FinRL provides an open-source ecosystem that features Deep Reinforcement Learning in finance for all-level users.
About FinRL
FinRL is the first open-source framework to demonstrate the great potential of applying deep reinforcement learning in quantitative finance. We help practitioners establish the development pipeline of trading strategies using deep reinforcement learning (DRL).
FinRL Ecosystem
Deep Reinforcement Learning to Automate Trading in Quantitative Finance
- FinRL ecosystem provides a way to take advantage of large-scale financial data (market data, alternative data, indexes and labels) through GPU-acceleration techniques, reduces latency for future financial simulations.
Our projects
FinRL
Framework
A full pipeline that automatically streamlines the development of algorithmic trading strategies.
ElegantRL
Algorithm
A DRL algorithm library that is developed for researchers and practitioners with finance-oriented optimizations.
FinRL-Meta
Data-Driven
A Universe of Market Environments for Financial Reinforcement Learning.
FinRL-Podracer
Cloud-Native
A high-performance and scalable solution for RLOps in finance.
PORTFOLIO
A showcase of our works
EXPERTISE
How we can be useful for you
Check Out Our Open-Source Solutions!
AI4Finance-Foundation
E: info@ai4finance.net
AI community has accumulated an open-source code ocean over the past decade. We believe applying these intellectual and engineering properties to finance will initiate a paradigm shift from the conventional trading routine to an automated machine learning approach, even RLOps in finance.
Columbia University
E: hy2500@columbia.edu
A lot of researchers from Columbia University are collaborating with us to build an open-source community and conduct academic research.
International Digital Economy Academy
E: recruiting@idea.edu.cn
The International Digital Economy Academy (“IDEA”) is an international innovation-driven research institute that focuses on artificial intelligence (“AI”), digital economy and cutting-edge technologies.
CONTACT
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