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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.
"Vibe-Trading: Your Personal Trading Agent"
Python toolkit for quantitative finance
The research engine that gives you an unfair advantage. Run thousands of trading ideas before others finish one.
Portfolio analytics for quants, written in Python
The QuantLib C++ library
TranslatedQuantitative research - replication of brokerage financial engineering research reports
Portfolio and risk analytics in Python
Financial portfolio optimization in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
High-performance TensorFlow library for quantitative finance.
Transparent and Efficient Financial Analysis
MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.
Performance analysis of predictive (alpha) stock factors
A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.
Python library for portfolio optimization, factor model construction, and risk management built on scikit-learn
MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
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).
Common financial risk and performance metrics. Used by zipline and pyfolio.
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.
Deterministic, dependency-free Chan-theory (缠论) structure engine + multi-market trading workstation (A-shares / HK / US / crypto) with teaching chart annotations and a mobile PWA.
Go library containing a collection of financial functions for time value of money (annuities), cash flow, interest rate conversions, bonds and depreciation calculations.
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.