Transaction-aware inverse reinforcement learning for trading in stock markets
Author:
Funder
Research Services and Knowledge Transfer Office, University of Macau
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-023-04959-w.pdf
Reference40 articles.
1. Mariani MC, Florescu I (2019) Quantitative Finance. John Wiley & Sons, London
2. Sutton RS (2020) Sutton & barto book: reinforcement learning: an introduction. In: A Bradford Book. MIT Press Cambridge, MA, London
3. Liu X-Y, Yang H, Gao J, Wang CD (2021) Finrl: deep reinforcement learning framework to automate trading in quantitative finance. In: Proceedings of the second ACM international conference on AI in finance, pp 1–9
4. Li Z, Liu X-Y, Zheng J, Wang Z, Walid A, Guo J (2021) Finrl-podracer: high performance and scalable deep reinforcement learning for quantitative finance. In: Proceedings of the second ACM international conference on AI in finance, pp 1–9
5. Wu X, Chen H, Wang J, Troiano L, Loia V, Fujita H (2020) Adaptive stock trading strategies with deep reinforcement learning methods. Information Sciences 538:142–158. https://doi.org/10.1016/j.ins.2020.05.066
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