Insider Trading Data: Fields, Sources, and Backtesting Rules
The schema and timing rules needed to turn public ownership filings into a defensible historical dataset.
Insider trading data is the structured history of ownership disclosures filed by corporate insiders and large beneficial owners. Research-grade data retains issuer and owner identity, transaction and filing timestamps, security type, transaction code, quantity, price, ownership nature, holdings after the transaction, footnotes, amendment status, and the SEC accession.
The minimum useful schema
The normalized row must remain linked to the SEC XML and accession. Multiple non-derivative and derivative tables can appear in one filing, and footnotes may qualify price, ownership, or the purpose of a transaction.
A vendor that collapses a filing into a single buy/sell label may be convenient for alerts but unsafe for quantitative research. Preserve the source values first; create classifications as a separate versioned layer.
- Issuer CIK and stable security identity
- Reporting-owner CIK, role, and relationship
- Transaction code, date, price, and quantity
- Direct or indirect ownership and post-transaction holdings
- Accepted timestamp, accession, amendment, and source hash
Point-in-time rules
Apply the public filing timestamp before any signal logic. Do not backfill a trade to the transaction date unless the strategy explicitly models unavailable information. If an amendment later changes the filing, retain both versions and select only the version known at the simulated time.
Company universes also need historical identity. Delisted companies, renamed issuers, and ticker changes should remain in the sample rather than disappearing from today’s lookup table.
Data quality tests
Test totals against the filing, verify ownership direction, parse footnotes, deduplicate amendments without deleting history, and distinguish an empty period from missing ingestion. Coverage should be reported by issuer and date, not inferred from the number of rows returned.
These controls matter more than decorative scores. A backtest can survive a plain schema; it cannot survive future filings, missing footnotes, or silent symbol substitutions.
How DataCedar preserves the evidence
DataCedar separates acquisition from serving. Permitted source responses are retained with retrieval time and identifiers, normalized into DataCedar-owned tables, checked against expected coverage, and exposed through a stable versioned API. A collector can be replaced without changing the customer contract or making an upstream provider a runtime dependency.
Every research stream carries effective and known-at time where the distinction matters. Rights-restricted, unavailable, partial, stale, and genuinely empty states remain visible, so a backtest can fail closed and a buyer can see the product boundary before committing engineering time.
Key takeaways
- 01Keep source filings and normalized transactions connected.
- 02Use accepted time as the known-at clock.
- 03Separate source values from derived sentiment labels.
- 04Report missing coverage explicitly.
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