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What each registered US futures commission merchant holds, monthly, from the Commodity Futures Trading Commission: adjusted net capital and the excess over the regulatory minimum, customers' assets in segregation and the excess above what is required, the Part 30 secured amount for foreign futures, and cleared-swap customer collateral.
Customers' assets in segregation is client money sitting in a broker's futures business, so this is a monthly, firm-level read on client balances at Interactive Brokers, Schwab's futures arm, StoneX and Marex weeks before any of them files a 10-Q.
Excess net capital is the cushion over the regulatory minimum, and it is where a firm under strain shows first.
Available Data Points:
- Period Date: The period the value describes — what the number is about (the valid clock).
- Published At: When the value first became knowable — when the publisher released it (the knowledge clock). Filter on this for anything where look-ahead bias would matter.
- Value: The numeric value, where the series has one.
- Value Text: The textual value, for categorical series such as a trial's status or phase.
- Unit: Unit of the value, e.g.
vehicles,percent,USD. - Value Type:
number,percent,currency,countortext. - Frequency: How often the publisher releases the series.
- Market: The market the reading describes — an ISO-3166 alpha-2 code (
DE), a sub-national one (US-CA), a supranational aggregate (EA,EU) orGLOBAL. - Series Slug: Which series the reading belongs to. Unique within a publisher, not globally.
- Series Name: Human-readable name of the series.
- Source Slug: Publisher/feed identifier, e.g.
kba_registrations. - Source Name: Human-readable name of the publisher or feed.
- Publisher: Who publishes the underlying data.
- Entity Ref: The publisher's own identifier for what the reading is about — a manufacturer name, a securitisation trust, a reactor unit, a country code. Kept so any value can be traced back to the row it was parsed from.
Coverage
About 73 firms, monthly, back to January 2016. The filing entity is a broker subsidiary rather than the listed group, and roughly a dozen firms belong to a listed parent; the rest are private, foreign-owned or subsidiaries of banks listed elsewhere and stay unmapped on purpose. The CFTC does not revise a month once published.
What to look for
Segregated customer assets are a flow signal: rising balances at a retail-facing broker mean funded accounts a quarter before the earnings call, and a fall not matched across the peer group is share loss rather than a market move.
Excess net capital matters most when it shrinks. A firm letting it run down is either growing faster than it retains earnings or absorbing losses.
Two dates on every reading, and the difference is the edge
periodDate is what the number is about. publishedAt is when it first became knowable. The gap between them is the whole point of alternative data — and it is also the trap. A Form 10-D describing July is filed in mid-August, so a backtest that treats the period as the knowledge date reads a document six weeks before it existed.
from_date and to_date filter on periodDate, because that is the axis you plot against. Join on publishedAt when you are joining against returns.
Filtering: one market or all of them
Called with no filters, the endpoint returns every series in the dataset, for every market ORTEX covers it in. Each row names its own market, seriesSlug and sourceSlug, so a single request is enough to chart the whole dataset.
Narrow it with any combination of market (one market), series (one measure) and source (one publisher). Filter values that are each valid but select nothing together return 400 invalidSelection rather than a misleading empty result.
Raw readings here; comparable ones next door
This endpoint serves the publisher's numbers. Raw values are frequently not comparable — receivables of $10.9bn against $4.9bn say nothing without each book's size, and a 5.3% charge-off rate means something different on a subprime book than a prime one. The Alt Data signals endpoint serves the same series as percentiles and z-scores against a stated comparison set, which is the form a screen or a backtest wants.
Why a company you expect may be missing
Three reasons, and none of them is a bug:
- The dataset is a window, not a census: Several of these publishers release a rolling window rather than a complete history.
- The filer is not the listed company: Registers name a marque, a charter or a trust. ORTEX maps those to the listed parent where the link is defensible and leaves them unmapped where it is not — a wrong mapping silently attributes another company's data to your ticker.
- The population is genuinely narrow: Not every listed company appears in every register, and no amount of mapping changes that.
How much history there is
Several of these publishers overwrite their own pages and keep no archive. Where that is so, the series begins on the day ORTEX started capturing it and lengthens from there — nobody, including the publisher, can supply the days before that. Everything ORTEX has ever fetched is archived on capture, so the series only ever grows.
Try it out! You can test the API with the trial key TEST. Simply include it in your request headers; either here, or add the header "Ortex-Api-Key": "TEST" to your http request.
Trial key restrictions: Trial keys may be limited to a specific date range and set of regions. Requests outside the allowed regions or entirely outside the allowed date range are rejected; a date window that partially overlaps the allowed range is trimmed to it, reported in meta.restriction.
Get full access! Get a key at app.ortex.com/apis
