Awesome Quant

"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

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

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.

Quant trading framework by OctoBot. Write, backtest & automate Python trading strategies like TradingView Pine Script. Work in progress.

Open-source AI trading signal engine with a public, inspectable outcome ledger. Our own signals lose money on average after modeled costs — we publish every row anyway. Multi-timeframe TA, backtester, paper trading, Telegram/Discord alerts. Self-hosted, Next.js + PostgreSQL, MIT.

AI-powered trading research platform. Test any idea on stocks, futures, and crypto with event studies, backtesting, and statistical validation. MCP server with 8 tools. pip install varrd.

AI-powered trading research platform. Test any idea on stocks, futures, and crypto with event studies, backtesting, and statistical validation. MCP server with 8 tools. pip install varrd.

Blazing fast Julia backtester.

Fast, Transparent Backtesting

Rust crate of validated, decimal-precise trading building blocks: price types, L2 order book, tick-to-OHLCV aggregation, hundreds of streaming indicators, position ledger, risk rules, Black-Scholes Greeks and a walk-forward backtester. On crates.io.

63 deterministic quant computation tools for autonomous financial agents. Options, derivatives, risk, portfolio, statistics, crypto/DeFi, macro/FX, TVM. 1,000 free calls/day — no signup.

Reference and issue mirror for @spfunctions/cli, the SimpleFunctions sf command-line interface.

Python client library to give traders, quants, and analysts access to forex macroeconomic data via the FXMacroData API.

Distributional crypto-return forecasting via Wasserstein-geodesic extrapolation in quantile-function space. WGeo family wins 12/12 (asset × horizon) cells over 6.75y walk-forward CRPS vs GARCH and classical baselines. v0.4.

Local-first backtesting engine with built-in overfitting detection. Asset-class agnostic. MCP-native.

Realistic limit-order fill simulator for options credit/debit spreads. Engine-agnostic, data-source-agnostic.

Sextant is a local Python Financial Backtest app with a Streamlit interface. The core is a strict bar-by-bar event loop (MarketEvent → SignalEvent → OrderEvent → FillEvent) — fully deterministic, with a complete JSON audit trail of every event.