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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

TSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非第三方官方项目

modular quant framework.

Algorithmic Trading in Python with Machine Learning

An open-source, high-performance quantitative trading framework in C++/Python focused on strategy analysis and backtesting Trading model R&D · Ultra-fast engine · Efficient backtesting

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

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

AI agents that actually place the trade. 12 brokers, real backtests, stocks options futures forex crypto and prediction markets.

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

Python AutoML for Trading Systems and Sports Betting

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 polars 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

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

Quantitative systematic trading strategy development and backtesting in Julia

Quantitative factor research skills for AI coding assistants

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.

Leveraged Futures Exchange for Simulated Trading

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