10 AI Trading GitHub Repos You Should Have on Your Radar
AI is moving into trading — from LLM-powered analysts to reinforcement learning and automated quant research.
If you're interested in AI + finance, these 10 open-source repos are worth exploring.
- TradingAgents
A multi-agent LLM framework that simulates a trading firm with specialized analysts, traders and risk-management agents.
🔗 https://github.com/TauricResearch/TradingAgents
- FinRL
An open-source financial reinforcement-learning framework for training AI agents on trading and portfolio-allocation tasks.
🔗 https://github.com/AI4Finance-Foundation/FinRL
- FinRL-X
An AI-native quantitative trading infrastructure combining ML, reinforcement learning, LLM-ready workflows and risk controls.
🔗 https://github.com/AI4Finance-Foundation/FinRL-Trading
- Qlib
Microsoft's open-source AI-oriented quantitative investment platform for research, modeling and strategy development.
🔗 https://github.com/microsoft/qlib
- FinGPT
An open-source financial LLM project focused on financial sentiment analysis, prediction and other finance-related AI tasks.
🔗 https://github.com/AI4Finance-Foundation/FinGPT
- NautilusTrader
A high-performance algorithmic trading platform with backtesting, live trading and infrastructure for AI trading agents.
🔗 https://github.com/nautechsystems/nautilus_trader
- OpenBB
An open-source investment research platform that brings financial data and analysis tools into one ecosystem.
🔗 https://github.com/OpenBB-finance/OpenBB
- FinMem
A research project exploring memory-augmented LLM agents for financial decision-making and trading.
🔗 https://github.com/pipiku915/FinMem-LLM-StockTrading
- FinAgent
A multimodal financial AI agent that combines financial information with visual market/chart analysis.
🔗 https://github.com/pipiku915/FinAgent
- VectorBT
A fast Python framework for quantitative research and vectorized backtesting of trading strategies.
🔗 https://github.com/polakowo/vectorbt
All open source.
AI + Finance.
Research + Trading.
Save this list — the future of quantitative trading is getting increasingly AI-native.