FinRL
An open-source framework for applying deep reinforcement learning to quantitative finance, featuring a train-test-trade pipeline for stock and crypto trading.
What is FinRL?
FinRL is an open-source framework that applies deep reinforcement learning to quantitative finance. It provides a structured pipeline for developing, training, and backtesting automated trading agents on financial data, solving the problem of creating adaptive, data-driven trading strategies.
Students, researchers, and developers interested in learning about or prototyping financial reinforcement learning strategies for stocks, cryptocurrencies, and portfolio management.
Developers choose FinRL for its status as the first open-source framework in this domain, its comprehensive educational resources, and its integrated workflow that simplifies the process of going from data to a trained trading agent.
Overview
FinRL®: Financial Reinforcement Learning. 🔥
Use Cases
Best For
- Learning the fundamentals of reinforcement learning applied to finance
- Prototyping and benchmarking new DRL trading algorithms
Related Projects
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
