Awesome Quant

Financial 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.

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.

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

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

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

Probabilistic time series modeling in Python

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

modular quant framework.

150+ quantitative finance Python programs to help you gather, manipulate, and analyze stock market data

Algorithmic Trading in Python with Machine Learning

Statistical and Algorithmic Investing Strategies for Everyone

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

Repository containing notebooks of my posts on Medium

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

Rust library for quantitative finance.

Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.

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

Machine Learning in Asset Management (by @firmai)

Python AutoML for Trading Systems and Sports Betting

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

Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering

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

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

Portfolio optimization with deep learning.

Time series analysis in the `tidyverse`

Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.

Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models

Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning

Detect trend in time series, drawdown, drawdown within a constant look-back window , maximum drawdown, time underwater.

Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.

Python library for backtesting technical/mechanical strategies in the stock and currency markets

Self-hosted AI trading strategy lab — paper trading, overnight strategy tournaments, 15+ technical indicators

AI-powered SDK featuring algorithmic trading, backtesting, deployment on 100+ exchanges, and multiple optimization engines.

Self-tuning multi-agent AI trading system. 8-source signal fusion (Polymarket + Kalshi + 10 ML models incl. Kronos foundation model), Bull/Bear/Judge debate on Claude Opus 4.7, Portfolio Manager gate.

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

AI crypto trading bot with deep neural network (84.9% accuracy, 25 coins). BiLSTM + Attention trained on GPU. Bybit, Binance, OKX, Gate.io. Free cloud or self-hosted.

High-Performance Automatic Differentiation for Python

MCP server for real-time news with bias scoring, live stock/ETF/crypto data, AI options pricing, balanced news synthesis, and meme search. 10 tools, 5000+ sources, free tier.