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Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
Free and Open Source Enterprise Resource Planning (ERP)
A extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities
FinRL-X: An AI-Native Modular Infrastructure for Quantitative Trading
Bitcoin arbitrage - opportunity detector
Python library for portfolio optimization, factor model construction, and risk management built on scikit-learn
PGPortfolio: Policy Gradient Portfolio, the source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"(https://arxiv.org/pdf/1706.10059.pdf).
Portfolio optimization with deep learning.
Say It Simply, Test It Properly. Agent-powered strategy research with independent ledger checks and reproducible reports.
Financial Market Intelligence MCP Server — stock quotes, technical analysis, crypto data, and portfolio insights for AI agents
Simple, modern ETH backtesting project using Pandas/Numpy: data prep, MA signals, portfolio simulation, and result visualization.