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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.
TranslatedQuantitative research - replication of brokerage financial engineering research reports
Transparent and Efficient Financial Analysis
Performance analysis of predictive (alpha) stock factors
Python toolkit for quantitative finance: stock analysis, technical indicators, strategy backtesting, portfolio optimization, and financial modeling.
Portfolio optimization with deep learning.
Technical Analysis Library for Golang
Predicts how news-driven supply-chain shocks ripple across S&P 500 stocks, with an event-study backtest and a hash-chained public prediction ledger. Built on MIT open-source SEC supply-graph code.
Do stock correlations predict the market? 66 pre-registered tests, the data, and a triple pendulum that explains why not. If you have an idea you want me to try, submit it as a PR and I will test it and get back to you.
Financial Market Intelligence MCP Server — stock quotes, technical analysis, crypto data, and portfolio insights for AI agents