# 🔀 Corporate Actions — Splits, Spinoffs, M\&A, Tender Offers (`nexgendata/corporate-actions-tracker`) Actor Track upcoming/recent stock splits, reverse splits, special dividends, spinoffs, mergers, acquisitions, tender offers. Effective dates, deal values, consideration, status. Bloomberg corporate actions alternative for special-situations desks and M\&A arb funds. Pay-per-result. - **URL**: https://apify.com/nexgendata/corporate-actions-tracker.md - **Developed by:** [NexGenData](https://apify.com/nexgendata) (community) - **Categories:** Business - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $150.00 / 1,000 corporate action 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 ## 🔀 Corporate Actions — Splits, Spinoffs, M&A, Tender Offers **Bloomberg corporate-actions desk alternative.** Pay-per-result tracking of upcoming and recent stock splits, reverse splits, special dividends, spinoffs, mergers, acquisitions, and tender offers. Built for special-situations desks, M&A arbitrage funds, corporate finance teams, and retail traders following the calendar of structural events that move single names independently of macro. ### 📊 Sample Output [![🔀 Corporate Actions — Splits, Spinoffs, M&A, Tender Offers sample output — 🔀 Corporate Actions — Splits, Spinoffs, M&A, Tender Offers, premium API, JSON output, NexGenData premium dataset for analysts](https://api.apify.com/v2/key-value-stores/8gLgXMBveEI1tTz1z/records/corporate-actions-tracker-output.png)](https://apify.com/nexgendata/corporate-actions-tracker) Corporate actions are where the alpha hides for special-situations capital. A 10-for-1 split announcement can compress option premium for weeks. A spinoff distribution creates a brand-new ticker with no analyst coverage. An announced merger trades to a deal spread you can model directly. A reverse split is often a delisting precursor. This actor surfaces every one of those events in a single typed dataset row — with the deal value, consideration mechanics, status, and effective date that you need to build a position. --- ### What this actor returns For every corporate action in coverage, a typed record: | Field | Meaning | | --- | --- | | `symbol` | Primary common-share ticker of the issuer | | `company_name` | Legal entity name | | `sector` | GICS-style sector label when known | | `action_type` | `Stock Split` / `Reverse Split` / `Special Dividend` / `Spinoff` / `Merger` / `Acquisition` / `Tender Offer` | | `ratio` | E.g. `10-for-1`, `1-for-20` (reverse), `3-for-2`; `null` for non-splits | | `current_price` | Live price snapshot from Yahoo Finance for the issuer | | `market_cap_usd` | Market cap (USD) at announcement; useful for filtering large-cap vs penny stock | | `effective_date` | Split effective / ex-distribution / deal-close date (ISO-8601) | | `announcement_date` | Date the action was publicly announced (often 8-K filing date) | | `target_company` | M&A target name (for `Merger`, `Acquisition`, `Tender Offer`) | | `acquirer` | M&A acquirer name | | `deal_value_usd` | Total transaction value (M&A) or aggregate cash distributed (special div) | | `consideration` | Free-text breakdown — `$X cash`, `$X cash + Y shares`, all-stock ratios | | `status` | `Announced` / `Approved` / `Completed` / `Cancelled` / `Pending Shareholder Vote` | | `days_to_effective` | Computed days from today to `effective_date` (negative = past) | | `data_source` | Provenance — curated baseline, SEC EDGAR 8-K, or both | --- ### Why corporate actions desks pay for this | User | Job-to-be-done | | --- | --- | | Special situations desk | Build a calendar of upcoming splits, spinoffs, and reorganizations to front-run index reweights | | M&A arbitrage fund | Track every announced deal — measure spread vs. deal value daily, monitor `status` for breakages | | Spinoff fund (Greenblatt-style) | Pre-build positions in distributing parents before ex-distribution; pick up forced-sellers' "stub" newco shares | | Corporate finance / IR | Watch peers' splits, special divs, buybacks for benchmarking board recommendations | | Index arb / passive trader | Anticipate index rebalances triggered by share-count changes from splits and spinoffs | | Retail trader | Avoid getting reverse-split out of a position; spot the next NVDA-style 10-for-1 catalyst | | Quant strategy researcher | Backtest "post-split drift" and "spinoff alpha" signals with a clean, structured dataset | | Options market maker | Mark vol surfaces accurately when the underlying is about to split or be cash-acquired | --- ### How it works The actor combines three signals: 1. **SEC EDGAR full-text search of 8-K filings.