Alphanume
Corporate EventsPro

Stock Dilution

See new share supply the day it is registered rather than the day the stock gaps: in the published study, the median dilutive filer was 14.9% lower a month later and 71% of them were down. Every S-1 registration statement is captured as it was known on the filing date, labeled dilutive or not, sized against market cap, and tracked forward until it becomes effective or is withdrawn.

GET /v1/dilutionUpdated daily from SEC EDGAR
  • Separate new supply from paperwork.

    dilutive marks the filings that put new shares into the market, and resale marks registrations of shares existing holders already own.

  • Size the offering against the company.

    shares_offered next to market_cap_at_filing, measured one trading day before the filing, shows how much supply is coming relative to what the company is worth.

  • Follow each filing to its outcome.

    became_effective with days_to_effective, or offering_withdrawn with days_to_withdrawal, resolves the filing instead of leaving it open.

Ask your agent
Prompt · MCP or REST

Which small companies just moved to sell a big block of new stock into the market? Rank them by how much dilution that would be and tell me which offerings went ahead and which were pulled.

Your agent translates this into dilutive filings only, resale registrations excluded, offering size measured against market cap on the filing date, and each filing's effectiveness or withdrawal outcome.

What this dataset is

The paperwork that comes before new shares hit the tape.

An S-1 is the registration statement a company files with the SEC before it can sell shares to the public. For a company that is already listed, an S-1 usually means new shares are being registered for sale: a secondary offering, or a resale of shares held by insiders and private investors. Smaller issuers live on this form because they are not eligible for the S-3 shelf process larger companies use.

Each row is one filing as it was known on the filing date, labeled for whether it is dilutive, with market context attached. Only the lifecycle fields move afterward, as the filing becomes effective, is withdrawn, or stays pending.

Each row includes:

  • The filing date and the exact filing timestamp in Eastern time, so an after-close filing is not mistaken for an intraday one.
  • The dilutive flag and the resale flag, separating new supply from shares existing holders are re-registering.
  • Shares registered in the filing, next to the issuer's market cap one trading day earlier.
  • The effectiveness outcome: whether it became effective, on what date, and how many days that took.
  • The withdrawal outcome: whether the offering was pulled, when, and how long it sat first.
  • The SEC file number, the accession number, and a direct link to the filing on EDGAR.

The filing date is the event date. Registered shares may price weeks later, price small, or never price at all, but the market learns the supply is coming the moment the registration reaches EDGAR, and that is the date this dataset stamps.

What you can do with it

Turn a registration statement into a dated supply shock.

A dilutive S-1 is a supply shock with a date on it. In the published study on this dataset, 437 dilutive filings ran a median 14.9% lower one month later, 15.5% behind SPY, with 71% of them down (z = 8.9). The effect scales with how large the offering is relative to the company: 74% of nano-cap filers were lower a month out, against 43% of large caps.

The lifecycle fields are what turn a filing list into a study design. effective_date marks the day the registered shares can actually be sold and days_to_effective measures how long that took, while offering_withdrawn flags the filings that never got there. That lets you separate the reaction to the announcement from the reaction to the supply itself, with the non-dilutive filings from the same weeks sitting there as a control group.

  • Build a short-candidate screen from dilutive filings with resale excluded, ranked by shares_offered against market_cap_at_filing.
  • Filter a long book so no position is carried into a registered offering unknowingly.
  • Run event studies off the filing date, using non-dilutive rows from the same window as controls.
  • Split results by market cap, where the published effect runs in order from nano caps to large caps.
  • Measure the gap between filing and effective_date, then the reaction when the shares become sellable.
Where the data comes from

Stamped on the filing date, resolved when the outcome lands.

Filings are swept daily from SEC EDGAR. The filing date and timestamp, the SEC file number, the accession number, and the filing link come straight from EDGAR metadata. The dilutive and resale labels are read from the filing itself, and market_cap_at_filing is measured one trading day before the filing so it carries no knowledge of the filing-day reaction.

After publication the record is fixed. Point-in-time fields never change, rows are never removed, and only the lifecycle fields update as events occur: became_effective and effective_date when the SEC declares the registration effective, offering_withdrawn and withdrawal_date when the company pulls it. last_updated records when that resolution last moved.

Fields that matter

The fields that separate dilution from paperwork.

The headline fields below are a subset. Every field, with exact types and semantics, is documented in the API reference.

