# 👁️ SEC Form 4 Insider Trading Tracker — CEO/CFO Buys & Sells (`nexgendata/sec-form4-insider-tracker`) Actor Track SEC Form 4 insider trading filings across US-listed companies. CEO, CFO, Director, 10%-owner buys & sells with shares, price, total value, post-transaction ownership. Cluster-buy detection. Bloomberg insider-flow alternative for hedge funds, quants, smart-money followers. Pay-per-result. - **URL**: https://apify.com/nexgendata/sec-form4-insider-tracker.md - **Developed by:** [NexGenData](https://apify.com/nexgendata) (community) - **Categories:** Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $100.00 / 1,000 form 4 records 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/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 ## SEC Form 4 Insider Trading Tracker — CEO/CFO Buys & Sells > **Track every Form 4 filing the SEC publishes — CEOs, CFOs, Directors, and 10% owners buying or selling their own company's stock. Cluster-buy detection. Real shares × price × total value × post-transaction ownership. Bloomberg insider-flow alternative for hedge funds, quants, and retail smart-money followers — without the $24K/year terminal.** ### 📊 Sample Output [![👁️ SEC Form 4 Insider Trading Tracker — CEO/CFO Buys & Sells sample output — 👁️ SEC Form 4 Insider Trading Tracker — CEO/CFO Buys & Sells, premium API, JSON output, NexGenData premium dataset for anal](https://api.apify.com/v2/key-value-stores/8gLgXMBveEI1tTz1z/records/sec-form4-insider-tracker-output.png)](https://apify.com/nexgendata/sec-form4-insider-tracker) When the CEO of a company buys $5M of his own stock with cash, that's a signal. Academic research consistently shows that **insider buying — especially cluster buying by multiple officers simultaneously — outperforms the S&P 500 by 6–12% over the following 12 months**. The data is free, public, and filed within 2 business days of every transaction. The problem is that nobody on Wall Street wants to pay $24K/year for a Bloomberg terminal just to monitor it, and the SEC's raw filing system is unusable at scale. This actor solves that. It pulls **every Form 4 filing across every US-listed company** — sortable by ticker, date range, transaction type (buys vs sells), insider role (CEO / CFO / Director / 10% owner), minimum dollar value, and cluster-buy flag — and returns a clean, structured dataset ready for your trading model, dashboard, alert system, or compliance audit. --- ### What Form 4 Is (And Why It Matters) Under SEC Section 16(a), **every officer, director, and 10% beneficial owner** of a US-listed company must file a Form 4 within **2 business days** of any transaction in that company's stock. The filing is public, free, and the official source of truth for "insider trading" — the legal kind, where insiders disclose their trades, not the illegal kind. The signal value is well-documented: - **Open-market CEO buys**: highest-conviction signal. The CEO is using personal after-tax cash to buy stock they could already get cheaper via options. - **Cluster buys** (3+ insiders buying in 30 days): strongest documented insider signal — Lakonishok & Lee (2001), Cohen-Malloy-Pomorski (2012) both find 6–12% annualized alpha. - **CFO sells under 10b5-1 plans**: weak signal (pre-scheduled). Discretionary CFO sells outside a plan: strong negative signal. - **10% owner activity**: signals strategic positioning by large holders (Berkshire, BlackRock, activist funds). --- ### Output Schema Each dataset item is one Form 4 transaction line: | Field | Type | Example | |---|---|---| | `filing_date` | `str` | `2026-05-08` | | `filing_time` | `str` | `18:48:54` | | `transaction_date` | `str` | `2026-05-08` | | `filer_name` | `str` | `Martell Frank` | | `filer_title` | `str` | `CEO` | | `relationship` | `str` | `Officer` / `Director` / `10% Owner` / `Other` | | `company_ticker` | `str` | `SMRT` | | `company_name` | `str` | `Smartrent, Inc.` | | `transaction_code` | `str` | `P` (Purchase) / `S` (Sale) / `A` (Award) / `G` (Gift) / `F` (Tax) / `M` (Option Exercise) | | `transaction_type` | `str` | `Open Market Purchase` | | `shares_transacted` | `int` | `50000` (signed: + buy, − sell) | | `shares_transacted_abs` | `int` | `50000` | | `price_per_share` | `float` | `1.12` | | `total_value_usd` | `int` | `56220` | | `total_value_usd_abs` | `int` | `56220` | | `shares_owned_after` | `int` | `3065266` | | `pct_change_owned_pct` | `float` | `2.0` | | `form_4_url` | `str` | `https://www.sec.gov/Archives/edgar/data/...