Trading Economics - Aluminum commodity page

One quote, thirty-seven years, thirteen fields. Trading Economics maintains a commodity page for aluminum that publishes a single current price in USD per tonne alongside the change versus the prior session, the trailing one-month and one-year percentage moves, the series' all-time high (4,103.00, set in March 2022) and all-time low (1,022.70), and model-based forecast targets for the end of the current quarter and twelve months out. Underneath sit roughly 9,500 daily observations running from October 1989 through August 2026. Two things make this series more useful than a bare price feed. First, the quotes are described by the publisher as composites built from over-the-counter and contract-for-difference instruments, so the number tracks the global metal rather than one exchange floor. Second, every row carries its own change arithmetic - day, month and year - already computed, which removes the join work most teams do by hand. A companion table repeats the identical quote fields for related commodities, including Scrap Aluminum, so primary-versus-scrap spreads read straight off adjacent rows. Get a sample of this dataset to see the full row set against your own aluminum data hub benchmarks.

Three consecutive rows from the cross-commodity table, reproduced verbatim - one flat record per commodity, no nesting:

Commodity: Aluminum         Price: 3224.50   Day: +37.00   Month: +1.06%   Year: +22.95%   Date: Aug/21
Commodity: Scrap Aluminum   Price: 2526.50   Day:  -7.71   Month: -0.30%   Year:  +8.06%   Date: Aug/20
Commodity: Lead             Price: 1911.83   Day:  +6.83   Month: +0.36%   Year:  +0.68%   Date: Aug/21

Read the spread off the first two lines: primary aluminum at 3,224.50 against scrap at 2,526.50 puts the premium at 698.00 USD per tonne, or roughly 28 percent over scrap, on the same quoting convention. Note the type discipline already visible here - Day arrives as an absolute USD figure while Month and Year arrive as percentage strings, and Date renders as month/day (Aug/21) rather than a full calendar date.

Thirteen fields, each with a verified definition and a worked example drawn from the live quote - the complete schema for every row. Nothing below is inferred: field semantics were checked against the source card and recorded at verification confidence. Five fields carry the quote itself and its change arithmetic (Price, Day, Month, Year, Date), five carry the summary statistics block (Actual, Previous, Highest, Lowest, Dates), and three carry series metadata (Unit, Frequency, temporalCoverage). Fields beyond these thirteen - for example extended forecast detail or additional commodity columns - are not part of the documented core and ship as additional fields on request, scoped to your use case before delivery.

Geography - world. The series is a global aluminum benchmark whose underlying quotes are linked to the major metal venues (LME, COMEX, SHFE) through OTC and CFD instruments rather than any single national market, so one USD-per-tonne number stands in for worldwide pricing. Temporal - daily observations from 1989-10-10 to the current date, about 9,500 trading days in total, expressed in the machine-readable form 1989-10-10/2026-08-21. That span crosses four decades of capacity cycles, China's demand surge and the 2021-22 energy squeeze that produced the 4,103.00 record high. Granularity - one quote per trading day. There is no intraday dimension to manage and no gaps to interpolate across sessions, which keeps backtests and chart joins deterministic.

API, files, or your warehouse. Daily, weekly, or hourly.

• Procurement and hedging desks - the Actual versus Previous pair plus the quarter-end and twelve-month model targets give a defensible basis for forward-buying windows on smelter contracts and pass-through clauses.
• Quantitative backtesting - a daily series reaching back to October 1989 supports strategy tests across multiple metal cycles with one consistent USD/tonne convention and no vendor-format drift mid-series.
• Relative-value and recycling studies - the companion rows for Scrap Aluminum and other metals share the identical thirteen-field schema, so primary-to-scrap spreads compute as a two-line subtraction.
• Macro and dashboard work - Highest (4,103.00, March 2022), Lowest (1,022.70) and the trailing change fields arrive precomputed, which is why the series drops into executive dashboards without a transformation layer.

Investors and quants get a four-decade daily benchmark with change fields already derived - see the data scientists use cases for modeling patterns. Market researchers and consultants get quotable extremes and forecast targets for metals commentary. Competitive-intel and product teams tracking raw-material exposure get a stable external yardstick - the competitive intel product teams use cases outline the monitoring pattern. Developers building data products get a fixed thirteen-column schema where every field is typed and exemplified - the developers builders use cases cover integration shapes.

Four notes worth reading before you wire this in. First, the quotes are a composite of OTC and CFD instruments, not an exchange settlement print - expect small, persistent differences from LME official closing prices, and pick one convention and hold it across your whole history. Second, Date is rendered as month/day (Aug/21), so reconstruct full dates from the observation timestamp when stitching a continuous series. Third, Month and Year arrive as percentage strings (22.95%) while Day is an absolute USD figure - normalize types before any arithmetic. Fourth, forecast cells are model outputs from the publisher, categorically different from observed quotes, so warehouse them in their own columns. On quality: Datadory scores this record 6 out of 10 on its documentation-and-reliability rubric, with all thirteen field definitions verified against the source card and a live sample row available above. Request a sample and we will send real rows from the dates you nominate, so you can test type handling against your own pipeline before committing.