Popular GitHub Repositories for Finance Newsletters

Investment Research for Everyone, Everywhere.

Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.

Code for Machine Learning for Algorithmic Trading, 2nd edition.

FinRL: Financial Reinforcement Learning. ?

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

? A curated list of awesome LLMs & deep learning strategies & tools in financial market.

FinRobot: An Open-Source AI Agent Platform for Financial Analysis using LLMs ? ? ?

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code ?.

Algorithmic Trading in Python with Machine Learning

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

TradeMaster is an open-source platform for quantitative trading empowered by reinforcement learning :fire: :zap: :rainbow:

Using python and scikit-learn to make stock predictions

Use unsupervised and supervised learning to predict stocks

Find big moving stocks before they move using machine learning and anomaly detection

Machine Learning in Asset Management (by @firmai)

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

The 500 AI Agents Projects is a curated collection of AI agent use cases across various industries. It showcases practical applications and provides links to open-source projects for implementation, illustrating how AI agents are transforming sectors such as healthcare, finance, education, retail, and more.

Datasets, papers and books on AI & Finance.

ARCH models in Python

Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. >150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/