` | | `is_cluster_buy` | `bool` | `true` if 3+ insiders bought this ticker in 30 days | | `is_cluster_sell` | `bool` | `true` if 3+ insiders sold this ticker in 30 days | | `data_source` | `str` | `openinsider.com + sec.gov` | --- ### Input Filters | Filter | Type | Description | |---|---|---| | `limit` | int (1–5000) | Max records to return. Default 100. | | `transaction_type` | enum | `buys` / `sells` / `all`. Default `buys` (highest signal). | | `date_range` | enum | `last_7d` / `last_30d` / `last_90d` / `last_180d` / `all`. Default `last_30d`. | | `min_value_usd` | int | Minimum transaction dollar value. 0 = no filter. | | `ticker` | str | Single ticker symbol to filter (e.g. `AAPL`). Blank = all. | | `insider_role` | enum | `all` / `ceo` / `cfo` / `officer` / `director` / `10%_owner`. | | `cluster_only` | bool | If true, return only cluster trades (3+ insiders same direction in 30 days). | --- ### Use Cases #### 1. Hedge Funds & Quant Shops Build a quant signal: long companies with 3+ open-market officer buys in the last 30 days, short companies with 3+ officer sells outside 10b5-1 plans. Backtest against the last 5 years using the `last_180d` window iterated through historical date ranges. #### 2. Retail "Smart Money" Followers Screen for high-conviction CEO/CFO buys above $1M. These are personal-cash trades — the CEO can't claim "tax-loss harvesting" or "diversification" when they're concentrating *more* into their own company. #### 3. Compliance & Risk Teams Monitor insider activity at your top suppliers, customers, and competitors. Sudden CFO sells before a quarterly earnings release? Get notified before the market. #### 4. M&A Bankers Track 10% owner activity at potential takeover targets. Activist accumulation patterns often precede public 13D filings by weeks. #### 5. Journalists & Researchers Audit-grade SEC links on every record. Drop the CSV into a story without worrying about source attribution. --- ### Comparison vs Bloomberg / FactSet / Refinitiv / TipRanks / OpenInsider Pro | Capability | This Actor | Bloomberg | FactSet | Refinitiv | TipRanks | OpenInsider Pro | |---|---|---|---|---|---|---| | Form 4 transaction-level data | ✅ | ✅ | ✅ | ✅ | ⚠ summary | ✅ | | CEO/CFO/Director role filter | ✅ | ✅ | ✅ | ✅ | ❌ | ⚠ manual | | Cluster-buy detection | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | | Min-value filter | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | | Post-transaction ownership | ✅ | ✅ | ✅ | ✅ | ⚠ partial | ✅ | | Direct SEC EDGAR link | ✅ | ⚠ separate | ⚠ separate | ⚠ separate | ❌ | ✅ | | API / programmatic access | ✅ | ✅ ($24K/yr) | ✅ ($30K/yr) | ✅ ($22K/yr) | ⚠ paid | ❌ scrape only | | Pay-per-result pricing | ✅ $0.10 | ❌ flat | ❌ flat | ❌ flat | ❌ flat | ❌ subscription | | Annual cost @ 10K records/yr | **$1,001** | $24,000+ | $30,000+ | $22,000+ | $2,400 | $948 | **Bottom line:** if you don't need a full Bloomberg terminal (and 99% of teams don't), this actor gets you the same insider-flow data for **3–4% of the cost**. --- ### Example Output ```json { "filing_date": "2026-05-08", "filing_time": "18:48:54", "transaction_date": "2026-05-08", "filer_name": "Martell Frank", "filer_title": "CEO", "relationship": "Officer", "company_ticker": "SMRT", "company_name": "Smartrent, Inc.", "transaction_code": "P", "transaction_type": "Open Market Purchase", "shares_transacted": 50000, "shares_transacted_abs": 50000, "price_per_share": 1.12, "total_value_usd": 56220, "total_value_usd_abs": 56220, "shares_owned_after": 3065266, "pct_change_owned_pct": 2.0, "form_4_url": "https://www.sec.gov/Archives/edgar/data/1837014/000119312526215194/xslF345X03/ownership.xml", "is_cluster_buy": false, "is_cluster_sell": false, "data_source": "openinsider.com (Form 4 aggregator) + sec.gov (audit link)" } ```` *** ### Quickstart #### Apify Console 1. Click **Start** on the actor page. 2. Set `transaction_type` to `buys`, `date_range` to `last_30d`, `min_value_usd` to `100000`. 