# Stock Alpha Signal Aggregator - Unified SEC Intelligence (`wiry_kingdom/stock-alpha-aggregator`) Actor Unified intelligence report per ticker. Combines Form 4 insider trades, 8-K material events, 10-Q/K financial filings, and computed bull/bear signal scores. One call per stock = complete SEC picture. Free official SEC EDGAR API. Replaces $25k/yr Bloomberg Terminal. - **URL**: https://apify.com/wiry\_kingdom/stock-alpha-aggregator.md - **Developed by:** [Mohieldin Mohamed](https://apify.com/wiry_kingdom) (community) - **Categories:** Business, Developer tools - **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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 ## Stock Alpha Signal Aggregator — One Call. One Ticker. Everything. **Stop pulling 5 different data sources. One call returns the complete SEC intelligence picture for any ticker: insider trading, material events, financial filings, and a computed bull/bear signal score. What Bloomberg Terminal costs $25,000/year for — in ONE Apify actor call.** This is the top of the stack. Built on top of every other SEC actor I've shipped. Instead of running Form 4 + 8-K + 10-Q + EDGAR separately and manually merging the output, you pass a ticker and get the fully-parsed, signal-scored, decision-ready intelligence report. ### What you actually get (verified on real tickers) #### TSLA — real output in one call | Metric | Value | |--------|------:| | Form 4 filings parsed | 7 | | Insider BUYS | **0** | | Insider SELLS | **45** | | Net insider value | **-$47,589,560** | | 8-K material events | 3 | | **Signal** | **🔴 BEARISH (score -2)** | #### NVDA — same call, different ticker | Metric | Value | |--------|------:| | Form 4 filings parsed | 15 | | Insider BUYS | **0** | | Insider SELLS | **44** | | Net insider value | **-$294,772,058** | | Distinct insiders selling | 3 (cluster) | | **Signal** | **🔴🔴 STRONGLY_BEARISH (score -4)** | #### PFE — same call, bullish differentiation | Metric | Value | |--------|------:| | Form 4 filings | 15 (mostly option grants) | | Actual open-market SELLS | 1 ($22k — noise) | | 8-K Item 8.01 (positive events) | 2 | | **Signal** | **🟢 BULLISH (score 3)** | **Same actor, three different tickers, three distinct real-world signals.** The aggregator correctly distinguishes heavy insider dumping (NVDA) from option grant noise (PFE) from position trimming (TSLA). ### What it actually does For each ticker you pass, this actor: 1. **Resolves ticker → SEC CIK** via the SEC company tickers mapping 2. **Pulls recent submissions** from the official SEC submissions API 3. **Parses each Form 4 XML** to extract: - Insider name, role (director/officer/10%+ owner), title - Every transaction (shares, price, code, value, direction) - Net aggregate buy vs sell activity 4. **Catalogs 8-K filings** with Item code classification: - Item 1.01 → Material agreement (bullish) - Item 1.03 → Bankruptcy (strongly bearish) - Item 2.01 → Completion of acquisition (bullish) - Item 2.06 → Material impairment (bearish) - Item 5.02 → Exec departure/appointment - ... 20+ more mapped Item codes 5. **Lists 10-Q / 10-K** periodic financial reports 6. **Computes an aggregate alpha signal** using simple rules: - +3 for net insider buying (code P) - +2 for cluster buys (3+ distinct insiders) - -3 for $1M+ net insider selling - -2 for cluster sells by multiple insiders - +1/-3 for positive/negative 8-K events - -1 for C-suite (CEO/CFO) selling ### Signal labels | Score | Label | Meaning | |-------|-------|---------| | ≥ +4 | 🟢🟢 STRONGLY_BULLISH | Multiple bullish signals stacking | | +1 to +3 | 🟢 BULLISH | Net positive factors | | 0 | ⚪ NEUTRAL | Mixed / insufficient data | | -1 to -3 | 🔴 BEARISH | Net negative factors | | ≤ -4 | 🔴🔴 STRONGLY_BEARISH | Multiple bearish signals stacking | ### Why this is the product **Raw data without synthesis is noise.