IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v295y2021i3p1074-1086.html
   My bibliography  Save this article

Adaptive online portfolio selection with transaction costs

Author

Listed:
  • Guo, Sini
  • Gu, Jia-Wen
  • Ching, Wai-Ki

Abstract

As an application of machine learning techniques in financial fields, online portfolio selection has been attracting great attention from practitioners and researchers, which makes timely sequential decision making available when market information is constantly updated. For online portfolio selection, transaction costs incurred by changes of investment proportions on risky assets have a significant impact on the investment strategy and the return in long-term investment horizon. However, in many online portfolio selection studies, transaction costs are usually neglected in the decision making process. In this paper, we consider an adaptive online portfolio selection problem with transaction costs. We first propose an adaptive online moving average method (AOLMA) to predict the future returns of risky assets by incorporating an adaptive decaying factor into the moving average method, which improves the accuracy of return prediction. The net profit maximization model (NPM) is then constructed where transaction costs are considered in each decision making process. The adaptive online net profit maximization algorithm (AOLNPM) is designed to maximize the cumulative return by integrating AOLMA and NPM together. Numerical experiments show that AOLNPM dominates several state-of-the-art online portfolio selection algorithms in terms of various performance metrics, i.e., cumulative return, mean excess return, Sharpe ratio, Information ratio and Calmar ratio.

