Awesome Quant

Open Data Platform for analysts, quants and AI agents.

Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.

"Vibe-Trading: Your Personal Trading Agent"

FinceptTerminal is a modern finance application offering advanced market analytics, investment research, and economic data tools, designed for interactive exploration and data-driven decision-making in a user-friendly environment.

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

Python wrapper for TA-Lib (http://ta-lib.org/).

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.

An advanced crypto trading bot written in Python

Portfolio analytics for quants, written in Python

The QuantLib C++ library

Financial portfolio optimization in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

High-performance TensorFlow library for quantitative finance.

MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

Portfolio Optimization in Python

modular quant framework.

Python toolkit for quantitative finance: stock analysis, technical indicators, strategy backtesting, portfolio optimization, and financial modeling.

Algorithmic Trading in Python with Machine Learning

ArcticDB is a high performance, serverless DataFrame database built for the Python Data Science ecosystem.

Python library for portfolio optimization built on top of scikit-learn

:boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling

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

QTPyLib, Pythonic Algorithmic Trading

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.

Various Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau

Rust library for quantitative finance.

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

Machine Learning in Asset Management (by @firmai)

Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy

A Python-based development platform for automated trading systems - from backtesting to optimisation to livetrading.

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.

Open source analytics and market risk library from OpenGamma

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

A Python library for mathematical finance

Quantitative Finance tools

Mathematical Finance Library: Algorithms and methodologies related to mathematical finance.

A composable, real time, market data and trade execution toolkit. Built with Elixir, runs on the Erlang virtual machine

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

Open Source Algorithmic Trading Engine

QLNet C# Library

Python framework for quantitative financial analysis and trading algorithms on decentralised exchanges

Entropy Pooling views and stress testing combined with Conditional Value-at-Risk (CVaR) portfolio optimization in Python.

Vectorized backtester and trading engine for QuantRocket

Prediction-market trading engine — Wang Transform pricing on 291K+ contracts; paper-traded across Kalshi · Polymarket · Solana DFlow (Jito bundles) · 633 tests

The fastest way from backtest to live trading.

Quant Option Pricing - Exotic/Vanilla: Barrier, Asian, European, American, Parisian, Lookback, Cliquet, Variance Swap, Swing, Forward Starting, Step, Fader

A JavaScript library to allocate and optimize financial portfolios.

Repo for code examples in Quantitative Finance with Python (1st edition) by Chris Kelliher