** You can scrape SEC filings all day, but until you answer "is the insider activity bullish or bearish?" — you have a pile of filings, not a trading decision. Commercial products that do exactly this kind of signal aggregation: - **Bloomberg Terminal** — $25,000-35,000/year (EVRY function for insider activity scoring) - **FactSet** — $12,000+/year (SEC Spotlight signal module) - **Refinitiv Eikon** — $20,000+/year - **S&P Capital IQ** — $10,000+/year (built-in insider activity scoring) - **InsiderSentiment.com** — $300/month - **InsiderArbitrage** — $100-500/month This actor delivers the same synthesis — **insider + material events + signal score** — via pay-per-event pricing. ### Who this is for - **Quant traders building signal pipelines** — one API call per ticker instead of 5 - **Retail traders picking stocks** — "should I buy NVDA?" → run this → see $294M insider selling → decide accordingly - **Portfolio managers doing due diligence** — one call = full SEC picture - **Financial journalists** — verify "insider activity" claims with real data - **M&A advisors** — assess a target's insider sentiment before an approach - **Activist investors** — check insider alignment before launching a campaign - **Compliance teams** — monitor insider activity at portfolio companies ### How to use 1. Click **Try for free** (or **Start**) 2. Add tickers to **tickers**: `["TSLA", "NVDA", "PFE", "AAPL"]` 3. Set **lookbackDays** (default 90 = last quarter) 4. Configure how many Form 4 / 8-K / 10-QK filings to parse per ticker 5. Leave **computeSignals: true** to get the signal score 6. Click **Start** Output is one intelligence report per ticker. ### Output (per ticker) ```json { "ticker": "NVDA", "issuerName": "NVIDIA CORP", "issuerCik": "0001045810", "sicCode": "3674", "sicDescription": "Semiconductors & Related Devices", "exchanges": ["Nasdaq"], "form4FilingsCount": 15, "eightKFilingsCount": 4, "tenQKFilingsCount": 2, "insiderNetShares": -2048500, "insiderNetValueUsd": -294772058.66, "insiderBuyCount": 0, "insiderSellCount": 44, "insiderTotalTransactions": 44, "topInsiders": [ { "name": "HUANG JEN HSUN", "title": "President and CEO", "netShares": -1500000, "netValueUsd": -213000000 }, { "name": "DALLY WILLIAM J", "title": "Chief Scientist", "netShares": -350000, "netValueUsd": -49700000 } ], "signalScore": -4, "signalLabel": "STRONGLY_BEARISH", "signalReasons": [ "High Form 4 filing velocity (15 filings)", "Net insider SELLING: $294,772,058 of sales", "Cluster sell: 44 sells by 3 distinct insiders" ], "recentForm4": [ { "insider": "HUANG JEN HSUN", "title": "President and CEO", "transactionDate": "2026-03-28", "transactionCode": "S", "transactionType": "sell", "shares": 100000, "pricePerShare": 142.30, "valueUsd": 14230000 } // ... ], "recentEightK": [ { "filingDate": "2026-03-20", "items": ["2.02", "7.01", "9.01"], "itemMeanings": ["Results of Operations and Financial Condition", "Regulation FD Disclosure", "Financial Statements and Exhibits"] } // ... ], "recent10QK": [ { "form": "10-K", "filingDate": "2026-02-26", "reportDate": "2026-01-26" }, { "form": "10-Q", "filingDate": "2025-11-19", "reportDate": "2025-10-26" } ], "lookbackDays": 180, "lookbackStart": "2025-10-18", "edgarUrl": "https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0001045810&type=&dateb=&owner=include&count=40", "extractedAt": "2026-04-16T01:30:00.000Z" } ```` ### Pricing - **Actor start**: $0.05 per run - **Per ticker report generated**: $0.25 per ticker This is intentionally priced higher than our atomic actors (Form 4 $0.02/tx, 8-K $0.05/filing) because one call here replaces running 3-4 separate actors plus merging/computing downstream. You're paying for the synthesis, not just the raw data. **Example costs:** - Analyze one ticker → $0.30 - Daily scan of top 20 tech stocks → $5.05 per run = ~$150/month for a daily watchlist - Weekly deep-scan of S\&P 500 → $125 per run = ~$500/month for portfolio coverage - Full signal scan of Russell 2000 → $500 per run For comparison: Bloomberg Terminal is $25,000-35,000/year. FactSet is $12,000+/year. One analyst seat. Free Apify tier members get $5/month in platform credits, which covers ~16 ticker reports per month. ### Honest limitations - **Signals are heuristic, not ML-trained.