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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.
The research engine that gives you an unfair advantage. Run thousands of trading ideas before others finish one.
MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.
Python toolkit for quantitative finance: stock analysis, technical indicators, strategy backtesting, portfolio optimization, and financial modeling.
Statistical and Algorithmic Investing Strategies for Everyone
基于深度强化学习的开源自动因子工厂。
A comprehensive quantitative trading system with AI-powered analysis, real-time data processing, and advanced risk management
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.