基于Copula-AR(n)-LSV的死亡率建模及长寿风险度量  

Copula-AR(n)-SVL Mortality Models and Measurement of Longevity Risk

作　　者：贺磊[1] 林琳 HE Lei;LIN Lin(Hunan Key Laboratory of Macroeconomic Big Data Mining and Its Application,School of Business,Hunan Normal University,Changsha,410081,China)

机构地区：[1]宏观经济大数据挖掘与应用湖南省重点实验室,湖南师范大学商学院,长沙10081

出　　处：《应用概率统计》2021年第1期26-36,共11页Chinese Journal of Applied Probability and Statistics

基　　金：湖南省社科基金青年项目(批准号:17YBQ0067)资助。

摘　　要：合理的死亡率模型是精准度量长寿风险的关键.考虑不同年龄组间死亡率的相依性以及各年龄组死亡率的自相关性和异方差结构,运用多元Copula和AR(n)-LSV模型构建了随机动态死亡率模型,并在此基础上进一步运用VaR、TVaR、GlueVaR对长寿风险进行测度.研究结果表明Copula-AR(n)-LSV模型比Lee-Cater模型更好地刻画了死亡率趋势和波动;死亡率随着时间的推移逐渐改善,个体将面临逐年增长的长寿风险.A reasonable mortality model is the key to accurately measuring longevity risks.This paper considers the dependence of mortality among different age groups and the autocorrelation and heteroscedastic structure of mortality in each age group.The multivariate Copula and AR(n)-LSV models are used to construct the mortality model.VaR,TVaR,Glue VaR are used to measure longevity risk.The results show that Copula-AR(n)-LSV characterizes mortality trends and fluctuations better than Lee-Cater model;When mortality in China gradually decline,insurance companies will face increasing longevity risk in the future.

关 键 词：死亡率模型 长寿风险 相依性 异方差 

分 类 号：F840.67[经济管理—保险]