🔎 📈 🐍 💰 Backtest trading strategies in Python.

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

QuantStart.com - QSTrader backtesting simulation engine.

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

An extension for Nautilus Trader

A stock backtesting engine written in Java. And a pairs trading (cointegration) strategy implementation using a bayesian kalman filter model

SimTradeLab is an open-source backtesting framework inspired by PTrade’s event-driven architecture. It features a lightweight, modular design and full syntax compatibility, enabling seamless strategy development and validation.

Extremely fast quantitative factor cleaning and backtesting library, based on Polars

Option and stock backtester / live trader

PyneCore - Pine Script Like Python Framework

Quantitative systematic trading strategy development and backtesting in Julia

Trade backtesting engine for DCA (Dollar Cost Averaging) and Grid trading strategies with technical indicator support and historical market data simulation for

Backtesting framework for modern option strategies

Hybrid Event-driven and Vectorized Strategy Backtesting Library

Sub-microsecond bare-metal execution engine with deterministic replay, lock-free order path, and hardware-timestamped latency measurement.

Python based open source quantitative trading platform development framework

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

Professional Backtesting Engine for crypto, stocks and forex

Python 开源量化框架： 覆盖“研究、回测、交易”全生命周期，构建从零到实盘的工业级量化闭环工作流。