3. Hit Run. Results appear in the dataset within ~30 seconds. #### cURL ```bash curl -X POST "https://api.apify.com/v2/acts/nexgendata~sec-form4-insider-tracker/run-sync-get-dataset-items?token=YOUR_TOKEN" \ -H "Content-Type: application/json" \ -d '{"limit": 100, "transaction_type": "buys", "date_range": "last_30d", "min_value_usd": 250000}' ``` #### Python SDK ```python from apify_client import ApifyClient client = ApifyClient("YOUR_TOKEN") run = client.actor("nexgendata/sec-form4-insider-tracker").call(run_input={ "limit": 500, "transaction_type": "buys", "date_range": "last_90d", "insider_role": "ceo", "min_value_usd": 1000000, "cluster_only": True, }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(f"{item['filing_date']} {item['company_ticker']} {item['filer_name']} " f"({item['filer_title']}) bought ${item['total_value_usd_abs']:,}") ``` *** ### Pricing **$0.10 per Form 4 transaction record returned**, plus **$0.01 per actor start**. - Smoke test (10 records): **$1.01** - Daily monitor (100 records/day): **$3.01/day**, ~$90/month - Full universe pull (5,000 records): **$500.01** Compare to: Bloomberg ($2,000+/month), FactSet ($2,500+/month), Refinitiv ($1,800+/month). Even TipRanks Premium ($199/month) doesn't expose transaction-level Form 4 data via API. *** ### How It Works **Primary data source:** [OpenInsider](http://openinsider.com) — a clean HTML aggregator that mirrors every SEC Form 4 filing within seconds of publication. We chose OpenInsider over the raw SEC EDGAR full-text search because: 1. **Pre-parsed cluster flags** — OpenInsider's `X` column already tags cluster activity. 2. **Transaction-pricing context** — OpenInsider parses the `price` and `quantity` fields out of the SEC XML reliably; SEC EDGAR returns the raw XML which is hostile to parse. 3. **Per-row SEC link** — every OpenInsider row links directly to the SEC EDGAR Form 4 XML for the audit trail. 4. **Doesn't rate-limit** under reasonable use. **Audit trail:** Every record includes `form_4_url` pointing to the official SEC EDGAR XML filing. You can verify any transaction independently in 1 click. **Cluster detection:** Computed locally on the returned dataset — we count distinct insiders per (ticker, direction) over the last 30 days and tag any company with 3+ insiders trading the same way. *** ### FAQ **Q: How fresh is the data?** A: OpenInsider re-scans SEC EDGAR every ~15 minutes. The SEC's own 2-business-day filing window is the binding constraint — even Bloomberg can't show you a Form 4 before the insider files it. **Q: Does this include Form 144 (planned sales)?** A: No — Form 144 is filed *before* a planned sale, and is a different filing. This actor tracks Form 4 (the actual transaction record). Form 144 is much noisier and has lower signal value. **Q: How are 10b5-1 plan sales handled?** A: The SEC requires insiders to flag 10b5-1 sales on the filing. We do not currently expose that flag explicitly, but you can identify likely 10b5-1 sales by clicking through to the `form_4_url` — they're typically routine, evenly-sized, and recur monthly. **Q: What about international (non-US-listed) insiders?** A: Form 4 is a US-only filing. For non-US insider disclosures, see local equivalents (UK FSA "PDMR" notices, Japanese "TOSHO" filings). **Q: Can I get historical data going back 10 years?** A: The `all` date range pulls the full OpenInsider screener window (~2 years). For deeper history, query the actor in a loop with rolling date windows — each Form 4 filing has its SEC URL preserved. *** ### Related Actors — Build A Full SEC / Smart-Money Stack | Actor | What It Does | |---|---| | [SEC Form 13F Holdings Tracker](https://apify.com/nexgendata/sec-form-13f-holdings-tracker) | Quarterly institutional holdings — Berkshire, Renaissance, every hedge fund with $100M+ AUM. | | [SEC Schedule 13D/G Activist Tracker](https://apify.com/nexgendata/sec-schedule-13dg-activist-tracker) | 5%+ ownership stakes by activists (Icahn, Ackman, Loeb). | | [SEC Form 8-K Material Events Scraper](https://apify.com/nexgendata/sec-form-8k-material-events-scraper) | Real-time material disclosures — M\&A, CEO changes, restatements. | | [Finviz Stock Screener](https://apify.com/nexgendata/finviz-stock-screener) | Filter the full US-listed universe by 60+ technical & fundamental criteria. | | [Chinese ADRs Stock Screener](https://apify.com/nexgendata/chinese-adrs-stock-screener) | Track Chinese companies listed on US exchanges with risk and delisting flags. | | [Finance MCP Server](https://apify.com/nexgendata/finance-mcp-server) | LLM-ready finance data — give Claude / GPT access to insider flows, fundamentals, charts. | *** ### Disclaimer This actor returns **public SEC Form 4 filing data** sourced from SEC EDGAR (via OpenInsider as an aggregator). All transaction details are filed by the insiders themselves under SEC regulation; we add no proprietary signal, ranking, or recommendation. **This is not investment advice.