Event windows: identify overlapping explanations
An event window is a predefined interval around a disclosed event, not proof that everything inside it was caused by that event. Build a timeline of public information and overlapping explanations before AI writes a causal story. The task is to identify what a narrow or broad window includes and what attribution remains unsupported.
SEC EDGAR API documentation describes submissions and their updating as filings are disseminated. A filing record can anchor a disclosure trail; it does not establish that a market outcome was caused by the filing or that no earlier public information existed.
Define the event clock
Specify the event itself: publication of a filing, release of results, announcement of an agreement or another documented disclosure. Distinguish that public-information event from the date of the underlying business activity. A contract signed earlier and announced later creates at least two different timeline entries.
Record source timestamp, timezone, precision and the market calendar used. A calendar date without an hour may be inadequate for a very narrow intraday window. Do not invent precision. If the disclosure occurs outside market hours, state the session convention used for the first eligible observation.
Choose the window before reviewing the desired outcome. Write why that interval fits the information question. Extending the window until a preferred move appears is a selection choice that needs disclosure, not a neutral adjustment. Preserve exploratory alternatives separately from the original plan.
Hypothetical overlapping announcements
Assume fictional Company Alder publishes a results announcement after the market closes on Monday. On Tuesday morning, an industry policy announcement occurs, and on Wednesday the company announces financing. A Monday-to-Wednesday window includes all three information events.
If an AI summary attributes the entire observed change to Monday’s earnings, it ignores the overlap. A narrower Tuesday-opening observation may reduce some contamination but still includes the policy announcement. The researcher must compare actual publication order and data resolution rather than assuming a shorter window removes every alternative.
Suppose the earnings release date is known but its hour is not. A precise before-versus-after comparison around Tuesday’s opening cannot be established from that record alone. Keep the timing unresolved or choose a coarser question. All companies and announcements in this scenario are hypothetical.
Event-window contamination worksheet
| Record | Evidence and classification |
|---|---|
| Primary disclosure | Original source, publication time and version |
| Underlying event | Business date, distinct from publication |
| Window boundaries | Session rules, timezone and chosen rationale |
| Company overlaps | Financing, guidance, litigation or other documented events |
| Common overlaps | Industry or market information within the interval |
| Unresolved alternatives | Missing timing or potentially relevant disclosures |
Do not mark no competing events merely because the first search returned none. Keep a search scope and coverage note. A defined filing search, issuer release review and relevant industry timeline offer a stronger basis than one keyword query, while still not proving exhaustive coverage.
Match the conclusion to the design
A descriptive event note can say an outcome occurred within the selected window and list overlapping information. A causal effect estimate requires a separate design and assumptions about the comparison outcome. Do not let polished language upgrade temporal proximity into identification.
Run sensitivity across justified windows, reporting changes in included events as well as numeric outcomes. If the conclusion depends on one boundary choice, make that dependence explicit. AI can organize the timeline and suggest overlooked alternatives, but each event and timestamp needs source evidence. The final deliverable should show what the window can isolate, what it bundles together and why any causal language remains limited.
FAQ
Does a narrow window automatically eliminate confounding news?
No. Relevant information can arrive within the same narrow interval or before an imprecisely timed disclosure.
Can AI infer an exact release time from a filing date?
No. Use an evidenced timestamp or retain date-level precision and limit the analysis accordingly.