Suggested Citation

  • Guo, Sini & Gu, Jia-Wen & Ching, Wai-Ki, 2021. "Adaptive online portfolio selection with transaction costs," European Journal of Operational Research, Elsevier, vol. 295(3), pages 1074-1086.
  • Handle: RePEc:eee:ejores:v:295:y:2021:i:3:p:1074-1086
    DOI: 10.1016/j.ejor.2021.03.023
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221721002496
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2021.03.023?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ling, Aifan & Sun, Jie & Wang, Meihua, 2020. "Robust multi-period portfolio selection based on downside risk with asymmetrically distributed uncertainty set," European Journal of Operational Research, Elsevier, vol. 285(1), pages 81-95.
    2. Staino, Alessandro & Russo, Emilio, 2020. "Nested Conditional Value-at-Risk portfolio selection: A model with temporal dependence driven by market-index volatility," European Journal of Operational Research, Elsevier, vol. 280(2), pages 741-753.
    3. Ha, Youngmin & Zhang, Hai, 2020. "Algorithmic trading for online portfolio selection under limited market liquidity," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1033-1051.
    4. Guo, Sini & Yu, Lean & Li, Xiang & Kar, Samarjit, 2016. "Fuzzy multi-period portfolio selection with different investment horizons," European Journal of Operational Research, Elsevier, vol. 254(3), pages 1026-1035.
    5. David P. Helmbold & Robert E. Schapire & Yoram Singer & Manfred K. Warmuth, 1998. "On‐Line Portfolio Selection Using Multiplicative Updates," Mathematical Finance, Wiley Blackwell, vol. 8(4), pages 325-347, October.
    6. Bin Li & Steven C. H. Hoi, 2012. "On-Line Portfolio Selection with Moving Average Reversion," Papers 1206.4626, arXiv.org.
    7. Chakrabarti, Deepayan, 2021. "Parameter-free robust optimization for the maximum-Sharpe portfolio problem," European Journal of Operational Research, Elsevier, vol. 293(1), pages 388-399.
    8. László Györfi & Gábor Lugosi & Frederic Udina, 2006. "Nonparametric Kernel‐Based Sequential Investment Strategies," Mathematical Finance, Wiley Blackwell, vol. 16(2), pages 337-357, April.
    9. Leal, Marina & Ponce, Diego & Puerto, Justo, 2020. "Portfolio problems with two levels decision-makers: Optimal portfolio selection with pricing decisions on transaction costs," European Journal of Operational Research, Elsevier, vol. 284(2), pages 712-727.
    10. Zhang, Wei-Guo & Liu, Yong-Jun & Xu, Wei-Jun, 2012. "A possibilistic mean-semivariance-entropy model for multi-period portfolio selection with transaction costs," European Journal of Operational Research, Elsevier, vol. 222(2), pages 341-349.
    11. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    12. Balter, Anne G. & Mahayni, Antje & Schweizer, Nikolaus, 2021. "Time-consistency of optimal investment under smooth ambiguity," European Journal of Operational Research, Elsevier, vol. 293(2), pages 643-657.
    13. Li, Xiang & Qin, Zhongfeng & Kar, Samarjit, 2010. "Mean-variance-skewness model for portfolio selection with fuzzy returns," European Journal of Operational Research, Elsevier, vol. 202(1), pages 239-247, April.
    14. Hiroshi Konno & Hiroaki Yamazaki, 1991. "Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market," Management Science, INFORMS, vol. 37(5), pages 519-531, May.
    15. Györfi László & Udina Frederic & Walk Harro, 2008. "Nonparametric nearest neighbor based empirical portfolio selection strategies," Statistics & Risk Modeling, De Gruyter, vol. 26(2), pages 145-157, March.
    16. Gaivoronski, Alexei A. & Stella, Fabio, 2003. "On-line portfolio selection using stochastic programming," Journal of Economic Dynamics and Control, Elsevier, vol. 27(6), pages 1013-1043, April.
    17. Alexei Gaivoronski & Fabio Stella, 2000. "Stochastic Nonstationary Optimization for Finding Universal Portfolios," Annals of Operations Research, Springer, vol. 100(1), pages 165-188, December.
    18. Cui, Xiangyu & Gao, Jianjun & Shi, Yun & Zhu, Shushang, 2019. "Time-consistent and self-coordination strategies for multi-period mean-Conditional Value-at-Risk portfolio selection," European Journal of Operational Research, Elsevier, vol. 276(2), pages 781-789.
    19. Yuanyuan Zhang & Xiang Li & Sini Guo, 2018. "Portfolio selection problems with Markowitz’s mean–variance framework: a review of literature," Fuzzy Optimization and Decision Making, Springer, vol. 17(2), pages 125-158, June.
    20. Xiang Li & Hui Jiang & Sini Guo & Wai-ki Ching & Lean Yu, 2020. "On product of positive L-R fuzzy numbers and its application to multi-period portfolio selection problems," Fuzzy Optimization and Decision Making, Springer, vol. 19(1), pages 53-79, March.
    21. Brandtner, Mario & Kürsten, Wolfgang & Rischau, Robert, 2020. "Beyond expected utility: Subjective risk aversion and optimal portfolio choice under convex shortfall risk measures," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1114-1126.
    22. Thomas M. Cover, 1991. "Universal Portfolios," Mathematical Finance, Wiley Blackwell, vol. 1(1), pages 1-29, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhijun Xu & Jing Zhou, 2023. "A simultaneous diagonalization based SOCP relaxation for portfolio optimization with an orthogonality constraint," Computational Optimization and Applications, Springer, vol. 85(1), pages 247-261, May.
    2. Guo, Sini & Gu, Jia-Wen & Fok, Christopher H. & Ching, Wai-Ki, 2023. "Online portfolio selection with state-dependent price estimators and transaction costs," European Journal of Operational Research, Elsevier, vol. 311(1), pages 333-353.
    3. Man Yiu Tsang & Tony Sit & Hoi Ying Wong, 2022. "Adaptive Robust Online Portfolio Selection," Papers 2206.01064, arXiv.org.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guo, Sini & Gu, Jia-Wen & Fok, Christopher H. & Ching, Wai-Ki, 2023. "Online portfolio selection with state-dependent price estimators and transaction costs," European Journal of Operational Research, Elsevier, vol. 311(1), pages 333-353.
    2. Bin Li & Steven C. H. Hoi, 2012. "Online Portfolio Selection: A Survey," Papers 1212.2129, arXiv.org, revised May 2013.
    3. Ha, Youngmin & Zhang, Hai, 2020. "Algorithmic trading for online portfolio selection under limited market liquidity," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1033-1051.
    4. Roujia Li & Jia Liu, 2022. "Online Portfolio Selection with Long-Short Term Forecasting," SN Operations Research Forum, Springer, vol. 3(4), pages 1-15, December.
    5. Yong Zhang & Xingyu Yang, 2017. "Online Portfolio Selection Strategy Based on Combining Experts’ Advice," Computational Economics, Springer;Society for Computational Economics, vol. 50(1), pages 141-159, June.
    6. Vajda, István & Ottucsák, György, 2006. "Empirikus portfólióstratégiák [Empirical portfolio strategies]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 624-640.
    7. Guy Uziel & Ran El-Yaniv, 2017. "Growth-Optimal Portfolio Selection under CVaR Constraints," Papers 1705.09800, arXiv.org.
    8. Man Yiu Tsang & Tony Sit & Hoi Ying Wong, 2022. "Adaptive Robust Online Portfolio Selection," Papers 2206.01064, arXiv.org.
    9. Bin Li & Steven C. H. Hoi, 2012. "On-Line Portfolio Selection with Moving Average Reversion," Papers 1206.4626, arXiv.org.
    10. Ting-Kam Leonard Wong, 2015. "Universal portfolios in stochastic portfolio theory," Papers 1510.02808, arXiv.org, revised Dec 2016.
    11. Shuo Sun & Rundong Wang & Bo An, 2021. "Reinforcement Learning for Quantitative Trading," Papers 2109.13851, arXiv.org.
    12. Xingyu Yang & Jin’an He & Hong Lin & Yong Zhang, 2020. "Boosting Exponential Gradient Strategy for Online Portfolio Selection: An Aggregating Experts’ Advice Method," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 231-251, January.
    13. Guo, Sini & Yu, Lean & Li, Xiang & Kar, Samarjit, 2016. "Fuzzy multi-period portfolio selection with different investment horizons," European Journal of Operational Research, Elsevier, vol. 254(3), pages 1026-1035.
    14. Chu, Gang & Zhang, Wei & Sun, Guofeng & Zhang, Xiaotao, 2019. "A new online portfolio selection algorithm based on Kalman Filter and anti-correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    15. Ottucsák György & Vajda István, 2007. "An asymptotic analysis of the mean-variance portfolio selection," Statistics & Risk Modeling, De Gruyter, vol. 25(1/2007), pages 1-24, January.
    16. Gupta, Pankaj & Mittal, Garima & Mehlawat, Mukesh Kumar, 2013. "Expected value multiobjective portfolio rebalancing model with fuzzy parameters," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 190-203.
    17. Liu, Yong-Jun & Zhang, Wei-Guo, 2015. "A multi-period fuzzy portfolio optimization model with minimum transaction lots," European Journal of Operational Research, Elsevier, vol. 242(3), pages 933-941.
    18. Seung-Hyun Moon & Yong-Hyuk Kim & Byung-Ro Moon, 2019. "Empirical investigation of state-of-the-art mean reversion strategies for equity markets," Papers 1909.04327, arXiv.org.
    19. James Chok & Geoffrey M. Vasil, 2023. "Convex optimization over a probability simplex," Papers 2305.09046, arXiv.org.
    20. Carroll, Rachael & Conlon, Thomas & Cotter, John & Salvador, Enrique, 2017. "Asset allocation with correlation: A composite trade-off," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1164-1180.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:295:y:2021:i:3:p:1074-1086. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.