SEC EDGAR Corporate Filings & 10-K / 8-K Extractor avatar

SEC EDGAR Corporate Filings & 10-K / 8-K Extractor

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from $1.05 / 1,000 item scrapeds

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SEC EDGAR Corporate Filings & 10-K / 8-K Extractor

SEC EDGAR Corporate Filings & 10-K / 8-K Extractor

Extract real-time corporate SEC filings including 10-K, 10-Q, 8-K, Form 4, and S-1 by company ticker or CIK. Extract accession numbers, filing dates, and document URLs.

Pricing

from $1.05 / 1,000 item scrapeds

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LiteZero

LiteZero

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4 days ago

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🏛️ SEC EDGAR Financial Filings & 10-K / 8-K Extractor

Extract official US Securities and Exchange Commission (SEC EDGAR) corporate filings including annual reports (10-K), quarterly reports (10-Q), material events (8-K), and insider trading forms with direct interactive document URLs and metadata.


🥊 Why This Actor Beats the Competition

Feature🏛️ SEC EDGAR Filings ExtractorComplex Financial Data APIsLegacy SEC Web Crawlers
SpeedInstant REST JSON extraction (< 1 sec)Slow heavy data pipelinesFragile table scrapers (5-15s)
PricingPay-Per-Result ($1.50 / 1k filings)$500–$2,000/mo enterprise feesExpensive server compute bills
Direct Document LinksGenerated direct links to .htm and inline XBRLOnly raw text or PDFBroken links due to complex SEC paths
Ticker & CIK ResolutionBuilt-in ticker-to-CIK mapping for all major stocksRequires manual CIK searchOften fails on ticker lookup
SEC Rate ComplianceAuto-throttled to respect SEC's 10 req/s ceilingProne to 429 IP bansFrequently blocked by SEC firewalls

🛠️ Step-by-Step: How to Use

Method 1: Apify Console (No-Code GUI)

  1. Enter one or more stock tickers or 10-digit CIK numbers (e.g. AAPL, MSFT, NVDA, TSLA).
  2. Select desired form types (default: 10-K, 10-Q, 8-K).
  3. Set maxFilingsPerCompany and click Start.

Method 2: Python SDK

from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run_input = {
"tickersOrCiks": ["AAPL", "NVDA"],
"formTypes": ["10-K", "10-Q"],
"maxFilingsPerCompany": 5
}
run = client.actor("litezero/sec-edgar-filings-scraper").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(f"[{item['ticker']}] Form {item['formType']} filed on {item['filingDate']}: {item['primaryDocumentUrl']}")

Method 3: Node.js SDK

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('litezero/sec-edgar-filings-scraper').call({
tickersOrCiks: ['TSLA', 'AMZN'],
formTypes: ['8-K'],
maxFilingsPerCompany: 10,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Method 4: cURL / REST API

curl --request POST \
--url "https://api.apify.com/v2/acts/litezero~sec-edgar-filings-scraper/runs?token=YOUR_APIFY_TOKEN" \
--header "Content-Type: application/json" \
--data '{"tickersOrCiks": ["AAPL"], "formTypes": ["10-K"]}'

📥 Input Parameters

ParameterTypeDefaultDescription
tickersOrCiksArray["AAPL", "TSLA"]List of stock tickers (e.g. NVDA, MSFT) or numeric CIKs.
formTypesArray["10-K", "10-Q", "8-K"]Specific SEC forms to retrieve. Leave empty for all forms.
maxFilingsPerCompanyInteger10Number of most recent filings to fetch per company.

📤 Sample Output JSON

{
"companyName": "Apple Inc.",
"cik": "0000320193",
"ticker": "AAPL",
"formType": "10-K",
"filingDate": "2025-11-01",
"reportDate": "2025-09-28",
"accessionNumber": "0000320193-25-000106",
"primaryDocumentUrl": "https://www.sec.gov/Archives/edgar/data/320193/000032019325000106/aapl-20250928.htm",
"filingSummaryUrl": "https://www.sec.gov/ix?doc=/Archives/edgar/data/320193/000032019325000106/aapl-20250928.htm",
"primaryDocDescription": "10-K",
"fileSize": 12849021,
"sic": "3571",
"sicDescription": "Electronic Computers",
"fiscalYearEnd": "0930",
"scrapedAt": "2026-10-02T16:45:00.000Z"
}

💡 Top Commercial Use Cases

  1. Automated Earnings Alert Bots: Detect new 10-K and 10-Q filings seconds after submission to extract guidance tables.
  2. Material Event Monitoring: Screen 8-K filings for executive turnover, acquisitions, or litigation updates.
  3. Institutional Equity Research: Build automated historical filing archives for quantitative sentiment analysis.