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Adaptive online portfolio strategy based on exponential gradient updates

Author

Listed:
  • Yong Zhang

    (Guangdong University of Technology)

  • Hong Lin

    (Guangdong University of Technology)

  • Lina Zheng

    (Guangdong University of Technology)

  • Xingyu Yang

    (Guangdong University of Technology)

Abstract

Based on the momentum principle and adaptive learning mechanism, we design online portfolio selection strategies, which are suitable for nonstationary financial market. Firstly, we propose a Moving-window-based Adaptive Exponential Gradient (MAEG) strategy, which updates the learning rate of the EG algorithm by maximizing the recent cumulative return using the price data in a fixed length moving window. Secondly, we consider a special case where all-historical price data is used to design another strategy named Adaptive Exponential Gradient (AEG). Finally, we conduct an extensive numerical analysis using real price data and the empirical results show that the performance of the proposed strategies is steadily superior to some online strategies. In addition, MAEG and AEG are able to withstand certain transaction costs, which further supports their practical applicability in trading applications.

Suggested Citation

  • Yong Zhang & Hong Lin & Lina Zheng & Xingyu Yang, 2022. "Adaptive online portfolio strategy based on exponential gradient updates," Journal of Combinatorial Optimization, Springer, vol. 43(3), pages 672-696, April.
    • Handle: RePEc:spr:jcomop:v:43:y:2022:i:3:d:10.1007_s10878-021-00800-7
    DOI: 10.1007/s10878-021-00800-7
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    References listed on IDEAS

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    1. Lo, Andrew W & MacKinlay, A Craig, 1990. "When Are Contrarian Profits Due to Stock Market Overreaction?," The Review of Financial Studies, Society for Financial Studies, vol. 3(2), pages 175-205.
    2. 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).
    3. Wenqiang Dai & Meng Zheng & Xu Chen & Zhuolin Yang, 0. "Online economic ordering problem for deteriorating items with limited price information," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-23.
    4. Alexei Gaivoronski & Fabio Stella, 2000. "Stochastic Nonstationary Optimization for Finding Universal Portfolios," Annals of Operations Research, Springer, vol. 100(1), pages 165-188, December.
    5. Xin Feng & Yinfeng Xu & Guanqun Ni & Yongwu Dai, 2018. "Online leasing problem with price fluctuations under the consumer price index," Journal of Combinatorial Optimization, Springer, vol. 36(2), pages 493-507, August.
    6. Jegadeesh, Narasimhan, 1990. "Evidence of Predictable Behavior of Security Returns," Journal of Finance, American Finance Association, vol. 45(3), pages 881-898, July.
    7. Yu, Jing-Rung & Paul Chiou, Wan-Jiun & Lee, Wen-Yi & Lin, Shun-Ji, 2020. "Portfolio models with return forecasting and transaction costs," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 118-130.
    8. Bin Li & Jialei Wang & Dingjiang Huang & Steven C. H. Hoi, 2018. "Transaction cost optimization for online portfolio selection," Quantitative Finance, Taylor & Francis Journals, vol. 18(8), pages 1411-1424, August.
    9. 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.
    10. Patrick O'Sullivan & David Edelman, 2015. "Adaptive universal portfolios," The European Journal of Finance, Taylor & Francis Journals, vol. 21(4), pages 337-351, March.
    11. Omer Berat Sezer & Mehmet Ugur Gudelek & Ahmet Murat Ozbayoglu, 2019. "Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019," Papers 1911.13288, arXiv.org.
    12. Tengfei Li & Kani Chen & Yang Feng & Zhiliang Ying, 2017. "Binary switch portfolio," Quantitative Finance, Taylor & Francis Journals, vol. 17(5), pages 763-780, May.
    13. Thomas M. Cover, 1991. "Universal Portfolios," Mathematical Finance, Wiley Blackwell, vol. 1(1), pages 1-29, January.
    14. Xing Chai & Wenhua Li & Hang Yuan & Libo Wang, 0. "Online scheduling on a single machine with linear deteriorating processing times and delivery times," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-13.
    Full references (including those not matched with items on IDEAS)

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