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.
Howtrader: A crypto quant framework for developing, backtesting, and executing your own trading strategies. Seamlessly integrates with TradingView and other third-party signals. Simply send a post request to automate trading and order placement. Supports Binance and Okex exchanges.
A curated list of awesome resources for quantitative investment and trading strategies focusing on artificial intelligence and machine learning applications in finance.
Python-based quant trading research project for short-term reversal option setups, universe selection, staged-entry backtesting, and live paper trading.
Cookiy AI Skill for AI agents (Claude, Codex, Cursor, OpenClaw) — end-to-end user research: AI interviews, synthetic users, quant surveys, participant recruitment.
宽宝 QuantBuddy: 一整套面向Agent Invesment投资研究与决策的底层设施与能力的调用skill, 覆盖A股/港股/美股/期货/宏观/ETF的量化分析与计算。支持行情、估值、财务查询、选股筛选、因子计算、策略回测。A complete infrastructure for Agent based investment analysis and decision through skill calling. Including quant skill for A-share, HK & US stocks/futures/ETF/macro — market data, fundamentals, screening, factor & backtest.
Quant infrastructure for AI agents — a free, open-source desktop workspace for macOS and Windows where your Claude Code or Codex turns a trading idea into a backtested strategy and runs it live.