# Sec Insider Alpha Sniper (`egsand/sec-insider-alpha-sniper`) Actor

- **URL**: https://apify.com/egsand/sec-insider-alpha-sniper.md
- **Developed by:** [Enrique G.](https://apify.com/egsand) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $4.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## 🎯 SEC Insider Alpha Sniper: Form 4 Cluster Buys & Smart Money Tracker

> **Track high-conviction insider buying from official SEC EDGAR Form 4 filings in real-time. Filter pure open-market purchases (Code P), detect executive cluster buying, calculate quantitative conviction scores, and follow C-suite smart money before Wall Street takes notice.**

***

### 🌟 What is SEC Insider Alpha Sniper?

Legendary investor Peter Lynch famously stated:

> *"Insiders might sell their shares for any number of reasons — buying a house, taxes, or college tuition. But they only buy shares for one single reason: **they believe the price is going up**."*

Every business day, corporate executives, board members, and major institutional shareholders file **SEC Form 4 disclosures** reporting transactions in their company's stock.

However, **80% of all SEC filings are pure noise**: routine stock options exercises, tax withholdings, or pre-scheduled automatic retirement sales (Rule 10b5-1).

**SEC Insider Alpha Sniper** cuts through the clutter. It monitors the official SEC EDGAR stream in real-time, isolates genuine **skin-in-the-game open-market purchases (Transaction Code P)**, identifies powerful **Executive Cluster Buys** (multiple C-suite executives accumulating simultaneously), and assigns a proprietary **Quantitative Conviction Score (1–100)** to every trade.

***

### 🚀 Key Features

- **🛡️ 100% Official SEC EDGAR Disclosures:** Direct data ingestion from the U.S. Securities and Exchange Commission with zero reliance on third-party aggregators or delayed feeds.
- **🎯 Pure Open-Market Purchases (Code P):** Automatically excludes non-discretionary noise (stock grants, option conversions, automated plan executions) to reveal true insider conviction.
- **👥 Multi-Executive Cluster Detection:** Flags stocks where 2 or more distinct company leaders (e.g., CEO, CFO, and Directors) accumulate shares within a 7 to 30-day window — historically one of the most reliable bullish catalysts in equity markets.
- **📊 Quantitative Conviction Scoring (1–100):** Evaluates every transaction using an institutional-grade scoring engine that weights executive role, dollar volume, percentage increase in holdings, and cluster density.
- **🌐 Universal Market-Wide or Watchlist Monitoring:** Scan the entire universe of 10,000+ U.S. publicly traded equities in real-time, or target your custom portfolio watchlists (e.g. `NVDA`, `PLTR`, `TSLA`, `AAPL`).
- **📋 Dual-Format Output:** Delivers structured JSON datasets ready for algorithmic pipelines alongside an **Executive Brief in Markdown** saved directly to your Key-Value Store for immediate human review.

***

### ⚙️ Input Parameters

Configure the Actor via simple settings or an automated JSON payload:

| Parameter | Type | Default | Description | Example |
| :--- | :---: | :---: | :--- | :--- |
| **`tickers`** | Array | `[]` | List of stock tickers to monitor. Leave empty to scan the entire US market in real-time. | `["NVDA", "PLTR", "SOFI"]` |
| **`transactionTypes`** | Array | `["P"]` | Form 4 transaction types to include. Code `P` represents open-market purchases; `S` tracks open-market sales. | `["P"]` |
| **`minTransactionValueUsd`** | Integer | `50000` | Minimum dollar value ($ USD) of the trade to filter out trivial purchases. | `100000` |
| **`onlyClusterBuys`** | Boolean | `false` | When enabled, only outputs stocks where 2+ distinct company insiders bought within the window. | `true` |
| **`onlyCSuite`** | Boolean | `false` | Filter exclusively for top-tier leadership: CEO, CFO, COO, President, and Board Chairs. | `true` |
| **`minConvictionScore`** | Integer | `50` | Minimum quantitative conviction score required (1 to 100). Scores $\ge 65$ reflect high conviction. | `65` |
| **`maxFilings`** | Integer | `100` | Maximum number of recent SEC Form 4 filings to scan per run (10 to 500). | `200` |
| **`lookbackDays`** | Integer | `7` | Lookback window in days used to correlate multi-insider cluster accumulation. | `14` |
| **`generateMarkdownSummary`** | Boolean | `true` | Creates an executive-ready Markdown summary in Key-Value store (`INSIDER_BRIEF_MD`). | `true` |

