Basis risk modelling: a co-integration based approach
Most mortality models are generally calibrated on national population. However, pensions funds and annuity providers are mainly interested in the mortality rates of their own portfolio. In this paper we put forward a multivariate approach for forecasting pairwise mortality rates of related population. The investigated approach links national population mortality to a subset population using an econometric model that captures a long-run relationship between both mortality dynamics. This model does not lay the emphasis on the correlation that the two given mortality dynamics would present but rather on the long-term behaviour, which suggests that the two time-series cannot wander off in opposite directions for very long without mean reverting force on grounds of biological reasonableness. The model additionally captures the short-run adjustment between the considered mortality dynamics. Our aim is to propose a consistent approach to forecast pairwise mortality and to some extent to better control and assess basis risk underlying index-based longevity securitization. An empirical comparison of the forecast of one-year death probabilities of portfolio-experienced mortality is performed using both a factor-based model and the proposed approach. The robustness of the model is tested on mortality rate data for England & Wales and Continuous Mortality Investigation assured lives representing a sub-population.
|Date of creation:||Feb 2012|
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- Carsten Trenkler, 2008.
"Determining p-values for systems cointegration tests with a prior adjustment for deterministic terms,"
Springer, vol. 23(1), pages 19-39, January.
- Trenkler, Carsten, 2004. "Determining p-values for Systems Cointegration Tests With a Prior Adjustment for Deterministic Terms," Papers 2004,37, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
- MacKinnon, James G & Haug, Alfred A & Michelis, Leo, 1999. "Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 563-577, Sept.-Oct.
- Mackinnon, J.G. & Haug, A.A. & Michelis, L., 1996. "Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration," G.R.E.Q.A.M. 96a09, Universite Aix-Marseille III.
- James G. MacKinnon & Alfred A. Haug & Leo Michelis, 1996. "Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration," Working Papers 1996_07, York University, Department of Economics.
- Stéphane Loisel, 2010. "Understanding, Modeling and Managing Longevity Risk: Key Issues and Main Challenges," Post-Print hal-00517902, HAL.
- Pauline Barrieu & Harry Bensusan & Nicole El Karoui & Caroline Hillairet & Stéphane Loisel & Claudia Ravanelli & Yahia Salhi, 2012. "Understanding, Modeling and Managing Longevity Risk: Key Issues and Main Challenges," Post-Print hal-00417800, HAL.
- Willets, R. C., 2004. "The Cohort Effect: Insights and Explanations," British Actuarial Journal, Cambridge University Press, vol. 10(04), pages 833-877, October.
- Willets, R. C. & Gallop, A. P. & Leandro, P. A. & Lu, J. L. C. & Macdonald, A. S. & Miller, K. A. & Richards, S. J. & Robjohns, N. & Ryan, J. P. & Waters, H. R., 2004. "Longevity in the 21st Century," British Actuarial Journal, Cambridge University Press, vol. 10(04), pages 685-832, October.
- Booth, H. & Tickle, L., 2008. "Mortality Modelling and Forecasting: a Review of Methods," Annals of Actuarial Science, Cambridge University Press, vol. 3(1-2), pages 3-43, September.
- Cairns, Andrew J.G. & Blake, David & Dowd, Kevin & Coughlan, Guy D. & Khalaf-Allah, Marwa, 2011. "Bayesian Stochastic Mortality Modelling for Two Populations," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 41(01), pages 29-59, May. Full references (including those not matched with items on IDEAS)