evgps/a3c_trading
A recurrent actor-critic reinforcement learning system for algorithmic trading using TensorFlow.
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This repository implements the Asynchronous Advantage Actor-Critic (A3C) algorithm with recurrent neural networks for algorithmic trading. It provides a gym-like trading environment, an A3C training framework with TensorBoard logging, and a testing notebook. The system uses deep reinforcement learning to make trading decisions and was developed based on a peer-reviewed paper published in the Journal of Communications Technology and Electronics.
Frequently asked
- What is evgps/a3c_trading?
- A recurrent actor-critic reinforcement learning system for algorithmic trading using TensorFlow.
- Is a3c_trading open source?
- Yes — evgps/a3c_trading is an open-source project tracked on heatdrop.
- What language is a3c_trading written in?
- evgps/a3c_trading is primarily written in Jupyter Notebook.
- How popular is a3c_trading?
- evgps/a3c_trading has 437 stars on GitHub.
- Where can I find a3c_trading?
- evgps/a3c_trading is on GitHub at https://github.com/evgps/a3c_trading.