Reinforcement Learning in Stock Trading
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DRL has been recognized as an effective approach in quantitative finance.
“As deep reinforcement learning (DRL) has been recognized as an effective approach in quantitative finance, getting hands-on experiences is attractive to beginners.”
From FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance (2020) · cites this paper as [10]
Cites
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155 · see citing works
Deep Reinforcement Learning with Double Q-Learning
Van Hasselt, H., Guez, A., & Silver, D. (2016) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v30i1.10295 · Cited by 3,318 · see citing works
Deep Direct Reinforcement Learning for Financial Signal Representation and Trading
Deng, Y., Bao, F., Kong, Y., Ren, Z., & Dai, Q. (2017) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2016.2522401 · Cited by 822 · cited 2× · see citing works
“Several research works in using reinforcement learning have been presented [22, 6, 1] in literature.”
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Deep reinforcement learning for automated stock trading: an ensemble strategy
Yang, H., Liu, X.-Y., Zhong, S., & Walid, A. (2020) · Proceedings of the First ACM International Conference on AI in Finance · doi:10.1145/3383455.3422540 · Cited by 196 · see citing works
“The critic-only learning approach, which is the most common, solves a discrete action space problem using, for example, Deep Q-learning (DQN) and its improvements, and trains an agent on a single stock or asset [9, 12, 21].”
BackgroundFinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance
Liu, X.-Y. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3737257 · Cited by 90 · see citing works
FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance
Liu, X.-Y., Yang, H., Chen, Q., Zhang, R., Yang, L., Xiao, B., & Wang, C. (2025) · doi:10.2139/ssrn.3737859 · Cited by 51 · see citing works
“We provide commonly used ones [14] as follows: • The change of the portfolio value when action a is taken at state s and arriving at new state s [12, 44, 10, 37, 45], i.”
InfluentialFinRL-podracer: high performance and scalable deep reinforcement learning for quantitative finance
Li, Z., Liu, X.-Y., Zheng, J., Wang, Z., Walid, A., & Guo, J. (2021) · Proceedings of the Second ACM International Conference on AI in Finance · doi:10.1145/3490354.3494413 · Cited by 28 · see citing works
“Recently, many researchers provide more DRL solutions for STP tasks [3, 8, 18].”
BackgroundFinMem: A Performance-Enhanced LLM Trading Agent With Layered Memory and Character Design
Yu, Y., Li, H., Chen, Z., Jiang, Y., Li, Y., Suchow, J. W., Zhang, D., & Khashanah, K. (2025) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2025.3593370 · Cited by 23 · see citing works
“F IN M EM ’s profiling module features dynamic character settings, enabling continuous updates in domain knowledge and risk preference to adapt to volatile trading environments, thereby enhancing F IN M EM ’s capabilities.”
Background
- Authors
- Dang, Q.-V.
- Affiliations
- Industrial University of Ho Chi Minh City (VN)
- Corresponding author
- Dang, Quang-Vinh
- ORCID
- Dang, Quang-Vinh
- Venue
- Advances in Intelligent Systems and Computing
- Publisher
- Springer International Publishing
- Published
- 2019-12-20
- Pages
- 311-322
- ISSN
- 2194-5357 (ISSN-L)
- 2194-5365
- OpenAlex
- W2986670013
- Cited by
- 57
- References
- 3
- Citations by year
- 2026: 3 · 2025: 6 · 2024: 16 · 2023: 15 · 2022: 6 · 2021: 6 · 2020: 5
- FWCI
- 6.04
- Type
- conference paper
- Language
- en
- Open access
- green
- hal.science
- Licence
- other-oa
- www.springer.com/tdm (tdm)
- Locations
- Advances in intelligent systems and computing (publishedVersion)
- HAL (submittedVersion, other-oa)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Stock Market Forecasting Methods
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Markets and Investment Strategies
- Social Sciences › Business, Management and Accounting › Accounting › Financial Analysis and Corporate Governance
- Keywords
- reinforcement learning, stock trading, deep reinforcement learning, trading decision-making, stock price prediction, financial markets
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