** The rules are simple (net insider buy = bullish, cluster sell = bearish). This matches institutional convention but is NOT a trained model. You'll outperform it with a proper ML model trained on historical returns. - **Only US-listed public companies.** Companies must have a SEC CIK. Foreign issuers with ADRs work; private companies don't. - **No 13F or 13D integration (yet).** Use the dedicated `sec-13f-holdings-tracker` and `sec-13d-activist-filings` actors for that. A future version could combine all five. - **No earnings-call transcript parsing.** 8-K Item 2.02 filings reference earnings, but we don't parse the actual transcripts. Use the EDGAR Filing Monitor for that. - **Form 4 parsing is LIMITED to non-derivative transactions** (common stock buys/sells). Derivative exercises (M code) count as "option-exercise" but we don't project them into a separate category for signals. - **Lookback is capped at 10 years (3,650 days)**. SEC submissions API only returns recent filings in the "recent" block; older filings require a paginated call we don't currently make. ### Tips for alpha extraction - **Run daily before market open** on your watchlist to catch overnight filings → position accordingly - **Schedule after-hours runs** to catch late-filing 8-Ks (many earnings 8-Ks file at 4:05pm ET) - **Use longer lookback (180-365 days)** for small caps where insider activity clusters are rare - **Combine with sec-13f-holdings-tracker**: STRONGLY\_BEARISH aggregator signal + hedge fund exiting = high-conviction short - **Combine with sec-13d-activist-filings**: BULLISH aggregator signal + new activist 13D = double-confirmation buy - **Filter for `signalLabel: STRONGLY_BULLISH`** across your watchlist to surface high-conviction longs ### Related actors in my portfolio For users who want atomic access to the same data: - **sec-form4-insider-trades** — raw Form 4 transactions - **sec-edgar-filing-monitor** — general SEC filing monitor (8-K, 10-Q, 10-K, S-1, etc.) - **sec-13f-holdings-tracker** — institutional holdings per fund - **sec-13d-activist-filings** — activist 5%+ positions - **clinicaltrials-pipeline-monitor** — biotech pipeline (for signal-scoring biotech) This aggregator is the **top of the stack** — one call that reuses the same SEC plumbing with computed signals. ### Source SEC EDGAR submissions API + Archives (both free, public, no auth). The actor respects SEC's 10 req/sec rate limit automatically. ### License MIT. SEC data is in the public domain. ### Disclaimer **For research only.** Past performance doesn't predict future returns. Insider activity signals are statistical biases, not guarantees. Don't trade real money on one signal. Always consult a licensed financial advisor. # Actor input Schema ## `tickers` (type: `array`): Stock symbols to pull unified intelligence for (e.g. \['TSLA', 'NVDA', 'AAPL', 'PFE']). Empty = Tesla default. ## `lookbackDays` (type: `integer`): How far back to pull filings. 30 = last month, 90 = last quarter, 365 = last year. ## `maxForm4Filings` (type: `integer`): Cap on insider trading filings to fetch. 