Pricing

Pay per usage

Buyback Insider Conviction: 8-K Repurchase Plus Insider Buys

For each ticker, finds 8-K share repurchase announcements and correlates them with insider open-market buying around the filing, scores conviction 0 to 100, and tiers each as conviction_buyback, accumulation, or watch. A buyback plus insiders buying is the signal. Pure EDGAR data, no keys.

Pricing

Pay per usage

Rating

0.0

(0)

Developer

Ken M

Actor stats

Bookmarked

Total users

Monthly active users

3 days ago

Last modified

Output

One row per buyback 8-K:

{
  "ticker": "OLN",
  "company": "Olin Corp",
  "eventType": "8-K buyback announcement",
  "fileDate": "2026-05-12",
  "daysAgo": 6,
  "filingUrl": "https://www.sec.gov/Archives/edgar/data/.../...-index.htm",
  "edgeScore": 71,
  "tier": "conviction_buyback",
  "insider": {
    "windowDays": 21,
    "buyCount": 3,
    "uniqueBuyers": 2,
    "sellCount": 0,
    "buyValueUsd": 520000,
    "netValueUsd": 520000,
    "topBuys": [{ "insider": "...", "role": "Director", "valueUsd": 300000, "date": "2026-05-10" }]
  }
}

Tiers and pricing

Pay per event. The first conviction_buyback row per run is free so you can validate output.

Tier	Meaning	Price
`watch`	Buyback announced, no insider buying in the window	$0.05
`accumulation`	Buyback with insider open-market buying in the window	$0.10
`conviction_buyback`	Buyback with a net insider buying cluster (two or more insiders)	$0.18

Combined cost note. This pipeline calls sec-form4-insider-tracker, which bills its own per-event charges to you in the same run. Both stages are EDGAR HTTP, so total compute stays small.

Input

Field	Default	Notes
`tickers`	`[]`	One or more tickers to scan for buyback announcements. Required.
`buybackKeywords`	`["repurchase","buyback"]`	Words an 8-K must contain to count as a buyback.
`maxAgeDays`	`120`	Ignore filings older than this.
`insiderWindowDays`	`21`	Days on either side of the filing to count insider activity.
`includeInsider`	`true`	Turn off for announcements only.
`minScore`	`0`	Drop and never charge filings below this 0 to 100 score.
`userAgent`	generic	EDGAR asks for a descriptive User-Agent with an email.

Good use cases

Screen a basket of names for buybacks that management is personally backing with open-market buys.
Separate real capital-return conviction from routine repurchase boilerplate.
Feed a value or special-situations screen with one clean signal per announcement.

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