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机构地区:[1]南开大学经济学院,天津300071
出 处:《保险研究》2013年第11期43-49,共7页Insurance Studies
基 金:中央高校基本科研业务费专项资金"金融工程与精算学中的定量风险管理统计模型与方法"(NKZXTD1101);国家自然科学基金面上项目(71271121)的资助
摘 要:本文首先对财险公司实际理赔数据进行分布拟合分析。通过三种拟合优度准则的比较,发现Burr分布比Pareto分布能更好地拟合赔款和直接理赔费用。其次,为了刻画赔款和直接理赔费用之间的相依关系,我们通过对常见的五类Copula函数进行参数估计,并比较赤迟信息准则(AIC)的大小,发现Gumbel Copula比其他常见的四类Copula函数更适合。最后,作为本文研究的应用实例,本文使用R软件的随机模拟函数,计算出一种特殊的再保险保费以及风险价值和尾部风险价值。In this paper,we firstly conducted a distribution fitting analysis on actual loss data of a non-life insur ance company. By comparing three criteria for goodness of fitting, we found that the Burr distributions were better than the Pareto distributions to fit the loss distribution functions of indemnity payment and allocated loss adjustment expense. Secondly, under the Akaike information criterion, we concluded that the best Copula function in commonly used five families was Gumbel Copula which could perfectly characterize the dependent relationship of indemnity payment and allocated loss adjustment expense. Based on these findings, we further calculated the reinsurance pre mium,value at risk and tail value at risk by stochastic simulation method with R software.
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