Stock Portfolio Optimization Based on Reinforcement Learning

Jinglong Li ()
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Jinglong Li: Beijing International Studies University, School of economics

A chapter in Proceedings of the 2023 5th International Conference on Economic Management and Cultural Industry (ICEMCI 2023), 2024, pp 123-130 from Springer

Abstract: 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.

Keywords: Stock portfolio optimization; Reinforcement Learning; financial indicators and statistical indicators; value function (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-368-9_16

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DOI: 10.2991/978-94-6463-368-9_16

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