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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
"Vibe-Trading: Your Personal Trading Agent"
Production-grade Rust-native trading engine with deterministic event-driven architecture
Lean Algorithmic Trading Engine by QuantConnect (Python, C#)
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
Python quantitative trading strategies including VIX Calculator, Pattern Recognition, Commodity Trading Advisor, Monte Carlo, Options Straddle, Shooting Star, London Breakout, Heikin-Ashi, Pair Trading, RSI, Bollinger Bands, Parabolic SAR, Dual Thrust, Awesome, MACD
A extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities
modular quant framework.
FinRL-X: An AI-Native Modular Infrastructure for Quantitative Trading
A Java library for technical analysis.
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
High-performance technical analysis indicators and backtesting framework in Go. Zero dependencies. ✨ See how! 👀
A light-weight deep reinforcement learning framework for portfolio management. This project explores the possibility of applying deep reinforcement learning algorithms to stock trading in a highly modular and scalable framework.
Trady is a handy library for computing technical indicators, and it targets to be an automated trading system that provides stock data feeding, indicator computing, strategy building and automatic trading. It is built based on .NET Standard 2.0.
Say It Simply, Test It Properly. Agent-powered strategy research with independent ledger checks and reproducible reports.