贯的框架,在该框架内我们可以在统计上准确地表征不确定的破产概率。此外,我们使用马尔可夫不等式来估计因使用不确定的破产概率而不是在固定参数下评估的风险。提出了一系列数值实验来说明所提出方法的潜力。

更新日期:2021-04-14
down
wechat
bug