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ucaiado/QLearning_Trading
Learning to trade with Q-learning reinforcement learning
What it is
A research project that applies reinforcement learning to trading using the Q-learning algorithm. An agent learns buy and sell decisions from market states, with code organised so the approach can be followed from start to finish. Researchers and developers looking for an introductory example of RL in trading can learn from it. It is a study project with a simple setup, not a strategy intended for live markets.
At a glance
Research onlyOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Beginners |
|---|---|
| Used for | Strategy research |
| Markets | US equities |
| Stack | Python |
| Learning curve | Easy to start |
| 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): 0 over the period, now 517. Gaps mean no snapshot was taken that day.
Learning to trade under the reinforcement learning framework