nshen7/alpha-gfn
A deep reinforcement learning framework for generating formulaic alpha factors for quantitative investment, powered by GFlowNet, implemented in Python&PyTorch.
This project helps quantitative traders and researchers automatically generate new mathematical formulas, called alpha factors, for predicting stock trends. It takes historical market data like prices and volumes, and outputs diverse formulas that signal potential buying or selling opportunities. Quantitative investment professionals can use these formulas to inspire new trading strategies or integrate them directly into existing ones.
104 stars.
Use this if you are a quantitative trader or researcher looking for an automated way to discover novel alpha factors for stock trend prediction.
Not ideal if you need to analyze non-technical indicators or market data beyond daily frequency, as this demo focuses solely on technical indicators and daily data.
Stars
104
Forks
16
Language
Jupyter Notebook
License
—
Category
Last pushed
Jan 23, 2026
Commits (30d)
0
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