#### Example Input:

```json
{
  "tickers": [],
  "transactionTypes": ["P"],
  "minTransactionValueUsd": 50000,
  "minConvictionScore": 60,
  "onlyClusterBuys": false,
  "onlyCSuite": false,
  "maxFilings": 150,
  "lookbackDays": 7,
  "generateMarkdownSummary": true
}
```

***

### 📦 Output Data Structure

The Actor pushes flat, clean, and normalized records to the default Apify Dataset. Every record provides complete executive and financial context:

```json
{
  "ticker": "ACME",
  "companyName": "Acme Industrial Technologies Corp.",
  "issuerCik": "0001234567",
  "filingDate": "2026-11-02",
  "periodOfReport": "2026-10-31",
  "insiderName": "Sterling Sarah",
  "insiderCik": "0001987654",
  "officerTitle": "Chief Executive Officer",
  "isDirector": true,
  "isOfficer": true,
  "isTenPercentOwner": false,
  "isCeoOrCfo": true,
  "transactionCode": "P",
  "transactionTypeDescription": "Open-Market Purchase",
  "shares": 25000,
  "pricePerShare": 42.50,
  "totalValueUsd": 1062500.00,
  "sharesOwnedFollowing": 150000,
  "stakeIncreasePct": 20.0,
  "is10b51Plan": false,
  "convictionScore": 88,
  "convictionRating": "ULTRA_CONVICTION",
  "isClusterBuy": true,
  "clusterSize": 3,
  "clusterInsiders": [
    "Sterling Sarah",
    "Reynolds David",
    "Vance Elena"
  ],
  "secFilingUrl": "https://www.sec.gov/Archives/edgar/data/1234567/000123456726000010/0001234567-26-000010-index.htm",
  "xmlUrl": "https://www.sec.gov/Archives/edgar/data/1234567/000123456726000010/wk-form4.xml"
}
```

#### Pre-Configured Dataset Views

1. **`insiderTrades` View:** A streamlined table ranking all verified open-market purchases by Conviction Score, transaction size, and insider title.
2. **`clusterBuyAlerts` View:** Highlights corporate enclaves where multiple executives are accumulating stock simultaneously.
3. **`INSIDER_BRIEF_MD` (Key-Value Record):** Formatted Markdown report featuring top trades, cluster summaries, and executive metrics.

***

### 🧠 Conviction Score Methodology

Transactions are evaluated on a 100-point scale:

- **Base Allocation (+35 pts):** Granted strictly to open-market purchases (`Code P`).
- **Seniority Weight (+10 to +25 pts):** Scaled by executive influence (CEO and CFO carry maximum statistical predictive power; followed by COO, President, and Board Directors).
- **Capital Commitment (+4 to +20 pts):** Scaled across dollar thresholds ($25k, $100k, $250k, $500k, and $1M+).
- **Equity Stake Expansion (+5 to +15 pts):** Rewards significant position growth (+5%, +20%, +50%+).
- **Cluster Multiplier (+10 to +15 pts):** Triggered when 2 or more distinct company leaders buy during the same window.
- **Discretionary Bonus (+5 pts / -10 pts):** Spontaneous, out-of-pocket buys receive full credit; pre-scheduled Rule 10b5-1 programmatic plans are flagged and discounted.

#### Conviction Tiers:

- **`ULTRA_CONVICTION` (80–100):** Massive discretionary purchase by C-suite leadership or active multi-insider cluster.
- **`HIGH_CONVICTION` (65–79):** Significant capital deployment with high stake expansion.
- **`MODERATE_CONVICTION` (50–64):** Standard open-market acquisition meeting minimum thresholds.
- **`ROUTINE_PURCHASE` (< 50):** Lower capital commitment or non-leadership purchases.

