🔎 📈 🐍 💰 Backtest trading strategies in Python.
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Updated
Dec 20, 2025 - Python
🔎 📈 🐍 💰 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
Backtesting and Trading Bots Made Easy for Crypto, Stocks, Options, Futures, FOREX and more. Lumibot also makes it very easy to run and backtest agentic AI trading strategies in a safer way.
A stock backtesting engine written in Java. And a pairs trading (cointegration) strategy implementation using a bayesian kalman filter model
Option and stock backtester / live trader
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.
A fork of Nautilus Trader with custom Polymarket and Kalshi adapters for backtesting
Quantitative systematic trading strategy development and backtesting in Julia
Hybrid Event-driven and Vectorized Strategy Backtesting Library
PyneCore - Pine Script Like Python Framework
Python based open source quantitative trading platform development framework
Sub-microsecond bare-metal execution engine with deterministic replay, lock-free order path, and hardware-timestamped latency measurement.
High-performance quantitative factor cleaning and backtesting library
Professional Backtesting Engine for crypto, stocks and forex
A Black-Scholes-based options backtesting simulator
backtrader documentation
High performance, low-latency backtesting engine for testing quantitative trading strategies on historical and live data in Rust
AI-powered SDK featuring algorithmic trading, backtesting, deployment on 100+ exchanges, and multiple optimization engines.
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