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Multi-period mean–variance portfolio optimization based on Monte-Carlo simulation

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  • Cong, F.
  • Oosterlee, C.W.

Abstract

We propose a simulation-based approach for solving the constrained dynamic mean–variance portfolio management problem. For this dynamic optimization problem, we first consider a sub-optimal strategy, called the multi-stage strategy, which can be utilized in a forward fashion. Then, based on this fast yet sub-optimal strategy, we propose a backward recursive programming approach to improve it. We design the backward recursion algorithm such that the result is guaranteed to converge to a solution, which is at least as good as the one generated by the multi-stage strategy. In our numerical tests, highly satisfactory asset allocations are obtained for dynamic portfolio management problems with realistic constraints on the control variables.

Suggested Citation

  • Cong, F. & Oosterlee, C.W., 2016. "Multi-period mean–variance portfolio optimization based on Monte-Carlo simulation," Journal of Economic Dynamics and Control, Elsevier, vol. 64(C), pages 23-38.
  • Handle: RePEc:eee:dyncon:v:64:y:2016:i:c:p:23-38
    DOI: 10.1016/j.jedc.2016.01.001
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    8. Yuqin Sun & Yungao Wu & Gejirifu De, 2023. "A Novel Black-Litterman Model with Time-Varying Covariance for Optimal Asset Allocation of Pension Funds," Mathematics, MDPI, vol. 11(6), pages 1-21, March.
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    11. Mahdi Massahi & Masoud Mahootchi & Alireza Arshadi Khamseh, 2020. "Development of an efficient cluster-based portfolio optimization model under realistic market conditions," Empirical Economics, Springer, vol. 59(5), pages 2423-2442, November.
    12. Cong, F. & Oosterlee, C.W., 2016. "On pre-commitment aspects of a time-consistent strategy for a mean-variance investor," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 178-193.
    13. Areski Cousin & Jérôme Lelong & Tom Picard, 2023. "Mean-variance dynamic portfolio allocation with transaction costs: a Wiener chaos expansion approach," Working Papers hal-04086378, HAL.
    14. Li, Yuying & Forsyth, Peter A., 2019. "A data-driven neural network approach to optimal asset allocation for target based defined contribution pension plans," Insurance: Mathematics and Economics, Elsevier, vol. 86(C), pages 189-204.
    15. Areski Cousin & J'er^ome Lelong & Tom Picard, 2023. "Mean-variance dynamic portfolio allocation with transaction costs: a Wiener chaos expansion approach," Papers 2305.16152, arXiv.org, revised Jun 2023.
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    17. Shiqi Gong & Shuaiqiang Liu & Danny D. Sun, 2023. "Optimal Market Making in the Chinese Stock Market: A Stochastic Control and Scenario Analysis," Papers 2306.02764, arXiv.org.
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    20. Fei Cong & Cornelis W. Oosterlee, 2017. "Accurate and Robust Numerical Methods for the Dynamic Portfolio Management Problem," Computational Economics, Springer;Society for Computational Economics, vol. 49(3), pages 433-458, March.

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    More about this item

    Keywords

    Dynamic portfolio management; Mean–variance optimization; Constrained optimization; Simulation method; Least squares regression;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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