Hostname: page-component-76fb5796d-22dnz Total loading time: 0 Render date: 2024-04-25T13:19:49.307Z Has data issue: false hasContentIssue false

Dynamic Programming Approach to Pension Funding: the Case of Incomplete State Information

Published online by Cambridge University Press:  29 August 2014

Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Haberman and Sung (1994) have presented a dynamic model for a defined benefit occupational pension scheme which considered two types of risk: the “contribution rate” and the “solvency” risk. The current paper, extends this work by deriving optimal funding control procedures for determining the contribution rate for the case of a stochastic model with incomplete state information, making use of the separation principle. The stochastic inputs modelled are the investment returns and the benefit outgo.

Type
Workshop
Copyright
Copyright © International Actuarial Association 2002

References

Bellman, R. (1957) “Dynamic Programming”, Princeton University Press, Princeton.Google ScholarPubMed
Bertsekas, D.P. (1976) “Dynamic Programming and Stochastic Control”, Academic Press, New York.Google Scholar
Chang, S.C. (1999) “Optimal Pension Funding through Dynamic Simulations: the case of Taiwan Public Employees Retirement System”. Insurance: Mathematics and Economics, 24, 187199.Google Scholar
Dufresne, D. (1988) “Moments of Pension Fund Contributions and Fund Levels when Rates of Return are Random”. Journal of the Institute of Actuaries, 115, 535544.CrossRefGoogle Scholar
Haberman, S. (1992) “Pension Funding with Time Delays – A Stochastic ApproachInsurance: Mathematics & Economics 11, 179189.Google Scholar
Haberman, S. (1993) “Pension Funding with Time Delays and Autoregressive Rates of Return”. Insurance: Mathematics & Economics 13, 4556.Google Scholar
Haberman, S., Butt, Z. and Megaloudi, C. (2000) “Contribution and Solvency Risk in a Defined Benefit Pension Scheme”. Insurance: Mathematics & Economics, 27, 237259.Google Scholar
Haberman, S. and Sung, J.H. (1994) “Dynamic Approaches to Pension Funding”, Insurance: Mathematics and Economics, 15, 151162.Google Scholar
Kwakernaak, H. and Sivan, R. (1972) “Linear Optimal Control Systems”, Wiley-Interscience, New York.Google Scholar
Keyfitz, N. (1985). “Applied Mathematical Demography” (second edition). Springer, New York.CrossRefGoogle Scholar
Owadally, M.I. and Haberman, S. (1999) “Pension Fund Dynamics and Gains/Losses Due to Random Rates of Investment Return. North American Actuarial Journal, 3 (No 3), 105117.CrossRefGoogle Scholar
Owadally, M.I. and Haberman, S. (2000) “Efficient Amortization of Actuarial Gains/Losses and Optimal Funding in Pension Plans”. Actuarial Research Paper No 133, Department of Actuarial Science and Statistics, City University. Under review.Google Scholar
Whittle, P. (1983). “Optimization over Time: Dynamic Programming and Stochastic Control”, Vol. II, John Wiley & Sons, Chichester.Google Scholar
Zimbidis, A. and Haberman, S. (1993) “Delay, Feedback and Variability of Pension Contributions and Fund Levels”. Insurance: Mathematics and Economics 13, 271285.Google Scholar