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Competitive Online Strategy Based on Improved Exponential Gradient Expert and Aggregating Method

Author

Listed:
  • Yong Zhang

    (Guangdong University of Technology)

  • Jiahao Li

    (Guangdong University of Technology)

  • Xingyu Yang

    (Guangdong University of Technology)

  • Jianliang Zhang

    (Guangdong University of Technology)

Abstract

In recent years, online portfolio selection (OLPS) has received more and more attention from quantitative investment and artificial intelligence communities. This paper first improves a classic OLPS strategy Exponential Gradient (EG) (Helmbold in MF 8:325–347, 1998) by fully exploiting multi-period price information via the $$L_{1}$$ L 1 -median estimator, and further designs a novel strategy named Aggregating Improved Exponential Gradient (AIEG) by using Weak Aggregating Algorithm (WAA) to aggregate an infinite number of Improved EG (IEG) expert advice. The universality of the proposed strategy is proved. This paper empirically evaluates the proposed strategy through a wide range of experiments. Promising empirical results verify that the proposed AIEG strategy performs well in terms of different aspects and can resist reasonable transaction costs.

Suggested Citation

  • Yong Zhang & Jiahao Li & Xingyu Yang & Jianliang Zhang, 2024. "Competitive Online Strategy Based on Improved Exponential Gradient Expert and Aggregating Method," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 789-814, August.
    • Handle: RePEc:kap:compec:v:64:y:2024:i:2:d:10.1007_s10614-023-10430-2
    DOI: 10.1007/s10614-023-10430-2
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    References listed on IDEAS

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    1. Xingyu Yang & Jin'an He & Yong Zhang, 2022. "Aggregating exponential gradient expert advice for online portfolio selection," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(3), pages 587-597, March.
    2. Alexei Gaivoronski & Fabio Stella, 2000. "Stochastic Nonstationary Optimization for Finding Universal Portfolios," Annals of Operations Research, Springer, vol. 100(1), pages 165-188, December.
    3. 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.
    4. Suleyman Basak & Georgy Chabakauri, 2010. "Dynamic Mean-Variance Asset Allocation," The Review of Financial Studies, Society for Financial Studies, vol. 23(8), pages 2970-3016, August.
    5. Patrick O'Sullivan & David Edelman, 2015. "Adaptive universal portfolios," The European Journal of Finance, Taylor & Francis Journals, vol. 21(4), pages 337-351, March.
    6. 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.
    7. 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.
    8. Thomas M. Cover, 1991. "Universal Portfolios," Mathematical Finance, Wiley Blackwell, vol. 1(1), pages 1-29, January.
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