quantlab documentation#
Version: 0.2.0
Useful links: Installation | Source repository | Issue tracker | PyPI
quantlab is a configuration-driven backend for quantitative equity research. It downloads
market data, turns it into (timestamp, symbol) panels stored as Zarr, computes factors,
trains return models, builds portfolios and backtests them, and every stage rebuilds from the
config it records.
New to quantlab? Install it and run the whole pipeline on synthetic data in ten minutes.
The pipeline stage by stage: data, universes, factors and labels, models, portfolios, backtests and the daily jobs.
Every public module, class and function, generated from the numpydoc docstrings.
The architecture, how to extend each layer, and the machinery underneath: resumable jobs, atomic writes, fingerprints, the risk model.