Refinitiv Datastream: global time-series of prices and macro series (licensed)

Licensed: not exercised here

Datastream is a paid licensed product (Refinitiv / LSEG), so it carries no provenance badge: it is not on WRDS for most institutions, and the access path below was not run in this session (no Refinitiv / LSEG 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.

Datastream is Refinitiv’s (LSEG) historical financial time-series database. It covers equities, bonds, commodities, indices, exchange rates, interest rates, and options/futures, alongside a large library of macroeconomic series across many countries, with long histories (some series run back to the 1960s and 1970s). Data is accessed by series mnemonic and datatype code. It is a standard source for international asset prices and macro series. A paper we distill uses it: Costain et al. on the term structure of interest rates.

• Cost: licensed, subscription. No free tier.
• Vendor: Refinitiv / LSEG (lineage: Thomson Reuters Datastream).
• Coverage: global, multi-asset and macro; daily, weekly, and monthly frequencies; deep history but uneven by series.

Access (when licensed)

• Refinitiv / LSEG, not WRDS. Datastream is usually reached through a Refinitiv terminal, the Datastream for Office Excel add-in, or the Datastream API / DSWS (DataStream Web Service); it is not generally reached through WRDS. Check whether your institution licenses it separately.
• Pulled by mnemonic plus datatype. Each request names a series mnemonic and a datatype code, for example RI (total-return index), P (price), or MV (market value), plus a frequency and date range.
• A terminal seat or API credentials are required. The DSWS service has Python and R clients for programmatic extraction. 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.

• Static / padded data. Datastream carries forward the last value on non-trading days and after a stock delists, producing spurious zero returns and flat stretches. Screen these out: a run of repeated identical values, or zero returns after the last live date, is padding, not data.
• Survivorship and dead stocks. Research lists and constituent lists differ, and using current index constituents introduces survivorship bias. Use the dead / research lists so delisted securities stay in the sample.
• Data errors at the extremes. There are well-documented spikes and reversals (a price that jumps and then reverts) that inflate small-stock returns. The standard Ince and Porter screens trim returns above set thresholds and delete suspicious reversals before any analysis.
• RI versus P. Use RI (return index) for total returns; P (price) excludes dividends and has its own adjustment quirks. Mixing them understates returns by the dividend component.
• Currency. Series come in local currency or a chosen currency, and the conversion / datatype must be set explicitly. Do not assume the default currency; record which one was requested.
• Mnemonics are not stable. The same economic series can have multiple codes, and codes change over time. Document the exact mnemonic, datatype, frequency, and extraction date so the extract is reproducible.
• Market-value and shares fields lag. MV and number-of-shares fields lag and are periodically restated; do not treat a recent value as final or assume point-in-time accuracy.

Reference: common datatypes

Datatype	What it holds
RI	Total-return index (price plus reinvested dividends); use for returns
P	Price (unadjusted for dividends)
MV	Market value (market capitalisation)
NOSH	Number of shares
UP	Unadjusted price
DY	Dividend yield
PE	Price-earnings ratio

Citation

Cite the provider and the database, e.g.: Refinitiv (LSEG) Datastream, accessed YYYY-MM-DD. State the exact mnemonics, datatypes, and frequency requested, and the extraction date. When you apply the standard data screens, cite Ince and Porter (2006), “Individual Equity Return Data from Thomson Datastream: Handle with Care!”, Journal of Financial Research.