numeraire-dataset#
Open, reproducible data loaders and builders for the numeraire research framework. This package ships code, not data: it fetches public (and, with your own credentials, licensed) sources and cleans them into tidy, point-in-time tables the framework consumes — so the cleaning is auditable and re-runnable, and no licensed data is ever redistributed inside a wheel.
from numeraire_dataset import load_ff_factors, load_gw_view
ff = load_ff_factors() # tidy frame: date, mkt_excess, smb, hml, risk_free
view, vintage = load_gw_view(start_date="1926-07-01", end_date="2020-12-31")
# feed `view` straight into numeraire's backtest; `vintage` stamps the run's provenance
The *_view helpers return a numeraire TimeSeriesView together with a
data_vintage stamp, so a downstream result can always trace back to the exact snapshot it was built
from.
Two layers#
- Sources
tidyfinance-backed loaders for standard sources (Fama–French, Goyal–Welch, and more) — thin functions returning tidy frames, with an optional point-in-time view helper that bridges into numeraire.
- Builders
self-built ETL for what tidyfinance does not cover — a vintage-aware FRED-MD builder (reference period × vintage × series, with stationarity transforms applied at build time) and, with your own credentials, WRDS panels.
Where to go next#
Installation — install and the optional extras.
User guide — the sources loaders and the FRED-MD builder, end to end.
Data zones: raw → clean → view (design) — the raw → clean → view lifecycle behind reproducible provenance.
API reference — the full API reference.