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"Vibe-Trading: Your Personal Trading Agent"

Python Backtesting library for trading strategies

Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.

Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).

The backtesting engine that gives you an unfair advantage. Run thousands of trading ideas before others finish one.

Free, open source, a high frequency trading and market making backtesting and trading bot, which accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades and order books(Level-2 and Level-3), with real-world crypto trading examples for Binance and Bybit

modular quant framework.

Algorithmic Trading in Python with Machine Learning

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。

Open-source Rust framework for building event-driven live-trading & backtesting systems

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

fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!

Python AutoML for Trading Systems and Sports Betting

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

An Open Source Portfolio Backtesting Engine for Everyone | 面向所有人的开源投资组合回测引擎

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.

A Python async and event driven framework for algorithmic trading, with a focus on crypto currencies.

GPU-accelerated Factors analysis library and Backtester

Python-based framework for backtesting trading strategies & analyzing financial markets [GUI :neckbeard:]

low code backtesting library utilizing pandas and technical analysis indicators

Agent-driven alpha factory — LLM autonomously designs, backtests, and submits factors to WorldQuant BRAIN

A backtester and spreadsheet library for stocks and ETFs

Quantitative systematic trading strategy development and backtesting in Julia

Self-hosted Python strategy research and Alpaca paper trading with broker reconciliation, evidence gates, and live execution disabled.

Leveraged Futures Exchange for Simulated Trading

AI-powered SDK featuring algorithmic trading, backtesting, deployment on 100+ exchanges, and multiple optimization engines.

High performance, low-latency backtesting engine for testing quantitative trading strategies on historical and live data in Rust

Python API for accessing Lake high frequency tick trades & order book data

Quantitative factor research skills for AI coding assistants

An open-source toolkit for quantitative analysis of crypto & stock markets, featuring an advanced market screener, portfolio backtester, and companion tools for the Gunbot trading bot.