贺磊, 林琳. 基于Copula-AR(n)-LSV的死亡率建模及长寿风险度量[J]. 应用概率统计, 2021, 37(1): 26-36. DOI: 10.3969/j.issn.1001-4268.2021.01.003
引用本文: 贺磊, 林琳. 基于Copula-AR(n)-LSV的死亡率建模及长寿风险度量[J]. 应用概率统计, 2021, 37(1): 26-36. DOI: 10.3969/j.issn.1001-4268.2021.01.003
HE Lei, LIN Lin. Copula-AR(n)-SVL Mortality Models and Measurement of Longevity Risk[J]. Chinese Journal of Applied Probability and Statistics, 2021, 37(1): 26-36. DOI: 10.3969/j.issn.1001-4268.2021.01.003
Citation: HE Lei, LIN Lin. Copula-AR(n)-SVL Mortality Models and Measurement of Longevity Risk[J]. Chinese Journal of Applied Probability and Statistics, 2021, 37(1): 26-36. DOI: 10.3969/j.issn.1001-4268.2021.01.003

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

  • 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.

     

    Abstract: 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, GlueVaR 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.

     

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