** Insider trading data is one input among many; past performance does not predict future results. *** ### Affiliate / Referral Like this actor? **Sign up for Apify with our referral link** to support more builds like this one: [**https://apify.com/nexgendata?fpr=2ayu9b**](https://apify.com/nexgendata?fpr=2ayu9b) You get the same free tier; we get a small commission. No price difference for you. ### 🔗 Related NexGenData Actors Part of the NexGenData **SEC Filing** suite — pair this Actor with: - [SEC Form 8-K Material Events Tracker](https://apify.com/nexgendata/sec-form-8k-material-events-scraper?fpr=2ayu9b) - [SEC Form 13F Holdings Tracker Hedge Fund Filings](https://apify.com/nexgendata/sec-form-13f-tracker-pro?fpr=2ayu9b) - [SEC Form D Tracker Private Capital Raises & Exempt Offerings](https://apify.com/nexgendata/sec-form-d-tracker?fpr=2ayu9b) - [SEC Form ADV Investment Adviser Registration Tracker](https://apify.com/nexgendata/sec-form-adv-investment-adviser-tracker?fpr=2ayu9b) # Actor input Schema ## `limit` (type: `integer`): Maximum number of Form 4 transaction records to push to the dataset (one row per insider transaction line). OpenInsider returns the most recent records first, sorted by filing date descending. Typical insider-flow analysts pull 100–500 records per refresh. ## `transaction_type` (type: `string`): Filter to open-market insider buys (P codes), open-market sells (S codes), or all transactions. 'Buys' is the highest-signal subset — directors and officers typically only buy with their own cash when they believe the stock is undervalued. 'Sells' includes both informed sales and routine 10b5-1 plan sales. ## `date_range` (type: `string`): How far back to look for Form 4 filings (by SEC filing date, not transaction date — insiders have 2 business days to file). Use last\_7d for breaking news / event-driven flow; last\_30d for the standard insider-monitor window; last\_90d for backtests; all for the full OpenInsider history available on the screener. ## `min_value_usd` (type: `integer`): Skip transactions below this dollar value. The dollar value is shares × price per share. Common thresholds: $25,000 (filter routine awards/gifts), $100,000 (material trades by mid-level officers), $1,000,000 (meaningful CEO/CFO conviction trades). Leave at 0 for no filter. ## `ticker` (type: `string`): Restrict results to a single US-listed ticker symbol (e.g. 'AAPL', 'TSLA', 'NVDA'). Leave blank to pull all tickers — the screener covers every US-listed common stock with a Form 4 filing in the requested window. ## `insider_role` (type: `string`): Filter by the insider's reported role / relationship. 'CEO' isolates the highest-signal trades (CEO buys are the strongest documented insider signal in academic studies). '10%\_owner' surfaces large strategic holders. 'all' returns every officer + director + 10% owner. ## `cluster_only` (type: `boolean`): If true, return only transactions where 3+ insiders at the same company traded in the same direction within the prior 30 days (cluster-buy / cluster-sell signal). Cluster buys are widely considered the strongest insider conviction signal — the academic consensus is that they outperform the market by 6–12% in the following 12 months. ## Actor input object example ```json { "limit": 100, "transaction_type": "buys", "date_range": "last_30d", "min_value_usd": 0, "ticker": "", "insider_role": "all", "cluster_only": false } ``` # 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 = { "limit": 100, "transaction_type": "buys", "date_range": "last_30d", "min_value_usd": 0, "ticker": "", "insider_role": "all", "cluster_only": false }; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/sec-form4-insider-tracker").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 = { "limit": 100, "transaction_type": "buys", "date_range": "last_30d", "min_value_usd": 0, "ticker": "", "insider_role": "all", "cluster_only": False, } # Run the Actor and wait for it to finish run = client.actor("nexgendata/sec-form4-insider-tracker").