Vine copula, constructed from bivariate copulas, provides great flexibility in modelling complex high-dimensional dependence. When applied to multi-population mortality modelling, vine copula yields significant improvement over traditional multivariate copulas. In this paper, we propose to capture time-varying features in mortality dependence with dynamic regular vine (R-vine) copula which is built from bivariate copulas with time-varying dependence parameters. We develop two dependence dynamics for R-vine copulas and illustrate the selection and estimation of dynamic R-vine copulas using mortality data from eight populations. The estimated R-vine copulas using the proposed dependence dynamics are shown to yield better goodness of fit than both static and regime-switching vine copulas. We further demonstrate the simulation of mortality paths using dynamic R-vine copulas and examine the impact of vine copula choice on the assessed effectiveness of longevity hedge.

由二元copulas构造的藤蔓copula，为建模复杂的高维依存关系提供了极大的灵活性。当应用于多种群死亡率建模时，藤蔓copula比传统的多变量copulas有了显着改善。在本文中，我们建议使用动态规则藤（R-vine）copula捕获死亡率依赖性的随时间变化的特征，该动态规则vine（R-vine）copula由具有时变依赖性参数的双变量copulas建立。我们为R-vine copulas开发了两个依赖动力学，并使用来自八个种群的死亡率数据说明了动态R-vine copulas的选择和估计。使用拟议的依赖性动力学估计的R-葡萄藤copulas比静态和政权转换的葡萄copulas产生更好的拟合优度。