Ranked by Attention Score: stars gained over the last 7 complete days
20 repositories by Attention Score · Oct 27, 2026 – Nov 2, 2026 (UTC)
LLM 驱动的多市场股票智能分析系统：多源行情、实时新闻、决策看板与自动推送，支持零成本定时运行。 LLM-powered multi-market stock analysis system with multi-source market data, real-time news, decision dashboard, automated notifications, and cost-free scheduled runs.
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.
基于Python的开源量化交易平台开发框架
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
AKShare is an elegant and simple financial data interface library for Python, built for human beings! 开源财经数据接口库
阿布量化交易系统(股票，期权，期货，比特币，机器学习) 基于python的开源量化交易，量化投资架构
A股行情分析与AI智能投研智能体：股票分析、量化交易分析、盘后复盘桌面工作台——easy stock
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 vector index built on TurboQuant, written in Rust with Python bindings
Zipline, a Pythonic Algorithmic Trading Library
QUANTAXIS 支持任务调度 分布式部署的 股票/期货/期权 数据/回测/模拟/交易/可视化/多账户 纯本地量化解决方案
A curated list of practical financial machine learning tools and applications.
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 extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities
Open Source Algorithmic Trading Engine
modular quant framework.
Go's answer to pandas + scikit-learn: a batteries-included data analysis library with dataframes, statistics, machine learning, quant, and GPU acceleration. Run Python with seamless two-way variable sharing, or explore data straight from the Insyra CLI.
AI-powered SDK featuring algorithmic trading, backtesting, deployment on 100+ exchanges, and multiple optimization engines.
Streaming-first technical indicators with a Rust core: native Python, Node.js and WebAssembly bindings plus a C ABI hub for C, C++, C#, Go, Java and R. 514 indicators, O(1) per-tick updates, no system dependencies. Drop-in TA-Lib replacement.