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Asset-liability management for Czech pension funds using stochastic programming

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  • Jitka Dupačová
  • Jan Polívka

Abstract

It is possible to model a wide range of portfolio management problems using stochastic programming. This approach requires the generation of input scenarios and probabilities, which represent the evolution of the return on investment, the stream of liabilities and other random phenomena of the problem and respect the no-arbitrage properties. The quality of the recommended capital allocation depends on the quality of the input scenarios and a validation of results is necessary. Appropriate scenario generation techniques and output analysis methods are described in the context of defined contribution pension fund and applied to the specific model of a Czech pension fund. The numerical results indicate various components that influence the recommended investment decisions and the fund’s achievements. In particular, the initial balance sheet position of the pension fund is important for the optimal investment strategy because of the accounting rules embedded in the model and tracking of both the market and purchasing value of assets. Copyright Springer Science+Business Media, LLC 2009

Suggested Citation

  • Jitka Dupačová & Jan Polívka, 2009. "Asset-liability management for Czech pension funds using stochastic programming," Annals of Operations Research, Springer, vol. 165(1), pages 5-28, January.
  • Handle: RePEc:spr:annopr:v:165:y:2009:i:1:p:5-28:10.1007/s10479-008-0358-6
    DOI: 10.1007/s10479-008-0358-6
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    References listed on IDEAS

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    1. Winklevoss, Howard E, 1982. "Plasm: Pension Liability and Asset Simulation Model," Journal of Finance, American Finance Association, vol. 37(2), pages 585-594, May.
    2. Dempster, M. A. H. & Germano, M. & Medova, E. A. & Villaverde, M., 2003. "Global Asset Liability Management," British Actuarial Journal, Cambridge University Press, vol. 9(1), pages 137-195, April.
    3. Kjetil Høyland & Stein W. Wallace, 2001. "Generating Scenario Trees for Multistage Decision Problems," Management Science, INFORMS, vol. 47(2), pages 295-307, February.
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