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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.

TranslatedA-share data for AI agents: K-lines, ticks, reports, fund flow, news, financials, filings, options, macro, futures, events, convertibles | 15 layers·87 endpoints·34 sources. Full-stack A-share data toolkit: market quotes and K-lines · same-day tick-by-tick trades · research reports · signals · capital flow · news · financials · announcements · limit-up board trading (打板) · ETF options · public sentiment · macro and interest rates · futures and block trades (including Dalian Commodity Exchange daily K-lines) · event-driven · convertible bonds | No API key needed except for iwencai

  • a-share
  • ai-agent
  • ai-skill
  • china-stocks

A股多Agent投研框架 — 适配A股数据源(龙虎榜/游资/解禁等),7位分析师基于A股规则的辩论决策,基于TradingAgents深度改造,适配大A。A-share multi-agent investment research framework — 7 AI analysts, bull/bear debate, risk assessment。

A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.

  • risk
  • pricing
  • risk-management
  • asset-allocation

Translated知策 (Zhice, "know strategy") | AI investment research and strategy experiment workbench: view markets and news, compare strategy judgments; organize investment documents into knowledge backed by source-text evidence, form rules through manual confirmation, screen candidates, and verify them in independent simulated accounts.