# Dividend Stock Screener — yield & value scanner (`agent_muse/dividend-stock-screener`) Actor

Screen dividend stocks by TTM yield, 52-week position and valuation — price, payouts, yield and distance from highs for any ticker list. API-backed, no scraping. Not financial advice.

- **URL**: https://apify.com/agent\_muse/dividend-stock-screener.md
- **Developed by:** [John Israel Lofamia](https://apify.com/agent_muse) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $5.00 / 1,000 results

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Dividend Stock Screener — yield & value scanner

**Find the income in the market.** Point this Actor at any list of stock tickers and get back a clean, ranked table: current price, trailing-twelve-month dividends, dividend yield, 52-week high/low, distance from the high, and P/E — sorted by yield, highest first.

### Who is this for?

**Income investors** — Stop opening twenty tabs. Screen your watchlist in one run: which dividend payers actually pay, which are sitting near 52-week lows, and which yields clear your bar.

**Value hunters** — Combine yield with `pct_off_52w_high`: a 6% yielder trading 25% below its high reads very differently from one at the top.

**Advisors & bloggers** — Re-run on a schedule and publish a fresh "top dividend yields this week" table from the dataset.

### What it does

For each ticker, the Actor queries the Yahoo Finance chart API (official, keyless — no HTML scraping, nothing to break):

- \~1 year of daily closes → **52-week high / low** and **% off the high**
- Dividend events over the trailing 12 months → **TTM dividends** → **yield = TTM / price**
- Trailing **P/E** when Yahoo reports one

Rows are sorted by `dividend_yield_pct` descending. Tickers that can't be screened (delisted, typo) come back as graceful `error` rows instead of crashing the run.

### Inputs

- **Tickers** (default: a 26-stock dividend-aristocrat watchlist — O, JNJ, PG, KO, PEP, MMM, VZ, XOM, CVX, ABBV, MRK, IBM, CSCO, WMT, MCD, HD, LOW, ADP, AFL, ED, GPC, KMB, MDT, NUE, PPG, TGT) — replace with any symbols you like.
- **Minimum dividend yield %** (default 0) — e.g. `4` keeps only 4%+ yielders.
- **Max results** (default 50) — highest yield first.

### Example output

| ticker | company\_name | price | ttm\_dividends\_usd | dividend\_yield\_pct | pct\_off\_52w\_high | pe\_ratio |
|---|---|---|---|---|---|---|
| VZ | Verizon Communications Inc. | 41.20 | 2.66 | 6.46 | -8.3 | 9.1 |
| O | Realty Income Corporation | 54.48 | 2.95 | 5.42 | -12.4 | 45.8 |

### Notes

- Yields are computed from *actual dividends paid* in the last 12 months, not forward estimates.
- Prices are regular-market (last close); the market moves — re-run for fresh numbers.
- **Not financial advice.** This tool screens numbers; it doesn't know your goals, taxes, or risk tolerance.

# Actor input Schema

## `maxResults` (type: `integer`):

Maximum tickers to return, highest yield first. Error rows always sort last.

## `min_yield_pct` (type: `number`):

Only keep stocks yielding at least this percent (TTM dividends / price). 0 = no filter.

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

Ticker symbols to screen, e.g. O, JNJ, XOM. Defaults to a dividend-aristocrat watchlist.

## Actor input object example

```json
{
  "maxResults": 50,
  "min_yield_pct": 0,
  "tickers": [
    "O",
    "JNJ",
    "XOM"
  ]
}
```

# Actor output Schema

## `results` (type: `string`):

Link to the dataset with all screened dividend stocks (yields, payouts, 52-week ranges).

# 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 = {
    "tickers": [
        "O",
        "JNJ",
        "XOM"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("agent_muse/dividend-stock-screener").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 = { "tickers": [
        "O",
        "JNJ",
        "XOM",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("agent_muse/dividend-stock-screener").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 '{
  "tickers": [
    "O",
    "JNJ",
    "XOM"
  ]
}' |
apify call agent_muse/dividend-stock-screener --silent --output-dataset

```

## MCP server setup

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

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/o2slop6GBdrkbMNPs/builds/V22wwTvzUrd6IBaJc/openapi.json