# Stock Dividend Calendar Scraper (`scrapemint/stock-dividend-calendar-scraper`) Actor

Upcoming US stock dividends, keyless: ex-dividend, record, payment and announcement dates with the declared rate, indicated annual dividend and days until the ex-dividend date. Filter by ticker or minimum rate, look 90 days ahead, and use monitor mode for newly announced dividends only.

- **URL**: https://apify.com/scrapemint/stock-dividend-calendar-scraper.md
- **Developed by:** [Ken M](https://apify.com/scrapemint) (community)
- **Categories:** Business, News
- **Stats:** 2 total users, 1 monthly users, 100.0% 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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 Dividend Calendar Scraper

Get the upcoming US dividend calendar as clean JSON: **ex-dividend, record, payment and announcement dates** with the declared cash rate, for a date range or your own ticker watchlist.

No login, no API key, no proxy. The actor reads keyless public JSON, so runs are fast and cheap.

### What you get

One row per company per ex-dividend date.

| Field | Description |
| --- | --- |
| `symbol` | Ticker |
| `companyName` | Company name as Nasdaq reports it |
| `exDividendDate` | Buy before this date to receive the dividend |
| `recordDate` | Date the holder of record is determined |
| `paymentDate` | Date the cash is paid out |
| `announcementDate` | Date the dividend was declared |
| `dividendRate` | Declared cash amount per share, or `null` when Nasdaq reports none |
| `indicatedAnnualDividend` | Annualised dividend per share, or `null` |
| `daysUntilExDividend` | Days from the run date to the ex-dividend date |
| `scrapedAt` | Run timestamp, ISO 8601 |

A missing value stays `null`. It is never reported as `0`, because a dividend of zero is a different claim from a dividend Nasdaq did not report.

### Input

| Field | Description |
| --- | --- |
| `dateFrom` | First ex-dividend date `YYYY-MM-DD` (default: today) |
| `dateTo` | Last ex-dividend date `YYYY-MM-DD` (default: +30 days, range capped at 90 days) |
| `tickers` | Optional watchlist, e.g. `["KO","PG","JNJ"]`. Empty = whole market |
| `minDividendRate` | Skip dividends below this cash amount per share, e.g. `0.50` |
| `newOnly` | Monitor mode: emit only dividends not seen in earlier runs |
| `maxRows` | Stop after N rows (default 500) |

#### Monitor mode

Set `newOnly` to `true` and put the actor on a daily schedule to get a feed of **newly announced** dividends only. Dividends already returned by a previous run are remembered and skipped, so a quiet day costs nothing.

### Example

```json
{ "dateFrom": "2026-08-06", "dateTo": "2026-08-20", "tickers": ["KO", "PG"] }
```

```json
{
  "symbol": "BMRC",
  "companyName": "Bank of Marin Bancorp Common Stock",
  "exDividendDate": "2026-08-06",
  "recordDate": "2026-08-06",
  "paymentDate": "2026-08-13",
  "announcementDate": "2026-07-23",
  "dividendRate": 0.25,
  "indicatedAnnualDividend": 1.0,
  "daysUntilExDividend": 1,
  "scrapedAt": "2026-08-05T13:20:41.512Z"
}
```

### Who it's for

Income investors tracking when to buy for the next payout, dividend capture traders working ex-dividend dates, portfolio and fintech apps that display an income calendar, and quants feeding ex-dividend dates into backtests and total return models.

### Pricing

Pay per dividend row. The first 2 rows of every run are free so you can validate the output before you pay.

### Notes

- Dividend rows appear on the calendar as companies declare them, so a date far in the future will fill in over time. Re-run closer to the date for the complete picture.
- The date range is capped at 90 days per run to keep runs fast.

# Actor input Schema

## `dateFrom` (type: `string`):

First ex-dividend date to include, as YYYY-MM-DD. Leave empty to start from today.

## `dateTo` (type: `string`):

Last ex-dividend date to include, as YYYY-MM-DD. Leave empty for 30 days after the start date. The range is capped at 90 days.

## `tickers` (type: `array`):

Only return these symbols. Leave empty to get every company with a dividend in the date range.

## `minDividendRate` (type: `string`):

Skip dividends below this cash amount per share, for example 0.50. Rows where Nasdaq reports no rate are skipped when this is set. Leave empty for no filter.

## `newOnly` (type: `boolean`):

Remember dividends already returned and emit only ones not seen before. Run this on a daily schedule for a clean feed of newly announced dividends. Quiet runs cost nothing.

## `maxRows` (type: `integer`):

Stop after this many rows.

## Actor input object example

```json
{
  "tickers": [],
  "newOnly": false,
  "maxRows": 500
}
```

# Actor output Schema

## `rows` (type: `string`):

Ticker, company name, ex-dividend, record, payment and announcement dates, the declared cash rate per share and the indicated annual dividend.

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "dateFrom": "",
    "dateTo": "",
    "tickers": [],
    "minDividendRate": "",
    "maxRows": 500
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapemint/stock-dividend-calendar-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "dateFrom": "",
    "dateTo": "",
    "tickers": [],
    "minDividendRate": "",
    "maxRows": 500,
}

# Run the Actor and wait for it to finish
run = client.actor("scrapemint/stock-dividend-calendar-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "dateFrom": "",
  "dateTo": "",
  "tickers": [],
  "minDividendRate": "",
  "maxRows": 500
}' |
apify call scrapemint/stock-dividend-calendar-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapemint/stock-dividend-calendar-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/UxWpooxKgw1GXLde2/builds/U5sVzzJ9CfTPDjeCp/openapi.json