论文摘要
再保险优化一直是精算科学领域一个重要的课题。众所周知,保险公司收取投保人保费并对投保人的风险负责。同时,保险公司也会在金融市场进行投资,所以它会面临来自保险业务和投资业务的双重风险。为了转移部分风险,保险公司往往会以部分潜在利润的损失为代价购买再保险。因此,如何寻找到一个能够平衡利润和风险的最优再保险策略已经在保险业引起广泛关注。本文探究了thinning相依模型中比例再保险的优化问题。在thinning相依模型中,导致索赔发生的随机源被分入不同的组内,并且每个组均可以一定的概率在每一个保险业务类别中引起赔付。与common-shock模型相比,thinning相依模型更加贴合实际。它使用更多的参数来描述问题,在实际应用中更加便于调整和拟合。在这里我们采用期望保费原理作为定价原理,并将期望效用最大化作为我们的优化目标。在第三章我们研究了 thinning相依风险模型中的最优策略。首先,我们探讨了解的存在和唯一性。之后,通过随机控制理论和与之相关的HJB方程,我们求出了thinning相依模型的最优策略和值函数的清晰解。在第四章我们研究了扩散逼近模型中的最优策略问题并给出了它的一般解。在第五章我们分析了得出的结果并提供了一些数值例子来展现不同参数对最优策略的影响。我们发现最优再保险策略不仅与再保费的安全载荷因子、时间以及投资的利润率有关,也与保险赔付额的分布和计数过程有很大关系。此外,决策人对于风险的态度对于最优策略也有很大影响。
论文目录
文章来源
类型: 硕士论文
作者: 杨新伟
导师: 梁志彬
关键词: 相依风险模型,比例再保险,随机最优控制,指数效用
来源: 南京师范大学
年度: 2019
分类: 基础科学,经济与管理科学
专业: 数学,宏观经济管理与可持续发展,保险
单位: 南京师范大学
分类号: F224;F840.4
DOI: 10.27245/d.cnki.gnjsu.2019.000903
总页数: 49
文件大小: 2378K
下载量: 17
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