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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.
TranslatedAn open-source quantitative trading platform development framework based on Python
FinceptTerminal is a modern finance application offering advanced market analytics, investment research, and economic data tools, designed for interactive exploration and data-driven decision-making in a user-friendly environment.
Translated[🔥updating ...] AI automated quantitative trading robot (fully local deployment) AI-powered Quantitative Investment Research Platform. 📃 online docs: https://ufund-me.github.io/Qbot ✨ :news: qbot-mini: https://github.com/Charmve/iQuant
ValueCell is a community-driven, multi-agent platform for financial applications.
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
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
A composable, real time, market data and trade execution toolkit. Built with Elixir, runs on the Erlang virtual machine
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.