RBNS的线性预测模型

Linear Prediction Model for RBNS

  • 摘要: 传统的准备金方法都是基于聚合数据的, 聚合数据是个体数据的汇总, 它们丢失了许多有用信息, 影响了准备金预测的准确性. 本文提出了一个基于个体数据的线性预测模型, 该模型不需要对数据的矩的具体形式进行假设, 更不需要对数据的分布进行假设, 而只需假设个体索赔数据的前两阶矩存在, 具有适用范围广, 简单易操作等特点. 在文章的最后, 通过随机模拟把提出的方法与著名的链梯法进行了对比, 模拟结果显示, 本文提出的方法是行之有效的

     

    Abstract: The traditional claims reserving approaches are all based on the aggregated data and usually produce inaccurate predictions of the reserve because the aggregated data usually failed to use all the information of the individual claims. A linear prediction model based on the individual claims is proposed in this paper, in which only the second order moment of the data is required. This method is flexible and simple and hence easy to apply in reality. The proposed method is compared with the traditional chain ladder method via a simulation study as well, and the simulation results illustrate that the proposed approach performs well

     

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