Algorithmic Trading Using Continuous Action Space Deep Reinforcement Learning
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Liu, Qingfu & Tao, Zhenyi & Tse, Yiuman & Wang, Chuanjie, 2022. "Stock market prediction with deep learning: The case of China," Finance Research Letters, Elsevier, vol. 46(PA).
- Aniruddha Dutta & Saket Kumar & Meheli Basu, 2020. "A Gated Recurrent Unit Approach to Bitcoin Price Prediction," JRFM, MDPI, vol. 13(2), pages 1-16, February.
- Liu, Mingxi & Li, Guowen & Li, Jianping & Zhu, Xiaoqian & Yao, Yinhong, 2021. "Forecasting the price of Bitcoin using deep learning," Finance Research Letters, Elsevier, vol. 40(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Pedro Reis & Ana Paula Serra & Jo~ao Gama, 2025. "The Role of Deep Learning in Financial Asset Management: A Systematic Review," Papers 2503.01591, arXiv.org.
- Christian Fieberg & Daniel Metko & Thorsten Poddig & Thomas Loy, 2023. "Machine learning techniques for cross-sectional equity returns’ prediction," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 289-323, March.
- Tej Bahadur Shahi & Ashish Shrestha & Arjun Neupane & William Guo, 2020. "Stock Price Forecasting with Deep Learning: A Comparative Study," Mathematics, MDPI, vol. 8(9), pages 1-15, August.
- Pawan Kumar Singh & Alok Kumar Pandey & S. C. Bose, 2023. "A new grey system approach to forecast closing price of Bitcoin, Bionic, Cardano, Dogecoin, Ethereum, XRP Cryptocurrencies," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2429-2446, June.
- Goodell, John W. & Ben Jabeur, Sami & Saâdaoui, Foued & Nasir, Muhammad Ali, 2023. "Explainable artificial intelligence modeling to forecast bitcoin prices," International Review of Financial Analysis, Elsevier, vol. 88(C).
- Sudersan Behera & Sarat Chandra Nayak & A. V. S. Pavan Kumar, 2024. "Evaluating the Performance of Metaheuristic Based Artificial Neural Networks for Cryptocurrency Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 1219-1258, August.
- Samuka Mohanty & Rajashree Dash, 2023. "A New Dual Normalization for Enhancing the Bitcoin Pricing Capability of an Optimized Low Complexity Neural Net with TOPSIS Evaluation," Mathematics, MDPI, vol. 11(5), pages 1-28, February.
- Lili Pan & Lin Wang & Qianqian Feng, 2022. "A Bibliometric Analysis of Risk Management in Foreign Direct Investment: Insights and Implications," Sustainability, MDPI, vol. 14(12), pages 1-18, June.
- Huang, Chiou-Jye & Shen, Yamin & Kuo, Ping-Huan & Chen, Yung-Hsiang, 2022. "Novel spatiotemporal feature extraction parallel deep neural network for forecasting confirmed cases of coronavirus disease 2019," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
- Guo, Wei & Liu, Qingfu & Luo, Zhidan & Tse, Yiuman, 2022. "Forecasts for international financial series with VMD algorithms," Journal of Asian Economics, Elsevier, vol. 80(C).
- Parth Daxesh Modi & Kamyar Arshi & Pertami J. Kunz & Abdelhak M. Zoubir, 2023. "A Data-driven Deep Learning Approach for Bitcoin Price Forecasting," Papers 2311.06280, arXiv.org.
- Jinghua Wang & Geoffrey M. Ngene & Yan Shi & Ann Nduati Mungai, 2023. "An Investigation of the Predictability of Uncertainty Indices on Bitcoin Returns," JRFM, MDPI, vol. 16(10), pages 1-12, October.
- Hao, Jun & Feng, Qianqian & Yuan, Jiaxin & Sun, Xiaolei & Li, Jianping, 2022. "A dynamic ensemble learning with multi-objective optimization for oil prices prediction," Resources Policy, Elsevier, vol. 79(C).
- Cakici, Nusret & Fieberg, Christian & Metko, Daniel & Zaremba, Adam, 2023. "Machine learning goes global: Cross-sectional return predictability in international stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 155(C).
- Chengying He & Yong Li & Tianqi Wang & Salman Ali Shah, 2024. "Is cryptocurrency a hedging tool during economic policy uncertainty? An empirical investigation," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
- Samuka Mohanty & Rajashree Dash, 2022. "Neural Network-Based Bitcoin Pricing Using a New Mutated Climb Monkey Algorithm with TOPSIS Analysis for Sustainable Development," Mathematics, MDPI, vol. 10(22), pages 1-23, November.
- Nagl, Maximilian, 2024. "Intricacy of cryptocurrency returns," Economics Letters, Elsevier, vol. 239(C).
- Kui Wang & Jie Wan & Gang Li & Hao Sun, 2022. "A Hybrid Algorithm-Level Ensemble Model for Imbalanced Credit Default Prediction in the Energy Industry," Energies, MDPI, vol. 15(14), pages 1-18, July.
- Ma, Tian & Sheng, Haoyun & Wang, Yuejie, 2024. "Noisy market, machine learning and fundamental momentum," Pacific-Basin Finance Journal, Elsevier, vol. 86(C).
- Liu, Qingfu & Tao, Zhenyi & Tse, Yiuman & Wang, Chuanjie, 2022. "Stock market prediction with deep learning: The case of China," Finance Research Letters, Elsevier, vol. 46(PA).
More about this item
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BIG-2022-11-07 (Big Data)
- NEP-CMP-2022-11-07 (Computational Economics)
- NEP-FMK-2022-11-07 (Financial Markets)
- NEP-MST-2022-11-07 (Market Microstructure)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2210.03469. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.