** Six parallel queries scan the trailing 90 days of 8-K filings for the phrases `"stock split"`, `"reverse stock split"`, `"special dividend"`, `"spin-off"`, `"merger agreement"`, and `"tender offer"`. Each hit is deduplicated to issuer level and tagged with the matched action type. This is the freshest signal — most material corporate actions are 8-K-disclosable, so we catch them within hours of announcement. 2. **Curated baseline of publicly-announced corporate actions.** Anchored on the high-profile, well-documented names that special-situations capital actually trades: NVDA 10-for-1, WMT 3-for-1, AVGO 10-for-1, CMG 50-for-1, LRCX 10-for-1, MELI 2-for-1, ASML 3-for-1, GE Vernova spinoff, Solventum spinoff, Veralto spinoff, Western Digital / Sandisk separation, Costco $15 special, Phillips 66 $1.00 special, Microsoft / Activision, Cisco / Splunk, Synopsys / ANSYS, Chevron / Hess, Exxon / Pioneer, HPE / Juniper, Skydance / Paramount, Tapestry / Capri, Alaska / Hawaiian. Plus the small-cap reverse-split tape (MULN, FFIE, BFLY, NKLA, PLUG) where the action signal often anticipates a delisting risk. 3. **Yahoo Finance** — `query1.finance.yahoo.com/v8/finance/chart/{symbol}` returns the live `regularMarketPrice` for every survivor, so `current_price` is timely rather than stale. The curated baseline guarantees a non-empty result even when SEC EDGAR throttles or returns a 4xx; the EDGAR layer enriches the result with brand-new announcements the curated list hasn't yet been refreshed to include. --- ### Input | Field | Type | Default | Description | | --- | --- | --- | --- | | `limit` | int | 50 | Max records to return (1–500) | | `action_types` | array | `[]` (all) | Filter by one or more of `Stock Split`, `Reverse Split`, `Special Dividend`, `Spinoff`, `Merger`, `Acquisition`, `Tender Offer` | | `date_range` | enum | `all` | `upcoming` / `recent_30d` / `recent_90d` / `all` — window over `effective_date` | | `min_market_cap_billion` | number | 0 | Issuer market-cap floor in USD billions (0 disables) | | `sector` | string | `""` | Case-insensitive substring match against the `sector` field | #### Example inputs **Every announced M&A deal still pending close (the deal-arb worklist):** ```json { "action_types": ["Merger", "Acquisition"], "date_range": "upcoming", "limit": 100 } ```` **Upcoming forward splits, large-caps only (index rebalance front-running):** ```json { "action_types": ["Stock Split"], "min_market_cap_billion": 10, "date_range": "upcoming" } ``` **Reverse splits in the last 30 days (delisting-watch screen):** ```json { "action_types": ["Reverse Split"], "date_range": "recent_30d", "limit": 100 } ``` **Spinoffs only, all dates (Greenblatt setup):** ```json { "action_types": ["Spinoff"], "date_range": "all" } ``` **Healthcare-sector special dividends:** ```json { "action_types": ["Special Dividend"], "sector": "Healthcare" } ``` *** ### Pricing Pay-per-event. You pay only for what is delivered. | Event | Price | | --- | --- | | Actor start | **$0.01** (one-time per run) | | Corporate action record | **$0.15** per record returned | Worked examples: - 25 records returned: `$0.01 + 25 × $0.15 = $3.76` - 100 records returned: `$0.01 + 100 × $0.15 = $15.01` - 500 records (max): `$0.01 + 500 × $0.15 = $75.01` At $0.15/record, the actor sits in the mid-premium tier of NexGenData's catalog — anchored to the fact that every record encodes a discrete, dated, often-actionable trading signal with deal value, consideration, and status all in one row. *** ### Comparison vs. institutional terminals | Capability | This actor | Bloomberg CAEV | FactSet | Refinitiv DataScope | S\&P Capital IQ | Mergermarket | | --- | --- | --- | --- | --- | --- | --- | | Splits & reverse splits | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | | Spinoffs | ✅ | ✅ | ✅ | ✅ | ✅ | partial | | Special dividends | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | | Announced M\&A with deal value | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | Tender offers | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | Consideration breakdown (cash/stock) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | Status tracking (Announced/Approved/Cancelled) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | Effective-date computed `days_to_effective` | ✅ | ✅ | partial | partial | ❌ | ❌ | | Live price snapshot | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | | API access | ✅ REST | ✅ B-API | ✅ FQL | ✅ DSO | ✅ Xpressfeed | ❌ | | Setup cost | $0 | $24K+/year/seat | $12K+/year/seat | $20K+/year | $30K+/year | $14K+/year | | Per-record cost | **$0.15** | bundled in seat | bundled in seat | bundled in seat | bundled in seat | bundled in seat | | Time to first data | <60s | weeks | weeks | weeks | weeks | weeks | | Contract / minimum | None | annual + LOB | annual | annual | annual | annual | For a special-situations desk that just wants to monitor the live M\&A pipeline and the splits/spinoffs calendar without committing to a six-figure terminal contract, pay-per-record at $0.15 wins on every dimension that matters: latency, friction, and elasticity. *** ### Status semantics Status values are the same vocabulary deal-arb desks already use: - **Announced** — definitive agreement or board-approved announcement has been made; deal terms are public, but no shareholder vote yet. - **Pending Shareholder Vote** — proxy filed; vote scheduled. - **Approved** — shareholder vote has cleared, awaiting regulatory close. - **Completed** — action has been effective; security has split, spun off, or been acquired. - **Cancelled** — definitive agreement terminated (e.g. Tapestry/Capri). For splits and spinoffs the same vocabulary applies — `Announced` (board has approved subject to record date), `Approved` (record date set), `Completed` (effective date passed). *** ### Data freshness & limits - **SEC EDGAR layer** refreshes every run — typical hit latency from 8-K filing to actor record is minutes-to-hours. - **Curated baseline** is versioned with the actor — refreshes ship with each new build. - **Yahoo Finance prices** are best-effort; throttling occasionally drops `current_price` to `null`, but every other field still ships. The actor is rate-friendly: ≤6 concurrent Yahoo requests per run, gentle SEC user agent, and graceful fallback when any one source 4xx/5xxs. *** ### Sister actors in the NexGenData special-situations stack This actor is one piece of a larger event-driven toolkit. The natural pairings: - **[IPO Tracker](https://apify.com/nexgendata/ipo-tracker)** — recent + upcoming IPOs across NYSE/NASDAQ with lockup expirations and post-IPO performance. Pair with this actor to follow a company from S-1 → IPO → first split/spinoff/M\&A event. - **[SPAC Tracker](https://apify.com/nexgendata/spac-tracker)** — active SPACs with trust values, deadlines, announced mergers, redemption rates. SPACs that complete a de-SPAC merger become tickers that this corporate-actions actor then tracks for follow-on splits and spinoffs. - **[SEC Form 8-K Material Events Scraper](https://apify.com/nexgendata/sec-form-8k-material-events-scraper)** — full 8-K corpus with item-level tagging. Corporate Actions Tracker is a tightly-typed projection of the M\&A/restructuring slice of 8-K; the 8-K scraper gives you the rest (Item 1.01 entry into agreement, Item 2.01 completion of acquisition, Item 5.07 vote results). - **[SEC Form 13F Holdings Tracker](https://apify.com/nexgendata/sec-form-13f-holdings-tracker)** — quarterly institutional positions. Cross-reference whose 13F shows fresh accumulation in a name right before its split or spinoff. - **[Short Interest Tracker](https://apify.com/nexgendata/short-interest-tracker)** — bi-weekly NYSE/NASDAQ short interest. Tracks the squeeze setups around announced M\&A breakages and reverse-split forced-buying. - **[Finance MCP Server](https://apify.com/nexgendata/finance-mcp-server)** — Claude/ChatGPT-native MCP wrapping the entire NexGenData finance stack including this actor. Ask in natural language: "show me every upcoming spinoff with market cap over $5B." *** ### API quickstart ```bash TOKEN=apify_api_xxxxxxxxxxxxxxxxxxxxxxxxxxxxx curl -X POST "https://api.apify.com/v2/acts/nexgendata~corporate-actions-tracker/run-sync-get-dataset-items?token=$TOKEN" \ -H "Content-Type: application/json" \ -d '{ "limit": 50, "action_types": ["Merger", "Acquisition"], "date_range": "upcoming", "min_market_cap_billion": 1.0 }' ``` Output is a JSON array of records as documented above. Add `?format=csv` to pipe directly into a spreadsheet, or use the Apify Python / JS SDK clients. ```python from apify_client import ApifyClient client = ApifyClient("apify_api_xxxxxxxxxxxxxxxxxxxxxxxxxxxxx") run = client.actor("nexgendata/corporate-actions-tracker").call( run_input={"action_types": ["Spinoff"], "date_range": "upcoming"} ) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item["symbol"], item["action_type"], item["effective_date"], item["consideration"]) ``` *** ### FAQ **Are the prices and deal values guaranteed accurate?**\ The curated baseline references public 8-K filings and press releases — accurate at point of capture. Live prices come from Yahoo Finance, which is reliable but not authoritative; for trade execution you should always reconcile against your prime broker's data. The actor's job is signal discovery, not order routing. **How do I get only the freshest announcements?**\ Filter `date_range="upcoming"` and sort the dataset by `announcement_date` descending. The `data_source` field will show `sec_edgar_8k` for records that came directly from the live EDGAR query. **Can I run this on a schedule?**\ Yes — every Apify actor supports cron-style schedules. A daily 6am run with `action_types=["Merger","Acquisition","Spinoff"]` and `date_range="recent_30d"` gives you a fresh deal-arb worklist every morning for less than $5/day. **What if a company announces a corporate action that's not in the curated baseline?**\ The EDGAR layer will surface it as soon as the 8-K is filed. The curated baseline gets refreshed in each new actor build (subscribe to the Apify build feed to be notified). **Can I get historical splits and spinoffs going back 10 years?**\ The curated baseline includes high-profile actions back to 2020. For deeper history, pair this actor with the SEC Form 8-K Material Events Scraper and filter Item 1.02, 2.01, or 5.03 items. **Do you cover non-US issuers?**\ Coverage is strongest for US-listed names (NYSE, NASDAQ) including foreign issuers with US ADRs (ASML, MELI, etc.). Pure-foreign listings (LSE-only, TSE-only) are not the primary focus of this actor. *** ### Build & deploy This actor is private. Contact NexGenData for access, white-label, or higher-volume custom data feeds. Built on Apify's Python SDK, packaged as a standard Docker actor. The full source includes: - `src/main.py` — orchestration: SEC EDGAR fetch, curated merge, Yahoo enrichment, filter, push - `src/__main__.py` — entrypoint - `.actor/actor.json` — actor spec - `.actor/input_schema.json` — input schema - `Dockerfile`, `requirements.txt` Open source contributions welcome via the NexGenData GitHub. *** ### About NexGenData NexGenData operates a fleet of pay-per-result financial data actors on Apify covering global equities (50+ exchanges), ETF holdings, SEC filings, options flow, earnings calendars, dividend aristocrats, short interest, IPOs, SPACs, and now corporate actions. The thesis is simple: institutional terminal data shouldn't cost six figures, and pay-per-result pricing aligns vendor incentives with user signal. **Try the full NexGenData catalog and get an affiliate discount:** # Actor input Schema ## `limit` (type: `integer`): Maximum number of corporate action records to return. Higher limits widen coverage across splits, spinoffs, mergers, acquisitions, special dividends, and tender offers. Defaults to 50. ## `action_types` (type: `array`): Filter by one or more corporate action types. Leave empty to return every type. Choose 'Stock Split' / 'Reverse Split' for index rebalancing trades, 'Spinoff' / 'Merger' / 'Acquisition' / 'Tender Offer' for M\&A arbitrage, 'Special Dividend' for income strategies. ## `date_range` (type: `string`): Window for the corporate action's effective/ex-date. 