#Alpha-factors
Showing 5 of 5 repositories tagged #alpha-factors, ranked by stars
Advanced Quantitative Factor Research: ML-powered stock return prediction with 72% performance improvement. Features comprehensive alpha factor library, systematic feature selection, and deep learning models (LSTM+ResNet achieving IC=0.06476).
📈This repo contains detailed notes and multiple projects implemented in Python related to AI and Finance. Follow the blog here: https://purvasingh.medium.com
A deep reinforcement learning framework for generating formulaic alpha factors for quantitative investment, powered by GFlowNet, implemented in Python&PyTorch.
Contains detailed and extensive notes on quantitative trading, leveraging NLP for finance, backtesting, alpha factor research, portfolio management and optimization.
PyTorch research stack for ML multi-factor trading: 213 factors, bias correction, portfolio optimization, and vectorized backtesting.