FieldTypeWhat it tells you
datestringFiling date of the registration statement
filing_timestampstringExact filing timestamp in Eastern time, which separates intraday filings from after-close ones
tickerstringIssuer ticker as of the filing
market_cap_at_filingfloatIssuer market cap one trading day before the filing, for sizing the offering against the company
shares_offeredfloatShares registered in the filing
dilutiveinteger1 when the filing is classified as dilutive, 0 when it is not
resaleinteger1 when the filing registers shares for resale by existing holders rather than new supply
became_effectiveinteger1 once the registration has been declared effective
effective_datestringDate the registration became effective
days_to_effectivefloatDays from filing to effectiveness
offering_withdrawninteger1 when the company pulled the offering; withdrawal_date carries the date
days_to_withdrawalfloatDays the filing sat before it was withdrawn
Query it in one call

One call returns the filing and what became of it.

One key works across the REST API, the hosted MCP server, and this dashboard. Every response is JSON with a { count, data } envelope.

Python
import requests

url = "https://api.alphanume.com/v1/dilution"
params = {
    "date_gte": "2026-02-01",
    "date_lte": "2026-02-28",
    "api_key": "alp_abc123"
}

r = requests.get(url, params=params)
print(r.json())
cURL
curl "https://api.alphanume.com/v1/dilution?date_gte=2026-02-01&date_lte=2026-02-28&api_key=alp_abc123"
Example response
{
  "count": 1,
  "data": [
    {
      "date": "2026-02-02",
      "filing_timestamp": "2026-02-02T16:05:51-05:00",
      "ticker": "IVDA",
      "company_name": "Iveda Solutions, Inc.",
      "market_cap_at_filing": 2557918.88,
      "dilutive": 1,
      "resale": 0,
      "shares_offered": 5434782.0,
      "became_effective": 0,
      "effective_date": "",
      "days_to_effective": null,
      "offering_withdrawn": 0,
      "withdrawal_date": "",
      "days_to_withdrawal": null,
      "root_file_number": "333-293126",
      "accession_number": "0001493152-26-004743",
      "filing_url": "https://www.sec.gov/Archives/edgar/data/1397183/000149315226004743/0001493152-26-004743-index.htm",
      "last_updated": "2026-02-02 23:01:15.364519-05:00"
    }
  ]
}
Honest limitations

What this data does not claim.

  • dilutive is a label on the filing, not a measurement of completed dilution. A registered offering can price small, price late, or never price at all.
  • market_cap_at_filing is measured one trading day before the filing, so it excludes any move on the filing day itself. That is deliberate for point-in-time work, and it means the ratio you compute is a pre-reaction ratio.
  • An unresolved filing carries became_effective and offering_withdrawn at 0, with empty date strings and null day counts. Absence of an outcome is not evidence of one.
  • The dataset covers S-1 registration statements. Larger issuers raise capital through the S-3 shelf process instead, which is a separate filing path and a separate dataset.
  • shares_offered is a share count taken from the filing, not a dollar amount. Pricing is set later, so the proceeds a company ends up with can differ substantially from any figure you infer at filing.
Common questions

Asked by researchers, answered plainly.

What is the difference between a dilutive S-1 and a resale registration?

A dilutive filing registers shares the company itself would sell, so the share count grows and every existing holder owns a smaller slice. A resale registration covers shares that already exist, usually issued privately, being made sellable by their current owners. Both add supply the market can absorb, but only the first one changes the number of shares outstanding.

Does every S-1 filing lead to an actual offering?

No. Some registrations are withdrawn, which the offering_withdrawn and withdrawal_date fields record, and others sit pending for months without ever being declared effective. The days_to_effective and days_to_withdrawal fields give you the real distribution of how long each path takes rather than an assumption.

Why does dilution hit small caps hardest?

Because the offering is enormous relative to the float and the daily volume that has to absorb it. A $20 million raise is a rounding error at a large company and a doubling of the share count at a microcap. The published study on this dataset shows exactly that gradient: 74% of nano-cap filers were lower one month later, against 43% of large caps.

How is this different from shelf registration data?

An S-1 registers a specific offering the company intends to make. An S-3 shelf pre-authorizes future sales that may or may not happen, sometimes years later. Companies eligible for a shelf mostly use one, so S-1 filings skew toward smaller issuers raising money now, which is why the two datasets cover different populations and different stages of the same problem.

Start querying

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