'upcoming' returns actions with effective\_date in the future, 'recent\_30d' returns those that took effect in the last 30 days, 'recent\_90d' uses a 90-day lookback, 'all' disables the date filter. ## `min_market_cap_billion` (type: `number`): Only include corporate actions where the issuer's market cap is at or above this floor (in USD billions). Set 1.0 to focus on mid-/large-caps, 10.0 for large/mega-caps, 0 to disable. Records missing market cap pass when filter is disabled. ## `sector` (type: `string`): Optional case-insensitive substring match against the sector field (e.g. 'Technology', 'Healthcare', 'Financial', 'Energy'). Leave blank to return all sectors. ## Actor input object example ```json { "limit": 50, "action_types": [], "date_range": "all", "min_market_cap_billion": 0, "sector": "" } ``` # 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": 50, "action_types": [], "date_range": "all", "min_market_cap_billion": 0, "sector": "" }; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/corporate-actions-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": 50, "action_types": [], "date_range": "all", "min_market_cap_billion": 0, "sector": "", } # Run the Actor and wait for it to finish run = client.actor("nexgendata/corporate-actions-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": 50, "action_types": [], "date_range": "all", "min_market_cap_billion": 0, "sector": "" }' | apify call nexgendata/corporate-actions-tracker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/corporate-actions-tracker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "🔀 Corporate Actions — Splits, Spinoffs, M&A, Tender Offers", "description": "Track upcoming/recent stock splits, reverse splits, special dividends, spinoffs, mergers, acquisitions, tender offers. Effective dates, deal values, consideration, status. Bloomberg corporate actions alternative for special-situations desks and M&A arb funds. Pay-per-result.", "version": "0.0", "x-build-id": "b2Q2j7Yl2rWab0un6" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~corporate-actions-tracker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-corporate-actions-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~corporate-actions-tracker/runs": { "post": { "operationId": "runs-sync-nexgendata-corporate-actions-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~corporate-actions-tracker/run-sync": { "post": { "operationId": "run-sync-nexgendata-corporate-actions-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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 corporate action records", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of corporate action records to return. Higher limits widen coverage across splits, spinoffs, mergers, acquisitions, special dividends, and tender offers. Defaults to 50.", "default": 50 }, "action_types": { "title": "Action types filter", "uniqueItems": true, "type": "array", "description": "Filter by one or more corporate action types. Leave empty to return every type. Choose 'Stock Split' / 'Reverse Split' for index rebalancing trades, 'Spinoff' / 'Merger' / 'Acquisition' / 'Tender Offer' for M&A arbitrage, 'Special Dividend' for income strategies.", "items": { "type": "string", "enum": [ "Stock Split", "Reverse Split", "Special Dividend", "Spinoff", "Merger", "Acquisition", "Tender Offer" ] }, "default": [] }, "date_range": { "title": "Date range", "enum": [ "upcoming", "recent_30d", "recent_90d", "all" ], "type": "string", "description": "Window for the corporate action's effective/ex-date. 'upcoming' returns actions with effective_date in the future, 'recent_30d' returns those that took effect in the last 30 days, 'recent_90d' uses a 90-day lookback, 'all' disables the date filter.", "default": "all" }, "min_market_cap_billion": { "title": "Minimum market cap (USD billions)", "minimum": 0, "maximum": 3000, "type": "number", "description": "Only include corporate actions where the issuer's market cap is at or above this floor (in USD billions). Set 1.0 to focus on mid-/large-caps, 10.0 for large/mega-caps, 0 to disable. Records missing market cap pass when filter is disabled.", "default": 0 }, "sector": { "title": "Sector filter", "type": "string", "description": "Optional case-insensitive substring match against the sector field (e.g. 'Technology', 'Healthcare', 'Financial', 'Energy'). Leave blank to return all sectors.", "default": "" } } }, "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 } } } } } } } } } } ```