Awesome Quant

Financial data platform for analysts, quants and AI agents.

Free, open source crypto trading bot

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

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.

The fundamental package for scientific computing with Python.

Production-grade Rust-native trading engine with deterministic event-driven architecture

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

FinRL®: Financial Reinforcement Learning. 🔥

SciPy library main repository

A computer algebra system written in pure Python

"Vibe-Trading: Your Personal Trading Agent"

Statsmodels: statistical modeling and econometrics in Python

Python toolkit for quantitative finance

Bayesian Modeling and Probabilistic Programming in Python

Automatic extraction of relevant features from time series:

An advanced crypto trading bot written in Python

The backtesting engine that gives you an unfair advantage. Run thousands of trading ideas before others finish one.

This is a database of 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets.

Portfolio analytics for quants, written in Python

Free open source crypto trading bot to automate AI, Grid, DCA and TradingView strategies on Binance, Hyperliquid and 15+ exchanges, with a simple interface.

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

Probabilistic time series modeling in Python

Visualizer for pandas data structures

modular quant framework.

Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians)

Algorithmic Trading in Python with Machine Learning

QuantStart.com - QSTrader backtesting simulation engine.

xlwings is a Python library that makes it easy to call Python from Excel and vice versa. It works with Excel on Windows and macOS as well as with Google Sheets and Excel on the web.

Systematic Trading in python

Extract data from a wide range of Internet sources into a pandas DataFrame.

A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.

bt - flexible backtesting for Python

ffn - a financial function library for Python

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

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

Common financial technical indicators implemented in Pandas.

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

CCXT for prediction markets. PMXT is a unified API for trading on Polymarket, Kalshi, and more.

Python client for Alpaca's trade API

Financial Data Extraction from Investing.com with Python

Zipline, a Pythonic Algorithmic Trading Library

A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.

Backtestable AI trading agents and Python algorithmic trading strategies for stocks, options, crypto, futures, forex, SEC filings, FRED macro data, and real brokers.

ARCH models in Python

Financial data reader

Finviz analysis python library.

A TD Ameritrade API client for Python. Includes historical data for equities and ETFs, options chains, streaming order book data, complex order construction, and more.

Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.

Portfolio optimization with deep learning.

Exchange calendars to use with pandas for trading applications