MODELLING MORTALITY DEPENDENCE WITH REGIME-SWITCHING COPULAS

Rui Fen Zhou

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Insurance, Mortality, Demography, Risk Management Financial Risk and Volatility Modeling Probability and Risk Models

Abstract

Abstract We propose a two-regime Markov switching copula to depict the evolution of mortality dependence. One regime represents periods of high dependence and the other regime represents periods of low dependence. Each regime features a regular vine (R-vine) copula that, built on bivariate copulas, provides great flexibility for modelling complex high-dimensional dependence. Our estimated model indicates that the years of recovery from extreme mortality deterioration and the years of health care reform more likely fall into the low regime, while the years in which extreme mortality deteriorating events break out and the peaceful years without major mortality-impacting events more likely fall into the high regime. We use a case study to illustrate how the regime-switching copula can be applied to assess the effectiveness of longevity risk hedge with different beliefs about future mortality dependence evolution incorporated.

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References

1987Co-Integration and Error Correction: Representation, Estimation, and Testing 1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation 1991Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models 1989A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle 1992Modeling and Forecasting U. S. Mortality 2007Pair-copula constructions of multiple dependence 1999State-Space Models with Regime Switching 2000State-Space Models with Regime-Switching: Classical and Gibbs Sampling Approaches with Applications

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