# SEC EDGAR Filings Scraper - Insider Trades & Reports (`flash_scraper/sec-edgar-filings-scraper`) Actor Scrape SEC EDGAR filings by stock ticker or company — form type + plain-English label, filing & report dates, filer, accession & direct doc links. Filter to Form 4 insider trades, 8-K, 10-K, 13F etc. + by date. Official SEC data, no API key. Export CSV/JSON/Excel. - **URL**: https://apify.com/flash\_scraper/sec-edgar-filings-scraper.md - **Developed by:** [Flash Scrape](https://apify.com/flash_scraper) (community) - **Categories:** News, Automation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.000035 / actor start This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. Actors are written with capital "A". ## 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. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Insider Trading Tracker — SEC Form 4 Buy/Sell Scraper with Signal Score Turn the SEC's raw EDGAR filings feed into a clean **insider trading** dataset — give it a stock ticker and get every **Form 4 insider buy/sell transaction**, parsed into shares, price, value, and a **-100 to +100 signal score** so you can rank real conviction trades in seconds, at **$5 per 1,000 results**. ### What does it do? This actor is an **insider trading scraper** built on the official SEC EDGAR API (data.sec.gov). Give it a **ticker** (or company name) and it resolves the CIK, pulls the company's filings, and for every **Form 3/4/5 insider filing** fetches the ownership XML and parses the **full transaction table** — insider name, role (director / officer / 10% owner), transaction code, shares, price per share, total value, and shares owned after. Every insider filing is then classified with an **insider_signal** ("Bullish — open-market buy", "Bearish — open-market sale", "Net insider buying", etc.) and a **buy/sell signal_score** from -100 (strong sell) to +100 (strong buy), plus `total_bought_value`, `total_sold_value`, and `net_transaction_value` so you can rank conviction trades instead of reading raw filings one by one. It also returns 8-K, 10-K, 13F, and S-1 filings with plain-English form labels and direct document links when you don't filter to Form 4 only. ### Why use it / who's it for - **Retail investors** building a personal insider-buying watchlist — see when a CEO or CFO is putting real money into their own stock, not just a link to a filing. - **Fintech builders** who need a clean, structured insider-trading feed to power a trading signal, screener, or alert app — no HTML scraping, no XML parsing on your end. - **Equity & credit analysts** who want Form 4 insider transactions joined with company profile data (SIC industry, exchange, fiscal year end) for fundamental research. - **Newsletter writers & fintwit / stock-alert accounts** who publish "insider buying alerts" and need a repeatable, automatable data source. - **Compliance teams & journalists** who need a clean, dated, linkable trail of officer/director trading activity. - **Use cases**: insider-trading watchlists across a portfolio of tickers, scheduled Form 4 alerts via Make/n8n/Zapier, ranking the market's most bullish/bearish insider signals this week, feeding a stock-screener or trading-signal model. ### How to use it 1. Enter one or more stock **tickers** (e.g. `["AAPL", "NVDA"]`) or a **company name** search. 2. Set **formType** to `4` to scope the run to insider trading filings only (leave blank for all filing types). 3. Optionally set **dateFrom** to only pull recent insider trades, and cap **maxItems** / **maxPerCompany**. 4. Leave **parseInsiderTransactions** on (default) to get the full parsed buy/sell transaction table and signal score on each row. 5. Run the actor and export results as CSV, JSON, or Excel — or pull them straight into Sheets/Airtable via integrations. ### Output fields | Field | Description | |---|---| | `ticker`, `company`, `cik` | Resolved stock ticker, company name, and SEC CIK | | `company_sic`, `company_industry` | SIC code and plain-English industry | | `company_exchange` | Listing exchange(s), e.g. Nasdaq | | `fiscal_year_end`, `state_of_incorporation`, `entity_category` | Company profile fields | | `form`, `form_label` | Filing form (e.g. `4`) and plain-English label ("Insider trade") | | `filing_date`, `report_date` | When it was filed / the transaction date | | `accession_number` | SEC