README
TorchTrade
A machine learning framework for algorithmic trading built on TorchRL.
TorchTrade's goal is to provide accessible deployment of RL methods to trading. The framework supports various RL methodologies including online RL, offline RL, model-based RL, contrastive learning, and many more areas of reinforcement learning research. Beyond RL, TorchTrade integrates traditional trading methods such as rule-based strategies, as well as modern approaches including LLMs (both local models and frontier model integrations) as trading actors.
TorchTrade provides modular environments for both live trading with major exchanges and offline backtesting. The framework supports:
- 🎯 Multi-Timeframe Observations - Train on 1m, 5m, 15m, 1h bars simultaneously