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Numerical Solution of Dynamic Portfolio Optimization with Transaction Costs

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  • Yongyang Cai
  • Kenneth L. Judd
  • Rong Xu

Abstract

We apply numerical dynamic programming to multi-asset dynamic portfolio optimization problems with proportional transaction costs. Examples include problems with one safe asset plus two to six risky stocks, and seven to 360 trading periods in a finite horizon problem. These examples show that it is now tractable to solve such problems.

Suggested Citation

  • Yongyang Cai & Kenneth L. Judd & Rong Xu, 2013. "Numerical Solution of Dynamic Portfolio Optimization with Transaction Costs," NBER Working Papers 18709, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:18709
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    References listed on IDEAS

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    1. Yongyang Cai & Kenneth Judd & Greg Thain & Stephen Wright, 2015. "Solving Dynamic Programming Problems on a Computational Grid," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 261-284, February.
    2. Yongyang Cai, 2019. "Computational Methods in Environmental and Resource Economics," Annual Review of Resource Economics, Annual Reviews, vol. 11(1), pages 59-82, October.
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    17. Kumar Muthuraman & Haining Zha, 2008. "Simulation‐Based Portfolio Optimization For Large Portfolios With Transaction Costs," Mathematical Finance, Wiley Blackwell, vol. 18(1), pages 115-134, January.
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    23. Cai, Yongyang & Judd, Kenneth L., 2012. "Dynamic programming with shape-preserving rational spline Hermite interpolation," Economics Letters, Elsevier, vol. 117(1), pages 161-164.
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    Cited by:

    1. Najafi, Amir Abbas & Pourahmadi, Zahra, 2016. "An efficient heuristic method for dynamic portfolio selection problem under transaction costs and uncertain conditions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 154-162.
    2. Yongyang Cai & Kenneth Judd & Jevgenijs Steinbuks, 2017. "A nonlinear certainty equivalent approximation method for dynamic stochastic problems," Quantitative Economics, Econometric Society, vol. 8(1), pages 117-147, March.
    3. Yongyang Cai & Kenneth Judd, 2015. "Dynamic programming with Hermite approximation," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 81(3), pages 245-267, June.
    4. Daniel Dimitrov, 2022. "Intergenerational Risk Sharing with Market Liquidity Risk," Tinbergen Institute Discussion Papers 22-028/VI, Tinbergen Institute.
    5. Alet Roux & Zhikang Xu, 2019. "Optimal investment and contingent claim valuation with exponential disutility under proportional transaction costs," Papers 1909.06260, arXiv.org, revised May 2021.
    6. Rongju Zhang & Nicolas Langren'e & Yu Tian & Zili Zhu & Fima Klebaner & Kais Hamza, 2016. "Dynamic portfolio optimization with liquidity cost and market impact: a simulation-and-regression approach," Papers 1610.07694, arXiv.org, revised Jun 2019.
    7. Peter Schober & Julian Valentin & Dirk Pflüger, 2022. "Solving High-Dimensional Dynamic Portfolio Choice Models with Hierarchical B-Splines on Sparse Grids," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 185-224, January.
    8. Sabastine Mushori & Delson Chikobvu, 2016. "A Stochastic Multi-stage Trading Cost model in optimal portfolio selection," EERI Research Paper Series EERI RP 2016/23, Economics and Econometrics Research Institute (EERI), Brussels.
    9. 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.
    10. 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.
    11. Kumar Yashaswi, 2021. "Deep Reinforcement Learning for Portfolio Optimization using Latent Feature State Space (LFSS) Module," Papers 2102.06233, arXiv.org.
    12. Yongyang Cai & Kenneth Judd & Greg Thain & Stephen Wright, 2015. "Solving Dynamic Programming Problems on a Computational Grid," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 261-284, February.

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    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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