TL;DR
The first open-source framework for financial reinforcement learning, providing an end-to-end pipeline for education and research.
Key features
Provides an integrated framework for implementing and backtesting reinforcement learning algorithms in financial market environments.
Forms an ecosystem including FinRL-Meta with Gym-style market environments and benchmarks, and ElegantRL, a lightweight DRL algorithm library.
Presents a migration path to the next-generation version, FinRL-X, which has a modular infrastructure for production deployment.
When to use it
When you want to apply reinforcement learning to financial market prediction or trading strategy development.
Useful for educational and research prototyping that requires training and backtesting reinforcement learning algorithms tailored to the financial domain.