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ucaiado/rl_trading
Environment for training high-frequency trading agents with RL
What it is
An environment for training and evaluating high-frequency trading agents with reinforcement learning. It provides simulated market data and a trading interface so RL strategies can be prototyped. Quant researchers and developers learning how reinforcement learning applies to fast trading are the intended users. A simulation cannot capture every detail of real order books and latency, so behaviour learned here may differ in live markets.
At a glance
Research onlyOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Professional quants |
|---|---|
| Used for | Strategy research, Backtesting |
| Markets | Futures, Multi-market |
| Stack | Python |
| Learning curve | Steep learning curve |
| Practical value | Low practical value |
| Cost | Free and open source |
| Hardware | No GPU needed |
| Maintenance | No commits in over six months |
GitHub stars, last 30 days
Daily snapshots since 2026-09-28 (up to 30 days): +1 over the period, now 290. Gaps mean no snapshot was taken that day.
An environment to high-frequency trading agents under reinforcement learning
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