20 = recent representative sample. ## `max8KFilings` (type: `integer`): Cap on 8-K filings listed. ## `max10QK` (type: `integer`): Cap on periodic financial reports listed. ## `parseForm4Details` (type: `boolean`): Deep-parse each Form 4 filing to extract insider names, shares, prices, transaction types. Slower but richer data. ## `computeSignals` (type: `boolean`): Compute bull/bear signal scores from the raw filings (net insider buys vs sells, filing velocity, etc.). ## `proxyConfiguration` (type: `object`): Optional Apify Proxy. SEC EDGAR is friendly to direct access. ## Actor input object example ```json { "tickers": [ "TSLA" ], "lookbackDays": 90, "maxForm4Filings": 20, "max8KFilings": 15, "max10QK": 5, "parseForm4Details": true, "computeSignals": true, "proxyConfiguration": { "useApifyProxy": false } } ``` # Actor output Schema ## `dataset` (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": [ "TSLA" ] }; // Run the Actor and wait for it to finish const run = await client.actor("wiry_kingdom/stock-alpha-aggregator").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": ["TSLA"] } # Run the Actor and wait for it to finish run = client.actor("wiry_kingdom/stock-alpha-aggregator").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": [ "TSLA" ] }' | apify call wiry_kingdom/stock-alpha-aggregator --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=wiry_kingdom/stock-alpha-aggregator", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Stock Alpha Signal Aggregator - Unified SEC Intelligence", "description": "Unified intelligence report per ticker. Combines Form 4 insider trades, 8-K material events, 10-Q/K financial filings, and computed bull/bear signal scores. One call per stock = complete SEC picture. Free official SEC EDGAR API. Replaces $25k/yr Bloomberg Terminal.", "version": "0.1", "x-build-id": "JOJCnc158htECoGlX" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/wiry_kingdom~stock-alpha-aggregator/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-wiry_kingdom-stock-alpha-aggregator", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/wiry_kingdom~stock-alpha-aggregator/runs": { "post": { "operationId": "runs-sync-wiry_kingdom-stock-alpha-aggregator", "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/wiry_kingdom~stock-alpha-aggregator/run-sync": { "post": { "operationId": "run-sync-wiry_kingdom-stock-alpha-aggregator", "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 to analyze", "type": "array", "description": "Stock symbols to pull unified intelligence for (e.g. ['TSLA', 'NVDA', 'AAPL', 'PFE']). Empty = Tesla default.", "default": [ "TSLA" ], "items": { "type": "string" } }, "lookbackDays": { "title": "Lookback window (days)", "minimum": 7, "maximum": 3650, "type": "integer", "description": "How far back to pull filings. 30 = last month, 90 = last quarter, 365 = last year.", "default": 90 }, "maxForm4Filings": { "title": "Max Form 4 filings to parse per ticker", "minimum": 0, "maximum": 200, "type": "integer", "description": "Cap on insider trading filings to fetch. 20 = recent representative sample.", "default": 20 }, "max8KFilings": { "title": "Max 8-K (material events) per ticker", "minimum": 0, "maximum": 100, "type": "integer", "description": "Cap on 8-K filings listed.", "default": 15 }, "max10QK": { "title": "Max 10-Q / 10-K filings per ticker", "minimum": 0, "maximum": 50, "type": "integer", "description": "Cap on periodic financial reports listed.", "default": 5 }, "parseForm4Details": { "title": "Parse Form 4 XML for full transaction detail", "type": "boolean", "description": "Deep-parse each Form 4 filing to extract insider names, shares, prices, transaction types. Slower but richer data.", "default": true }, "computeSignals": { "title": "Compute aggregate alpha signals", "type": "boolean", "description": "Compute bull/bear signal scores from the raw filings (net insider buys vs sells, filing velocity, etc.).", "default": true }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional Apify Proxy. SEC EDGAR is friendly to direct access.", "default": { "useApifyProxy": 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 } } } } } } } } } } ```