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Longevity: A ‘Simple’ Stochastic Modelling of Mortality

Published online by Cambridge University Press:  10 June 2011

J. Duchassaing
Affiliation:
Partner Reinsurance Europe Limited, 153 rue de Courcelles, F-75817 Paris Cedex 17. Tel: +33 (0) 1 44 01 69 89; Fax: +33 (0)1 44 01 17 82; E-mail: [email protected]

Abstract

All UK insurers exposed to longevity risk need to perform stress tests for their Individual Capital Assessment (ICA). Some have put in place deterministic models which are arguably too simple; others have developed stochastic models that can be demanding and complex.

This paper presents a simple model to turn any deterministic mortality scenario into a stochastic model. We propose a simple model of stochastic variation that is easy to explain and to implement, which could be an alternative to and/or complete some of the well known models. The model can be applied to any best estimates of future mortality rates, as it aims to describe how longevity behaves around the projected expected values.

The paper proposes a possible calibration on the England and Wales population mortality that produces a minimum indication of possible future variation and uses the results to validate the model's assumptions. Using sample portfolios and the stochastic model, we can simulate cash flows to determine the distribution of the net present values (NPV) of annuity outgo.

Type
Sessional meetings: papers and abstracts of discussions
Copyright
Copyright © Institute and Faculty of Actuaries 2009

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References

REFERENCES

Bauer, D., Börger, M., Russ, J. & Zwiesler, H.-J. (2007). The volatility of mortality. Available at http://www.ifa-ulm.de/downloads/Vola_of_mortality.pdfGoogle Scholar
Boyer, S. & Fontana, E. (2009). RAC (Risk adjusted Capital) calculation for the non diversifiable part of the longevity and mortality risk. Thesis, Private communication.Google Scholar
Cairns, A.J.G., Blake, D., Dowd, K., Coughlan, G.D., Epstein, D., Ong, A. & Balevich, I. (2009). A quantitative comparison of stochastic mortality models using data from England and Wales and the United States. North American Actuarial Journal, 13(1), 135. http://www.jpmorgan.com/directdoc/LM_NAAJ2009QuantComparison.pdfGoogle Scholar
CEIOPS (2009). Draft CEIOPS' Advice for Level 2 Implementing Measures on Solvency II: Standard formula SCR — Article 109 c. Life underwriting risk. Consultation Paper No. 49, CEIOPS-CP-49/09.Google Scholar
CMI (2009a). Continuous Mortality Investigation Reports: No. 23. The Institute of Actuaries and the Faculty of Actuaries. http://www.actuaries.org.uk/knowledge/cmi/cmi_reports/cmir23Google Scholar
CMI (2009b). Continuous Mortality Investigation Working Paper: Number 37. Version 1.1 of the CMI Library of Mortality Projections. The Institute of Actuaries and the Faculty of Actuaries. http://www.actuaries.org.uk/_data/assets/pdf_file/0017/148211/WP37_v3.pdfGoogle Scholar
FRC (2006). GN46 Individual Capital Assessment V2.0 (BAS Amendment 1). Financial Reporting Council/Board of Actuarial Standard. http://www.frc.org.uk/documents/pagemanager/frc/GN46 Individual Capital Assessment V2.0 (BAS Amendment 1).pdfGoogle Scholar
HMD (2008). The Human Mortality Database, as accessed in 2008. http://www.mortality.org/Google Scholar
Jarque, C.M. & Bera, A.K. (1981). Efficient tests for normality, homoscedasticity and serial independence of regression residuals: Monte Carlo evidence. Economics Letters, 7(4), 313318.Google Scholar
Morgan, JP (2007). LifeMetrics: A toolkit for measuring and managing longevity and mortality risks. http://www.jpmorgan.com/directdoc/lifemetrics_technical.pdfGoogle Scholar