ClementPerroud/Gym-Trading-Env
A Gymnasium RL environment for training algorithmic trading agents on simulated stock market data.
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Gym Trading Env provides a simulation environment for stocks and trading that integrates with the Gymnasium RL framework. It enables researchers and developers to train, test, and visualize reinforcement learning agents for algorithmic trading strategies. The environment supports complex operations like short selling and margin trading, with high-performance rendering capable of displaying hundreds of thousands of candles. It also includes data downloading capabilities from multiple exchanges for easy experimental setup.
Frequently asked
- What is ClementPerroud/Gym-Trading-Env?
- A Gymnasium RL environment for training algorithmic trading agents on simulated stock market data.
- Is Gym-Trading-Env open source?
- Yes — ClementPerroud/Gym-Trading-Env is open source, released under the MIT license.
- What language is Gym-Trading-Env written in?
- ClementPerroud/Gym-Trading-Env is primarily written in Python.
- How popular is Gym-Trading-Env?
- ClementPerroud/Gym-Trading-Env has 494 stars on GitHub.
- Where can I find Gym-Trading-Env?
- ClementPerroud/Gym-Trading-Env is on GitHub at https://github.com/ClementPerroud/Gym-Trading-Env.