ml-quant-trading

What it is

A reproducible PyTorch research stack for cross-sectional factor research: 213 mask-aware factors, public-data validation, cost-aware backtests, auditable reports, and a preview typed portfolio-decision adapter.

The homepage listed on the repository, initial-d.github.io, puts it like this: An open-source PyTorch research stack for mask-first factor computation, limit-move contamination checks, portfolio optimization, cost-aware backtesting, and reproducible public-data validation.

Getting started

From the README:

python -m pip install mlquantx
mlquant demo

Where the decision sits

ml-quant-trading runs its own weights or its own runtime rather than calling a hosted API, so its decisions do not depend on a vendor being up or on a key being funded. The trade is that the model is now yours to keep current.

Models it references: Alpha.

How active it is

Created 2025-06-05, last pushed 2026-11-02, 102 stars and 39 forks when we read it on 2026-11-02. Everything in this category is weeks old at most, so a stale push date means something different here than it would on a mature project. Check the repository before you depend on it.