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 '{ "limit": 100, "transaction_type": "buys", "date_range": "last_30d", "min_value_usd": 0, "ticker": "", "insider_role": "all", "cluster_only": false }' | apify call nexgendata/sec-form4-insider-tracker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/sec-form4-insider-tracker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "👁️ SEC Form 4 Insider Trading Tracker — CEO/CFO Buys & Sells", "description": "Track SEC Form 4 insider trading filings across US-listed companies. CEO, CFO, Director, 10%-owner buys & sells with shares, price, total value, post-transaction ownership. Cluster-buy detection. Bloomberg insider-flow alternative for hedge funds, quants, smart-money followers. Pay-per-result.", "version": "0.0", "x-build-id": "CXou68aaCWJeHuZ6j" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~sec-form4-insider-tracker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-sec-form4-insider-tracker", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~sec-form4-insider-tracker/runs": { "post": { "operationId": "runs-sync-nexgendata-sec-form4-insider-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~sec-form4-insider-tracker/run-sync": { "post": { "operationId": "run-sync-nexgendata-sec-form4-insider-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "limit": { "title": "Max Form 4 records to return", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum number of Form 4 transaction records to push to the dataset (one row per insider transaction line). OpenInsider returns the most recent records first, sorted by filing date descending. Typical insider-flow analysts pull 100–500 records per refresh.", "default": 100 }, "transaction_type": { "title": "Transaction type", "enum": [ "buys", "sells", "all" ], "type": "string", "description": "Filter to open-market insider buys (P codes), open-market sells (S codes), or all transactions. 'Buys' is the highest-signal subset — directors and officers typically only buy with their own cash when they believe the stock is undervalued. 'Sells' includes both informed sales and routine 10b5-1 plan sales.", "default": "buys" }, "date_range": { "title": "Filing date range", "enum": [ "last_7d", "last_30d", "last_90d", "last_180d", "all" ], "type": "string", "description": "How far back to look for Form 4 filings (by SEC filing date, not transaction date — insiders have 2 business days to file). Use last_7d for breaking news / event-driven flow; last_30d for the standard insider-monitor window; last_90d for backtests; all for the full OpenInsider history available on the screener.", "default": "last_30d" }, "min_value_usd": { "title": "Minimum transaction value (USD)", "minimum": 0, "maximum": 1000000000, "type": "integer", "description": "Skip transactions below this dollar value. The dollar value is shares × price per share. Common thresholds: $25,000 (filter routine awards/gifts), $100,000 (material trades by mid-level officers), $1,000,000 (meaningful CEO/CFO conviction trades). Leave at 0 for no filter.", "default": 0 }, "ticker": { "title": "Ticker symbol filter (optional)", "type": "string", "description": "Restrict results to a single US-listed ticker symbol (e.g. 'AAPL', 'TSLA', 'NVDA'). Leave blank to pull all tickers — the screener covers every US-listed common stock with a Form 4 filing in the requested window.", "default": "" }, "insider_role": { "title": "Insider role filter", "enum": [ "all", "ceo", "cfo", "officer", "director", "10%_owner" ], "type": "string", "description": "Filter by the insider's reported role / relationship. 'CEO' isolates the highest-signal trades (CEO buys are the strongest documented insider signal in academic studies). '10%_owner' surfaces large strategic holders. 'all' returns every officer + director + 10% owner.", "default": "all" }, "cluster_only": { "title": "Cluster trades only", "type": "boolean", "description": "If true, return only transactions where 3+ insiders at the same company traded in the same direction within the prior 30 days (cluster-buy / cluster-sell signal). Cluster buys are widely considered the strongest insider conviction signal — the academic consensus is that they outperform the market by 6–12% in the following 12 months.", "default": false } } }, "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 } } } } } } } } } } ```