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Stock Portfolio Optimization Based on Reinforcement Learning

In: Proceedings of the 2023 5th International Conference on Economic Management and Cultural Industry (ICEMCI 2023)

Author

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  • Jinglong Li

    (Beijing International Studies University, School of economics)

Abstract

This paper made a profound study of the application of reinforcement learning in portfolio optimization, using deep learning algorithm, combine various indicators, and analyze the explanatory variables that can effectively improve portfolio risk control through multi-dimensional financial indicators and statistical indicators. Designing a reasonable and effective value function from the reward and punishment mechanism to achieve the optimization goal of income maximization and risk control, mining problems from the perspective of practice, and the research results is of great significance for portfolio management.

Suggested Citation

  • Jinglong Li, 2024. "Stock Portfolio Optimization Based on Reinforcement Learning," Advances in Economics, Business and Management Research, in: Feng-xia Cao & Satya Narayan Singh & Ahmad Jusoh & Deepanjali Mishra (ed.), Proceedings of the 2023 5th International Conference on Economic Management and Cultural Industry (ICEMCI 2023), pages 123-130, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-368-9_16
    DOI: 10.2991/978-94-6463-368-9_16
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