***

### 🔌 Automated Integrations & Workflows

Connect **SEC Insider Alpha Sniper** to your existing workflow in minutes:

- **Telegram & Discord Alerts:** Connect Apify Webhooks to send instant push notifications whenever an `ULTRA_CONVICTION` or `Cluster Buy` event is detected.
- **Automated Spreadsheets:** Sync directly with Google Sheets, Airtable, or Notion using Make (Integromat) or Zapier.
- **Algorithmic Trading & Quant Models:** Query the Apify API via Python, JavaScript, or cURL to feed live insider sentiment into quantitative strategy engines.
- **Scheduled Runs:** Set a recurring schedule (e.g., every 30 minutes during market hours, or once daily after market close) to maintain an always-updated smart money tracker.

***

### ❓ Frequently Asked Questions

##### Are these disclosures official and legal?

Yes, 100%. All data is parsed directly from official U.S. Securities and Exchange Commission (SEC) Form 4 filings submitted under Section 16(a) of the Securities Exchange Act of 1934.

##### Does this cover all U.S. exchanges?

Yes. The monitor covers all equities listed on the NYSE, NASDAQ, AMEX, and major OTC markets.

##### What is the advantage over standard SEC scrapers?

Generic scrapers dump thousands of uncurated rows containing routine stock grants and salary awards. **SEC Insider Alpha Sniper** applies quantitative filtering to isolate pure discretionary purchases, detects cluster accumulation, and ranks trades by empirical predictive conviction.

# Actor input Schema

## `tickers` (type: `array`):

List of US stock tickers to monitor (e.g. AAPL, NVDA, TSLA, PLTR). Leave empty to scan the entire US stock market in real-time.

## `transactionTypes` (type: `array`):

Form 4 transaction types to include. Code 'P' represents pure open-market purchases (skin-in-the-game). Code 'S' tracks open-market sales.

## `minTransactionValueUsd` (type: `integer`):

Filter out small purchases. Only transactions with dollar value equal or greater than this threshold will be processed.

## `onlyClusterBuys` (type: `boolean`):

If enabled, only outputs stocks where 2 or more distinct company executives/directors bought shares within the lookback window.

## `onlyCSuite` (type: `boolean`):

Filter for key leadership positions only: CEO, CFO, COO, President, and Board Chairs/Directors.

## `minConvictionScore` (type: `integer`):

Minimum quantitative conviction score required to include a transaction (1 to 100). Scores above 65 indicate strong discretionary buying.

## `maxFilings` (type: `integer`):

Maximum number of recent SEC Form 4 filings to scan and analyze.

## `lookbackDays` (type: `integer`):

Time window in days to detect cluster buying across different executives of the same company.

## `generateMarkdownSummary` (type: `boolean`):

Creates an executive-ready Markdown summary brief in the Key-Value Store (INSIDER_BRIEF_MD) for instant reading or report delivery.

## Actor input object example

```json
{
  "tickers": [],
  "transactionTypes": [
    "P"
  ],
  "minTransactionValueUsd": 50000,
  "onlyClusterBuys": false,
  "onlyCSuite": false,
  "minConvictionScore": 50,
  "maxFilings": 100,
  "lookbackDays": 7,
  "generateMarkdownSummary": true
}
```

# Actor output Schema

## `insiderTrades` (type: `string`):

Dataset view containing verified open-market purchases ranked by quantitative conviction score.

## `clusterBuyAlerts` (type: `string`):

Dataset view filtering for stocks where multiple executives accumulated shares in the same window.

## `executiveBrief` (type: `string`):

Formatted executive brief summarizing top insider buys, cluster activity, and conviction ratings.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("egsand/sec-insider-alpha-sniper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("egsand/sec-insider-alpha-sniper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call egsand/sec-insider-alpha-sniper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,egsand/sec-insider-alpha-sniper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/PYBbyAzV4uNrFnOMb/builds/3zpLfDNfYe6cMncTr/openapi.json