TensorTrade
An open-source Python framework for building, training, and evaluating reinforcement learning agents for algorithmic trading.
What is TensorTrade?
TensorTrade is an open-source Python framework for building, training, and evaluating reinforcement learning agents for algorithmic trading. It solves the problem of creating and testing custom trading systems by providing modular components like environments, action schemes, and reward functions that simulate realistic trading conditions. The framework includes research-backed insights and integrates with tools like Ray RLlib for distributed training.
Quantitative researchers, data scientists, and developers interested in applying reinforcement learning to financial markets and algorithmic trading. It's also suitable for students and hobbyists exploring the intersection of AI and finance.
Developers choose TensorTrade for its modular, composable architecture that simplifies building custom trading agents, its integration with powerful RL libraries like Ray RLlib, and its comprehensive tutorials and research findings that guide effective implementation and avoid common pitfalls.
Overview
An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.
Use Cases
Best For
- Researchers experimenting with reinforcement learning in financial markets
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