OpenByteInc/QuantDinger Alternatives

Choose if you want an actively maintained all-in-one AI quant bot with local deployment and similar scope.

[🔥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

Choose if you prefer a comprehensive AI trading system with real-time data processing and risk management under MIT.

A comprehensive quantitative trading system with AI-powered analysis, real-time data processing, and advanced risk management

Choose if you need deep integration with Qlib, RD-Agent, and TradingAgents and can accept AGPL-3.0.

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。

Choose if you want a lightweight backtestable AI trading agent library with broker integration and GPL-3.0.

Backtestable AI trading agents and Python algorithmic trading strategies for stocks, options, crypto, futures, forex, SEC filings, FRED macro data, and real brokers.

Choose when you need a pure Python factor/data framework without the AI-agent layer, under MIT license.

modular quant framework.

Choose if you specifically want reinforcement-learning-based trading, not LLM multi-agent.

TradeMaster is an open-source platform for quantitative trading empowered by reinforcement learning :fire: :zap: :rainbow:

Choose if you want a full factor-mining workflow with live trading in a Chinese-focused framework.

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。

Choose if you need a mature AI research platform with strong ML model zoo and backtesting, not LLM agents.

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.

Choose if you want a battle-tested event-driven trading framework with deep broker connectivity, no AI.

基于Python的开源量化交易平台开发框架

Choose if you need a general multi-agent framework for financial apps, not a full trading stack.

ValueCell is a community-driven, multi-agent platform for financial applications.

Choose if you want an autonomous hedge-fund layer with swarm intelligence rather than a self-hosted trading OS.

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.

Choose if you want a clean framework for strategy development/deployment without the AI research layer.

Framework for quantitative trading. Complete framework for development, backtesting, and deploying automated trading algorithms and trading bots.

Choose for high-frequency, low-latency trading in C++ rather than Python/AI.

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】

Choose for a lightweight C++ integrated backtest/trading system without Python dependencies.

a light-weighted, integrated trading/backtesting system/platform（综合量化交易回测系统/平台）

Choose if you want a focused ML-trading library with backtesting/live trading and a simpler API than a full OS.

Algorithmic Trading in Python with Machine Learning

Choose if you want a Python quant system covering stocks/options/futures/BTC with ML, under GPL-3.0.

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

Choose if you want a purpose-built crypto trading bot with its own UI and strategy framework.

An advanced crypto trading bot written in Python

Choose if you want a C++-core high-speed quant framework with Python bindings.

Hikyuu Quant Framework 基于C++/Python的超高速开源量化交易研究框架，同时可基于策略部件进行资产重用，快速累积策略资产。

Choose if you need a modular event-driven backtester with data vendor/broker integrations, Apache-2.0.

Modular Python library that provides an advanced event driven backtester and a set of high quality tools for quantitative finance. Integrated with various data vendors and brokers, supports Crypto, Stocks and Futures.

Choose if you are locked into Java/Kotlin and can accept an unmaintained legacy framework.

Kotlin(Java)开源量化交易开发框架

Choose if you only need the multi-agent LLM research layer, not backtesting/live execution.

TradingAgents: Multi-Agents LLM Financial Trading Framework

Choose if you need a personal AI research agent for daily reviews, not a trading platform.

Vibe-Research: Your Personal Trading Research Agent · A股/美股/港股 的个人投研 Agent：每日复盘、资讯雷达、个股数据、板块中心、我的持仓、研究记录、回测。Vibe-Research 把数据和功能配齐，由你自己的 Agent 驱动投资研究。基于开源的 Codex Harness 打造。

Choose if you want an Elixir/Erlang real-time market data and execution toolkit, accepting staleness.

A composable, real time, market data and trade execution toolkit. Built with Elixir, runs on the Erlang virtual machine