accession number | | `primary_doc_url`, `filing_index_url`, `insider_xml_url` | Direct links to the filing document, index, and raw ownership XML | | `is_xbrl`, `size` | XBRL flag and file size | | `insider_name`, `insider_role` | Reporting insider's name and role | | `insider_is_director`, `insider_is_officer`, `insider_is_ten_percent_owner` | Insider relationship flags | | `transactions` | Full parsed **insider trading** table: security, date, code, code_label, shares, price_per_share, value, shares_owned_after | | `transaction_count` | Number of transactions on the filing | | `total_bought_value`, `total_sold_value`, `net_transaction_value` | Dollar totals bought vs. sold | | `insider_signal`, `signal_score` | Plain-English **insider trading signal** and a -100…+100 buy/sell score | #### Example output A real sample from a live run: | ticker | company | form | form_label | filing_date | primary_doc_url | |---|---|---|---|---|---| | AAPL | Apple Inc. | 4 | Insider trade | 2026-06-17 | [form4.xml](https://www.sec.gov/Archives/edgar/data/320193/000114036126025622/xslF345X06/form4.xml) | | AAPL | Apple Inc. | 4 | Insider trade | 2026-06-17 | [form4.xml](https://www.sec.gov/Archives/edgar/data/320193/000114036126025620/xslF345X06/form4.xml) | | AAPL | Apple Inc. | 4 | Insider trade | 2026-05-29 | [form4.xml](https://www.sec.gov/Archives/edgar/data/320193/000114036126023363/xslF345X06/form4.xml) | | AAPL | Apple Inc. | SD | SD | 2026-05-28 | [ef20073373_sd.htm](https://www.sec.gov/Archives/edgar/data/320193/000114036126023149/ef20073373_sd.htm) | ### Input example ```json { "tickers": ["AAPL", "NVDA"], "formType": "4", "dateFrom": "2026-01-01", "parseInsiderTransactions": true, "maxItems": 500 } ```` ### How much does it cost? This actor is **pay-per-event at $0.005 per result — $5 per 1,000 insider trading records** (effective 2026-07-16). There's no subscription: you only pay for filings actually returned. New Apify accounts get **roughly 1,000 results free** on the platform's free tier, enough to build and test a full insider-trading watchlist across a dozen tickers before spending anything. ### FAQ #### Is it legal to scrape SEC insider trading filings? Yes. Form 4, 8-K, 10-K, and all other filings come straight from the SEC's public EDGAR API (data.sec.gov) — the same government database anyone can browse for free. This actor just parses it into structured rows. #### How fresh is the insider trading data? The SEC "recent" feed (used by this actor) holds each company's latest filings, typically updated the same day insiders file their Form 4 — often within two business days of the actual trade, as required by SEC rules. #### Do I need an SEC API key or account? No. The SEC EDGAR data API is free and open; this actor needs no API key, login, or proxy to run. #### What's the difference between signal\_score and insider\_signal? `insider_signal` is a plain-English label ("Bullish — open-market buy", "Bearish — open-market sale", "Net insider buying/selling", "Routine"). `signal_score` is the same classification as a number from -100 (strong sell) to +100 (strong buy), so you can sort or threshold programmatically. #### Can I track multiple tickers at once? Yes — pass an array of tickers and the actor resolves each to its CIK and pulls filings for all of them in parallel, sorted newest first. ### Other Flash Scrape lead tools - [Email Verifier](https://apify.com/flash_scraper/email-verifier) — validate and clean lead lists before outreach - [Company Domain Enricher](https://apify.com/flash_scraper/company-domain-enricher) — find the right website/domain for any company name - [Local Business Leads Scraper](https://apify.com/flash_scraper/local-business-leads) — B2B leads by city and category - [Google Maps Leads Opener](https://apify.com/flash_scraper/google-maps-leads-opener) — bulk-open Google Maps business leads for fast outreach # Actor input Schema ## `tickers` (type: `array`): Stock ticker symbols, e.g. 