基于贝叶斯推断的巨灾损失数据整合方法与建模
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摘要
在对巨灾损失进行建模时,单个保险公司想要累积足够多的巨灾建模数据非常困难,也难以实现,一个有效的途径就是将本公司数据结合其他保险公司的同类数据,加上通过情形测试或其他方式获得的专家意见一起整合使用.利用贝叶斯推断整合保险公司巨灾损失索赔的外部数据、内部数据以及专家意见,对巨灾损失的发生频率和损失程度进行建模与估计,实现动态更新,并利用我国的地震巨灾损失数据进行实证分析。
It is hard for an insurance company to get enough data to do catastrophe modeling.Combining internal data,relevant external data and expert opinions could be a good way to model catastrophe loss.By means of Bayesian inference,data from three sources for an insurance company were combined to model the distributions of frequency and severity of catastrophe loss.Our catastrophe modeling method is new and could be updated dynamically.Finally,an empirical analysis was done based China's on earthquake loss data.
引文
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