How to Track Spikes in a Company's SEC Filing Activity via API

Use Alphanume's SEC Filing Intensity endpoint to flag companies whose EDGAR activity has suddenly picked up.

Filing activity is bursty. A company that normally files a handful of documents a month might file a dozen in a single day when something is happening. The Alphanume SEC Filing Intensity endpoint turns that pattern into a daily count you can monitor and filter programmatically.

The endpoint

GET https://api.alphanume.com/v1/filing-intensity

This is a Pro endpoint. Authenticate with ?api_key=alp_your_key or an X-API-Key header. The useful filters are ticker, date, and the filing-count filters filing_count_gte, filing_count_lte, filing_count_gt, filing_count_lt, and filing_count_eq.

Find high-activity days

import requests

r = requests.get(
    "https://api.alphanume.com/v1/filing-intensity",
    params={"filing_count_gte": 5, "date": "2026-06-15", "api_key": "alp_your_key"},
)
for row in r.json()["data"]:
    print(row["date"], row["ticker"], row["filing_count"])

Filtering on filing_count_gte surfaces every name with an unusually busy filing day. Combined with a date, this is a one-call daily scan for companies that just stepped up their EDGAR activity.

Build a relative spike detector

A raw count is most useful when compared to a name's own baseline. Pull a history with date range filters, compute a rolling average of filing_count per ticker, and flag days where the count jumps well above that baseline. That turns the absolute count into a normalized burst signal.

GET https://api.alphanume.com/v1/filing-intensity?date_gte=2026-01-01&api_key=alp_your_key

Combine it with corporate-event data

A filing burst is a prompt to look closer, not a conclusion on its own. Cross-reference spikes against Stock Dilution and Corporate Default Events to see whether the activity coincides with offerings or distress disclosures.

Access and limits

SEC Filing Intensity is Pro-only, refreshed nightly at 11:30 PM EST, with a 600 requests per minute rate limit and HTTP 429 on overage. The dataset is cursor-paginated, returning has_more and next_cursor. Read the API documentation, review Alphanume datasets, or grab a free Alphanume API key.

Absolute counts versus relative spikes

The quickest scan is a single filtered call: filing_count_gte with a date returns every name with an unusually busy filing day. That is enough to catch the loudest activity, but a raw threshold treats a serial filer and a normally quiet company the same, so it misses the more interesting signal.

A relative detector is more discerning. Pull a history with the date range filters, compute a rolling average of filing_count per ticker, and flag days where the count jumps well above that baseline. A burst is a prompt to look closer, not a conclusion, so cross-reference it against dilution and corporate default data to see whether the activity coincides with an offering or a distress disclosure.

Frequently asked questions

What is the filing intensity endpoint?

GET https://api.alphanume.com/v1/filing-intensity. It is a Pro endpoint; authenticate with ?api_key=alp_your_key or an X-API-Key header.

How do I find high-activity days?

Filter on filing_count_gte with a date, for example filing_count_gte=5, to surface every name with an unusually busy filing day.

Which filing-count filters exist?

filing_count_gte, filing_count_lte, filing_count_gt, filing_count_lt, and filing_count_eq, alongside ticker and date.

How do I build a relative spike detector?

Pull a history with date range filters, compute a rolling average of filing_count per ticker, and flag days where the count jumps well above that baseline.

How do I confirm what a spike means?

Cross-reference the spike against dilution and corporate default data to see whether the activity coincides with offerings or distress disclosures.