'AAPL', 'NVDA', 'TSLA'. The actor resolves them to SEC CIKs. ## `companyName` (type: `string`): Company name search (matches the SEC company title, partial). Use instead of / with tickers. ## `ciks` (type: `array`): SEC Central Index Keys, if you already have them. ## `formType` (type: `string`): Keep only filings whose form starts with this, e.g. '4' (insider trades), '8-K', '10-K', '13F', 'SC 13'. Leave empty for all forms. ## `dateFrom` (type: `string`): Only filings on/after this date (YYYY-MM-DD). Optional. ## `maxItems` (type: `integer`): Maximum filings to return across all companies. ## `maxPerCompany` (type: `integer`): Cap per company (the SEC 'recent' feed holds up to ~1000 latest filings). ## `parseInsiderTransactions` (type: `boolean`): For insider filings, fetch and parse the ownership XML into a structured transaction table (insider name, role, code, shares, price, value, shares owned after) plus a buy/sell signal score. ## `maxInsiderDocs` (type: `integer`): Cap on how many Form 3/4/5 documents to fetch + parse per run (each is one extra request to SEC). ## Actor input object example ```json { "tickers": [ "NVDA", "TSLA" ], "ciks": [], "maxItems": 200, "maxPerCompany": 1000, "parseInsiderTransactions": true, "maxInsiderDocs": 300 } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "tickers": [ "AAPL" ] }; // Run the Actor and wait for it to finish const run = await client.actor("flash_scraper/sec-edgar-filings-scraper").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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "tickers": ["AAPL"] } # Run the Actor and wait for it to finish run = client.actor("flash_scraper/sec-edgar-filings-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "tickers": [ "AAPL" ] }' | apify call flash_scraper/sec-edgar-filings-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=flash_scraper/sec-edgar-filings-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "SEC EDGAR Filings Scraper - Insider Trades & Reports", "description": "Scrape SEC EDGAR filings by stock ticker or company — form type + plain-English label, filing & report dates, filer, accession & direct doc links. Filter to Form 4 insider trades, 8-K, 10-K, 13F etc. + by date. Official SEC data, no API key. Export CSV/JSON/Excel.", "version": "0.1", "x-build-id": "BKWOSLwGoVZcBQdrK" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/flash_scraper~sec-edgar-filings-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-flash_scraper-sec-edgar-filings-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/flash_scraper~sec-edgar-filings-scraper/runs": { "post": { "operationId": "runs-sync-flash_scraper-sec-edgar-filings-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/flash_scraper~sec-edgar-filings-scraper/run-sync": { "post": { "operationId": "run-sync-flash_scraper-sec-edgar-filings-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "tickers": { "title": "Stock tickers", "type": "array", "description": "Stock ticker symbols, e.g. 'AAPL', 'NVDA', 'TSLA'. The actor resolves them to SEC CIKs.", "items": { "type": "string" } }, "companyName": { "title": "Company name", "type": "string", "description": "Company name search (matches the SEC company title, partial). Use instead of / with tickers." }, "ciks": { "title": "CIKs (advanced)", "type": "array", "description": "SEC Central Index Keys, if you already have them.", "default": [], "items": { "type": "string" } }, "formType": { "title": "Form type filter", "type": "string", "description": "Keep only filings whose form starts with this, e.g. '4' (insider trades), '8-K', '10-K', '13F', 'SC 13'. Leave empty for all forms." }, "dateFrom": { "title": "Filed on/after (date)", "type": "string", "description": "Only filings on/after this date (YYYY-MM-DD). Optional." }, "maxItems": { "title": "Max filings (total)", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum filings to return across all companies.", "default": 200 }, "maxPerCompany": { "title": "Max filings per company", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Cap per company (the SEC 'recent' feed holds up to ~1000 latest filings).", "default": 1000 }, "parseInsiderTransactions": { "title": "Parse insider transactions (Form 3/4/5)", "type": "boolean", "description": "For insider filings, fetch and parse the ownership XML into a structured transaction table (insider name, role, code, shares, price, value, shares owned after) plus a buy/sell signal score.", "default": true }, "maxInsiderDocs": { "title": "Max insider documents to parse", "minimum": 0, "maximum": 2000, "type": "integer", "description": "Cap on how many Form 3/4/5 documents to fetch + parse per run (each is one extra request to SEC).", "default": 300 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```