# Stock Earnings Calendar Tracker (Nasdaq, EPS consensus) (`gochujang/stock-earnings-tracker`) Actor Upcoming earnings calendar from Nasdaq for next N days: ticker, company, BMO/AMC timing, consensus EPS estimate, number of analyst estimates, prior-year EPS, fiscal quarter end, market cap. Telegram alerts on upcoming. No API key required. - **URL**: https://apify.com/gochujang/stock-earnings-tracker.md - **Developed by:** [Hojun Lee](https://apify.com/gochujang) (community) - **Categories:** Developer tools, Automation, Other - **Stats:** 6 total users, 4 monthly users, 94.3% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 Earnings Calendar Tracker > Upcoming earnings calendar from **Nasdaq** for next N days: ticker, company, BMO/AMC timing, consensus EPS estimate, analyst count, prior-year EPS, fiscal quarter end, market cap. **No API key.** --- ### Why this exists Earnings season drives 30%+ of single-stock price moves. The free calendars on Yahoo / Investing.com require scraping that breaks weekly. Paid feeds (Zacks, Estimize) charge $100-$500/mo. This actor wraps Nasdaq's free public earnings JSON endpoint with clean filtering: by date range, ticker, market cap, sort order, and Telegram digest. --- ### What you get per row | Field | Example | Notes | |---|---|---| | `report_date` | `2026-06-10` | ISO date | | `symbol` | `ORCL` | ticker | | `name` | `Oracle Corporation` | | | `timing` | `AMC` | BMO/AMC/TNS | | `eps_forecast` | `1.58` | consensus EPS estimate | | `num_estimates` | `11` | analyst count | | `last_year_eps` | `1.35` | prior-year same quarter | | `last_year_report_date` | `6/11/2025` | | | `fiscal_quarter_ending` | `May/2026` | | | `market_cap_usd` | `609,204,063,720` | | `timing`: - **BMO** — Before Market Open - **AMC** — After Market Close - **TNS** — Time Not Supplied --- ### Use cases 1. **Position planning** — Don't get caught holding through an earnings call you forgot about 2. **Options strategies** — Filter for high-IV names reporting this week 3. **Earnings momentum** — Pull a watchlist of large caps reporting + their consensus 4. **Sector rotation** — See when a whole sector (e.g. retail) is about to report 5. **Macro context** — Weight aggregate consensus EPS growth by market cap as a top-down growth proxy --- ### Quick start #### Default — next 7 days, all reporters ```json {} ```` #### Mega caps only (>$10B), this week ```json { "daysAhead": 7, "minMarketCapUsd": 10000000000, "sortBy": "mcap_desc" } ``` #### Track specific tickers ```json { "daysAhead": 30, "symbols": ["NVDA", "AAPL", "MSFT", "TSLA"] } ``` #### Daily digest to Telegram ```json { "daysAhead": 1, "minMarketCapUsd": 5000000000, "alertOnUpcoming": true, "telegramBotToken": "YOUR_BOT_TOKEN", "telegramChatId": "YOUR_CHAT_ID" } ``` *** ### Pricing **Pay-Per-Event**: `$0.001 per earnings row returned.` | Run | Rows | Cost | |---|---|---| | Default (7 days, all) | ~150 | $0.15 | | Today's mega caps | 5–10 | $0.005–0.01 | | 30-day forward calendar | ~700 | $0.70 | *** ### Output sort options | `sortBy` | Description | |---|---| | `date_asc` | Earliest reporters first, market cap tiebreak (default) | | `mcap_desc` | Largest companies first | | `eps_estimate_desc` | Highest EPS estimate first | *** ### Data source [Nasdaq Earnings Calendar JSON](https://www.nasdaq.com/market-activity/earnings) — free public endpoint, US listings. *** ### Related actors (same author) - [SEC EDGAR Filing Tracker](https://apify.com/gochujang/sec-edgar-tracker) — Catch the 8-K when earnings drop - [Insider Trading Tracker](https://apify.com/gochujang/insider-trading-tracker) — CEO/CFO Form 4 around earnings - [Treasury Yield Curve Tracker](https://apify.com/gochujang/treasury-yield-tracker) - [Economic Calendar Tracker](https://apify.com/gochujang/economic-calendar-tracker) — FOMC, CPI, NFP *** ### Feedback A short review helps analysts find it: [Leave a review on Apify Store](https://apify.com/gochujang/stock-earnings-tracker#reviews) # Actor input Schema ## `daysAhead` (type: `integer`): How many days from today to include (1 = today only, 7 = next week). ## `symbols` (type: `array`): Only include these tickers (case-insensitive). Empty = all reporters. ## `minMarketCapUsd` (type: `integer`): Skip companies whose market cap is below this. 0 = no filter. ## `sortBy` (type: `string`): Row order. ## `limit` (type: `integer`): Max earnings rows to return. ## `alertOnUpcoming` (type: `boolean`): Send list of upcoming earnings to Telegram after run. ## `telegramBotToken` (type: `string`): Telegram bot token. ## `telegramChatId` (type: `string`): Chat ID. ## Actor input object example ```json { "daysAhead": 7, "symbols": [], "minMarketCapUsd": 0, "sortBy": "date_asc", "limit": 500, "alertOnUpcoming": false, "telegramChatId": "" } ``` # Actor output Schema ## `dataset` (type: `string`): No description ## `summary` (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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("gochujang/stock-earnings-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 = {} # Run the Actor and wait for it to finish run = client.actor("gochujang/stock-earnings-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 '{}' | apify call gochujang/stock-earnings-tracker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=gochujang/stock-earnings-tracker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Stock Earnings Calendar Tracker (Nasdaq, EPS consensus)", "description": "Upcoming earnings calendar from Nasdaq for next N days: ticker, company, BMO/AMC timing, consensus EPS estimate, number of analyst estimates, prior-year EPS, fiscal quarter end, market cap. Telegram alerts on upcoming. No API key required.", "version": "0.1", "x-build-id": "5TuiITfLVNxU1i2hl" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/gochujang~stock-earnings-tracker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-gochujang-stock-earnings-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/gochujang~stock-earnings-tracker/runs": { "post": { "operationId": "runs-sync-gochujang-stock-earnings-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/gochujang~stock-earnings-tracker/run-sync": { "post": { "operationId": "run-sync-gochujang-stock-earnings-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "daysAhead": { "title": "Days ahead", "minimum": 1, "maximum": 30, "type": "integer", "description": "How many days from today to include (1 = today only, 7 = next week).", "default": 7 }, "symbols": { "title": "Ticker filter", "type": "array", "description": "Only include these tickers (case-insensitive). Empty = all reporters.", "default": [], "items": { "type": "string" } }, "minMarketCapUsd": { "title": "Min market cap (USD)", "minimum": 0, "type": "integer", "description": "Skip companies whose market cap is below this. 0 = no filter.", "default": 0 }, "sortBy": { "title": "Sort by", "enum": [ "date_asc", "mcap_desc", "eps_estimate_desc" ], "type": "string", "description": "Row order.", "default": "date_asc" }, "limit": { "title": "Max rows", "minimum": 1, "maximum": 2000, "type": "integer", "description": "Max earnings rows to return.", "default": 500 }, "alertOnUpcoming": { "title": "Telegram alert", "type": "boolean", "description": "Send list of upcoming earnings to Telegram after run.", "default": false }, "telegramBotToken": { "title": "Telegram Bot Token", "type": "string", "description": "Telegram bot token." }, "telegramChatId": { "title": "Telegram Chat ID", "type": "string", "description": "Chat ID.", "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 } } } } } } } } } } ```