There is a specific kind of financial information asymmetry that has bothered market observers for decades. When a company's CEO buys $2 million of their own stock in the open market, that transaction is legally required to be disclosed to the SEC within two business days. The disclosure is filed as a Form 4. It is published on EDGAR — the SEC's Electronic Data Gathering, Analysis, and Retrieval system — immediately upon filing. It is free to access. It is explicitly public-domain US government data with no copyright restrictions whatsoever.
The CEO knows something about their company's future that you do not. They have bet $2 million of their personal wealth on that knowledge. And they have been legally compelled to tell you about it within 48 hours.
This is one of the most remarkable features of US securities law. The transparency requirement that was designed to prevent insider trading from operating in darkness has inadvertently created one of the most valuable free datasets in finance.
The problem is not access. The problem is signal extraction.
EDGAR receives thousands of Form 4 filings every week. The raw XML is not designed for human reading. A single filing might contain a CEO's routine stock award vesting — a transaction with no informational content whatsoever, since it is automatic and pre-scheduled. Another filing might contain a CFO buying $500,000 of stock in the open market one week before a major contract announcement. These two transactions are structurally identical Form 4 filings. Their informational content is completely different.
The tools that extract signal from this noise — Unusual Whales, Quiver Quant, Capitol Trades, Finviz insider tracking — charge between $48 and $200 per month for access to processed insider data. Bloomberg Terminal access, which includes the deepest institutional-grade insider analysis, costs upwards of £20,000 per year. These prices reflect not the cost of accessing the data — which is free — but the cost of processing it, scoring it, filtering it, and presenting it in a form where a human can act on it quickly.
I became interested in this data while working on a side project involving algorithmic trading signals. The research literature on insider transaction informativeness is extensive and consistent: open-market purchases by corporate insiders — particularly purchases by CEOs and CFOs, particularly large purchases relative to the executive's historical pattern, particularly purchases clustered across multiple insiders at the same company within a short window — are statistically associated with positive abnormal returns over the following six to twelve months.
This is not a secret. It is published in peer-reviewed finance journals. The signal exists. The question is whether an individual retail trader or a fintech newsletter operator can access it affordably enough to act on it.
The SEC Form 4 Insider Trading Alert actor was built to make that access practical.
The actor connects to two EDGAR endpoints. The first is the full-text search API, which allows querying for recent Form 4 filings filtered by date range and company. The second is the company submissions endpoint, which provides a structured history of all filings for a specific company identified by CIK number. Both are free, public, explicitly designed for programmatic access, and documented on the SEC's developer portal with a standard User-Agent requirement — the agency asks developers to identify their tools in request headers, which the actor does.
For each Form 4 filing retrieved, the actor parses the XML to extract the core transaction details: ticker symbol, company name, insider name and title, transaction type (open market purchase versus automatic vesting versus option exercise — critically different signals), transaction date, number of shares traded, price per share, total transaction value, and shares owned following the transaction.
The scoring layer is where the actor's value is concentrated. Each transaction receives a signal score from 0 to 100 based on four factors. Transaction type: open market purchases score highest because they represent discretionary spending of the insider's own money. Position level: CEO and CFO purchases score higher than director purchases. Transaction size: values above $500,000 receive premium scoring; above $1 million, maximum weighting. Cluster detection: when two or more insiders at the same company make open-market purchases within a seven-day window, a cluster flag is added and the score is elevated further.
A CFO buying $750,000 of their own company's stock on the open market, in the same week that the company's chairman makes a $400,000 purchase — that is a cluster event. The scoring logic surfaces it clearly.
The actor charges £0.001 per filing parsed and £0.05 per scored and delivered alert. A weekly run scanning all Form 4 filings and delivering the ten highest-scoring events costs approximately £0.50. A subscription-oriented workflow monitoring a specific watchlist of tickers costs less than £5 per month.
Unusual Whales charges $48 per month. Quiver Pro charges $100 per month. The underlying data is the same data — EDGAR, public domain, free.
The price difference between those tools and this actor is not data access. It is the processing layer. This actor provides that processing layer at a fraction of the subscription cost, in a format that plugs directly into n8n pipelines, Slack notifications, Airtable bases, or any workflow that can consume a structured JSON dataset.
Wall Street has always known where to look. Now so do you.