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A Portfolio Model with Risk Control Policy Based on Deep Reinforcement Learning

Author

Listed:
  • Caiyu Jiang

    (School of Science, Wuhan University of Technology, Wuhan 430070, China)

  • Jianhua Wang

    (School of Science, Wuhan University of Technology, Wuhan 430070, China)

Abstract

It was shown that deep reinforcement learning (DRL) has the potential to solve portfolio management problems in recent years. The Twin Delayed Deep Deterministic policy gradient algorithm (TD3) is an actor-critic method, a typical DRL method in continuous action space. Despite the success of DRL in financial trading, surprisingly, most of the literature ignores the element of risk control. The research is proposed to combine long- and short-term risk (LSTR) control with the TD3 algorithm to build a portfolio model with risk management capabilities. Using Chinese stock data from the Shanghai Stock Exchange, we train and validate the proposed portfolio model. Performances were compared to the TD3 model without risk control. The results indicated that our proposal offers better risk control and investment returns.

Suggested Citation

  • Caiyu Jiang & Jianhua Wang, 2022. "A Portfolio Model with Risk Control Policy Based on Deep Reinforcement Learning," Mathematics, MDPI, vol. 11(1), pages 1-16, December.
    • Handle: RePEc:gam:jmathe:v:11:y:2022:i:1:p:19-:d:1009624
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    References listed on IDEAS

    as
    1. Esther Mohr & Robert Dochow, 2017. "Risk management strategies for finding universal portfolios," Annals of Operations Research, Springer, vol. 256(1), pages 129-147, September.
    2. Francesco Bertoluzzo & Marco Corazza, 2012. "Reinforcement Learning for automatic financial trading: Introduction and some applications," Working Papers 2012:33, Department of Economics, University of Venice "Ca' Foscari", revised 2012.
    3. Huang, Xiaoxia, 2008. "Portfolio selection with a new definition of risk," European Journal of Operational Research, Elsevier, vol. 186(1), pages 351-357, April.
    4. 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.
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    Cited by:

    1. Yuling Huang & Kai Cui & Yunlin Song & Zongren Chen, 2023. "A Multi-Scaling Reinforcement Learning Trading System Based on Multi-Scaling Convolutional Neural Networks," Mathematics, MDPI, vol. 11(11), pages 1-19, May.

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