quantitative trading / algorithmic trading platform
VeighNa is an open-source Python framework for developing quantitative trading systems, providing modular components for strategy backtesting, live trading gateways, risk management, and data recording.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
AI/LLM-driven all-in-one quant research/trading platform; choose for auto-generated strategies and local AI integration rather than a modular event-driven framework.
[🔥updating ...] AI 自动量化交易机器人(完全本地部署) AI-powered Quantitative Investment Research Platform. 📃 online docs: https://ufund-me.github.io/Qbot ✨ :news: qbot-mini: https://github.com/Charmve/iQuant
AI multi-agent quant trading platform with backtesting/live trading; use if you want an AI-agent-based workflow instead of vnpy's modular framework.
AI quantitative trading platform for crypto, stocks, and forex with backtesting, live trading, market data, and multi-agent research.vibe-trading ,trading-agents,ai-trader,ai-trading
Reinforcement-learning-focused quant trading platform; choose for RL research rather than event-driven trading systems.
TradeMaster is an open-source platform for quantitative trading empowered by reinforcement learning :fire: :zap: :rainbow:
All-in-one quant framework with factor mining/ML; use if you want an integrated research-to-live workflow rather than vnpy's open modular system.
FinHack®，一个易于拓展的量化金融框架，它在当前版本中集成了数据采集、因子计算、因子挖掘、因子分析、机器学习、策略编写、量化回测、实盘接入等全流程的量化投研工作。
AI-oriented quant research platform strong in ML modeling; choose for research/backtest focus, not live trading execution.
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.
Modular quant framework with data processing; choose if you prefer a lightweight data-centric framework over vnpy's trading-centric one.
modular quant framework.
Integrated C++ trading/backtesting system; choose for C++ performance or embeddability instead of Python.
a light-weighted, integrated trading/backtesting system/platform（综合量化交易回测系统/平台）
Kotlin/Java quant trading development framework; choose if you want JVM-language trading stack.
Kotlin(Java)开源量化交易开发框架
AI-native multi-market quant trading platform integrating Qlib/agents; choose for deep AI-factor integration and 7x24 sentiment analysis.
QuantMind（量化大脑）开源版是一款面向个人开发者与投研团队的 AI 原生多市场量化交易平台。深度集成微软 Qlib、RD-Agent 因子演化与 TradingAgents 多智能体投研，提供从 300+ 维因子挖掘、13 种机器学习与深度学习模型工场、Optuna 自动调参、Qlib 高性能回测、截面批量推理、7x24 实时舆情情绪分析，到通达信深度联动（板块推送/预警雷达/闪电下单）与实盘模拟交易的完整闭环。全面支持 A股、港股、美股、期货及区块链。系统采用 Docker Compose 一键私有化部署，数据与模型完全本地化，保障策略隐私，功能零门槛无限制。
High-frequency C++ trading platform; choose for ultra-low-latency HFT, not general Python quant.
高频量化交易平台 C++ Trade Platform for quant developer 【浮生着甚苦奔忙，量化之路阻且长。 行行代码凝心血，十年辛苦不寻常】
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
Older Python quant framework for stock trading; choose if you want a simpler historical codebase, but it is no longer actively maintained.
quant framework for stock
Does the same job, but ships as an app. Useful to a person, not swappable into a codebase.
Self-contained autonomous hedge fund app with swarm AI agents; use as an end-user tool, not a library to integrate.
Build your autonomous hedge fund in minutes. AutoHedge harnesses the power of swarm intelligence and AI agents to automate market analysis, risk management, and trade execution.
These projects were analysed and named vnpy among their alternatives. The relationship is not symmetric — how vnpy rates them is a separate judgement, made when vnpy is analysed in its own right.
calls vnpy “choose for live trading and broker connectivity, whereas Qlib focuses on research and backtesting”
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.
calls vnpy “Live-trading platform/framework especially for China markets; choose it when execution matters more than research terminal features.”
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.
calls vnpy “choose it when you need a production-grade, broker-connectable trading execution framework rather than an AI research platform.”
[🔥updating ...] AI 自动量化交易机器人(完全本地部署) AI-powered Quantitative Investment Research Platform. 📃 online docs: https://ufund-me.github.io/Qbot ✨ :news: qbot-mini: https://github.com/Charmve/iQuant
calls vnpy “choose if you need robust live trading connectivity and an event-driven architecture for brokerage integration, whereas abu is more research-oriented.”
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
calls vnpy “Choose if you want a battle-tested event-driven trading framework with deep broker connectivity, no AI.”
AI quantitative trading platform for crypto, stocks, and forex with backtesting, live trading, market data, and multi-agent research.vibe-trading ,trading-agents,ai-trader,ai-trading
calls vnpy “Choose if you need a mature, extensible event-driven quant trading framework in Python.”
ValueCell is a community-driven, multi-agent platform for financial applications.
calls vnpy “Choose for a production-style trading platform with extensive exchange/broker support, if you're willing to handle its complexity.”
An advanced crypto trading bot written in Python