Global Financial Data (GFD): long-run cross-country series (licensed)

Licensed: not exercised here

Global Financial Data is a paid licensed product (Global Financial Data, Inc.), so it carries no provenance badge: the access path below was not run in this session (no GFD credentials were available). The page documents the access route and the gotchas; treat it as unverified until someone exercises it through a licensed account. This is the honest grade under the institute’s Verified discipline.

Global Financial Data (GFD) is a commercial database of long-run historical financial and macroeconomic series: equity price and total-return indices, bond yields, exchange rates, commodity prices, interest rates, and macro aggregates, assembled for many countries with histories reaching back centuries in some series. Its distinguishing feature is long-run cross-country coverage: it stitches together historical sources to extend series far before the start of modern machine-readable feeds, which makes it a standard input for survivorship-bias and very-long-horizon return studies. A paper we distill uses it: Van Binsbergen, Hua, Peeters & Wachter draw on annual total returns for 55 countries from 1920 to 2020 to estimate survivorship-corrected crash risk.

• Cost: licensed, subscription. No free tier.
• Vendor: Global Financial Data, Inc.
• Coverage: thousands of series across dozens of countries; equity, fixed income, FX, commodities, and macro, with deep historical extensions assembled from archival sources.

Access (when licensed)

• Through the GFD web platform or API. Series are pulled from the GFD Finaeon platform (web interface and an API), keyed by GFD’s own ticker/series codes. An extract is a set of series codes over a date range.
• Some series reach researchers via institutional libraries. Universities sometimes provide GFD access through a library subscription rather than a direct lab licence; check which route your institution provides.
• API credentials are required. Keep any credentials in .env, never hard-coded.

Gotchas (the ones that bite pipelines)

These are the failure modes to expect; they are documented, not verified here.

• Spliced series carry a methodology break at every join. A “long-run” series is a concatenation of underlying historical sources with different construction methods; the further back you go, the more the index reflects GFD’s splicing choices rather than a single consistent methodology. Read the series documentation before treating a multi-century series as homogeneous.
• Total-return versus price indices. GFD provides both; mixing a price index for one country with a total-return index for another silently biases cross-country return comparisons. Confirm the index type for every series in a panel.
• Currency and real-versus-nominal. Series are in native currency and mostly nominal; cross-country aggregation requires explicit FX conversion and a consistent deflator choice. Do not mix currencies or nominal-with-real series.
• Sparse and interpolated early history. Early observations can be annual, interpolated, or carried from a single archival source; apparent low volatility in the deep past may be an artifact of sparse sampling rather than calm markets.
• Country composition changes over time. Borders, market existence, and index membership shift across a century-long sample; a “country” series can reflect different underlying markets at different dates. Treat the country panel as unbalanced and document entry/exit.
• Provenance is the value and the risk. Because the long histories come from archival reconstruction, cross-check GFD against an independent source (e.g. official statistics or another historical compilation) when a single series drives a result.

Reference: representative series families

Family	Examples
Equity indices	Country total-return and price indices, long-run composites
Fixed income	Government bond yields, bill rates, long-term interest rates
FX	Bilateral exchange rates, long-run currency series
Commodities	Gold, oil, agricultural and metal price histories
Macro	CPI, GDP, population, and other long-run aggregates

Series are keyed by GFD codes; pull the specific codes you need, record the index type (price vs. total return), and note the historical splice points.

Citation

Cite the provider and database, e.g.: Global Financial Data (GFD), accessed YYYY-MM-DD. State the series codes used, the index type, the currency, and the date range so the sample is reproducible.