# US Stock Prices & Daily History: NYSE, Nasdaq, ETFs (`mrdoe/us-stock-price-history`) Actor

US stock and ETF quotes and daily OHLCV history from public Nasdaq market data: price, change, 52-week range, market cap, sector, dividend, after-hours price and daily returns. Bulk tickers per run, no API key.

- **URL**: https://apify.com/mrdoe/us-stock-price-history.md
- **Developed by:** [MrDoe](https://apify.com/mrdoe) (community)
- **Categories:** Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.70 / 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.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

![US Stock Prices & Daily History: NYSE, Nasdaq, ETFs - US stock price API returning quotes and daily OHLCV history for NYSE and Nasdaq tickers](https://api.apify.com/v2/key-value-stores/kE36venAoVchGsE6b/records/us-stock-price-history--hero.png)

### What does US Stock Prices & Daily History: NYSE, Nasdaq, ETFs do?

US Stock Price & History returns quotes and daily price history for US-listed stocks and ETFs from public Nasdaq market data. In quotes mode each ticker gives one row with the last price, change and percent change, previous close, volume and average volume, the 52-week range and where the price sits in it, market capitalisation, sector and industry, the analyst one-year target, annual dividend and yield, the ex-dividend date and the after-hours price when available. In history mode each ticker gives one row per trading day with open, high, low, close, volume, the daily return and the day's range. It handles class shares such as BRK.B, works for ETFs, and processes many tickers in one run.

### Why use US Stock Prices & Daily History: NYSE, Nasdaq, ETFs?

- Quotes and daily history from one Actor, for stocks and ETFs on NYSE and Nasdaq.
- Fundamentals in the quote row: market cap, sector, dividend, target price and 52-week range position.
- Derived features in history rows: daily return and day range, ready for a model.
- Class shares and ETFs work, and unknown tickers are skipped without stopping the run.
- No API key or login, bulk tickers per run, billed only for rows returned.

### What makes this different

Free stock price sources rate-limit or block scrapers, and paid APIs need keys and contracts. This Actor gives you cleaned quotes and history for whole watchlists with the parsing done for you, so a screen, report or predictor can start from tidy rows.

### Who can use the US Stock Price & History and how?

- **Quant researchers and predictors:** collect clean OHLCV and 52-week features for models.
- **Retail investors:** screen a watchlist by range position, dividend and market cap.
- **Newsletter writers:** publish a daily price table.
- **Fintech and portfolio apps:** show quotes without running a data contract.
- **Backtesting:** pull years of daily bars for chosen tickers.
- **AI agent builders:** let an assistant answer what a stock is trading at.
- **Finance teams:** track holdings and dividend dates.
- **Students and educators:** get free daily data for coursework.

### How it works

![US Stock Prices & Daily History: NYSE, Nasdaq, ETFs workflow: your input, collection, output](https://api.apify.com/v2/key-value-stores/kE36venAoVchGsE6b/records/us-stock-price-history--how-it-works.png)

1. **Your input** — list the tickers (or ISINs).
2. **The Actor collects it** — the Actor reads Nasdaq public market data for each one.
3. **Your output** — you get one row per stock with price, change, range position and fundamentals, or one row per trading day in history mode.

### What data can you extract?

The dataset has 42 fields per row:

| Field                    | Type    | Description                                                                   |
| ------------------------ | ------- | ----------------------------------------------------------------------------- |
| `record_type`            | string  | quote or bar.                                                                 |
| `ticker`                 | string  | Ticker symbol.                                                                |
| `name`                   | string  | Company or fund name.                                                         |
| `exchange`               | string  | Exchange.                                                                     |
| `asset_class`            | string  | stocks or etf.                                                                |
| `price`                  | number  | Last price.                                                                   |
| `change`                 | number  | Change from the previous close.                                               |
| `change_pct`             | number  | Change from the previous close, percent.                                      |
| `previous_close`         | number  | Previous close.                                                               |
| `volume`                 | number  | Volume in shares.                                                             |
| `average_volume`         | number  | Average daily volume.                                                         |
| `bid`                    | number  | Best bid.                                                                     |
| `ask`                    | number  | Best ask.                                                                     |
| `day_low`                | number  | Day low.                                                                      |
| `day_high`               | number  | Day high.                                                                     |
| `week52_low`             | number  | 52-week low.                                                                  |
| `week52_high`            | number  | 52-week high.                                                                 |
| `range_position_52w_pct` | number  | Where the price sits in its 52-week range, 0 = at the low, 100 = at the high. |
| `market_cap`             | number  | Market capitalisation.                                                        |
| `sector`                 | string  | Sector.                                                                       |
| `industry`               | string  | Industry.                                                                     |
| `one_year_target`        | number  | Analyst one-year target price.                                                |
| `dividend_annualized`    | number  | Annualised dividend per share.                                                |
| `dividend_yield_pct`     | number  | Dividend yield, percent.                                                      |
| `ex_dividend_date`       | string  | Ex-dividend date.                                                             |
| `after_hours_price`      | number  | After-hours price.                                                            |
| `after_hours_change_pct` | number  | After-hours change, percent.                                                  |
| `market_status`          | string  | Market open or closed.                                                        |
| `last_trade`             | string  | Time of the last trade.                                                       |
| `is_real_time`           | boolean | Whether the price is real time.                                               |
| `as_of`                  | string  | When the data was read.                                                       |
| `fetch_path`             | string  | How the data was obtained.                                                    |
| `source`                 | string  | Data source.                                                                  |
| `scraped_at`             | string  | Timestamp.                                                                    |
| `actor_version`          | string  | Actor version.                                                                |
| `date`                   | string  | Trading date, YYYY-MM-DD.                                                     |
| `open`                   | number  | Open.                                                                         |
| `high`                   | number  | High.                                                                         |
| `low`                    | number  | Low.                                                                          |
| `close`                  | number  | Close.                                                                        |
| `daily_return_pct`       | number  | Return versus the previous bar, percent.                                      |
| `range_pct`              | number  | High-low range as percent of the low.                                         |

### How to use US Stock Prices & Daily History: NYSE, Nasdaq, ETFs

![US Stock Prices & Daily History: NYSE, Nasdaq, ETFs input form](https://api.apify.com/v2/key-value-stores/kE36venAoVchGsE6b/records/us-stock-price-history--input.png)

1. Open the Actor and go to the **Input** tab.
2. Enter **Tickers** (for example `AAPL`, `MSFT`, `SPY`, `BRK.B`) and run for quotes. Switch **Mode** to history and set a date range or lookback for daily bars. Schedule daily to store your own history.
3. Optionally set filters and a **Max results** limit.
4. Click **Start**. A default run finishes in under a minute.
5. Open the **Output** tab, then download the dataset or connect it to your tools.

### Input Parameters

| Parameter            | Type    | Required | Default                   | Description                                                                |
| -------------------- | ------- | -------- | ------------------------- | -------------------------------------------------------------------------- |
| `tickers`            | array   | No       | `["AAPL","MSFT","SPY"]`   | US stock or ETF symbols, one per line, for example AAPL, MSFT, SPY, BRK.B. |
| `mode`               | string  | No       | `"quotes"`                | quotes returns one row per stock; history returns one row per trading day. |
| `startDate`          | string  | No       | —                         | First date for history mode, YYYY-MM-DD. Leave empty to use the lookback.  |
| `endDate`            | string  | No       | —                         | Last date for history mode, YYYY-MM-DD. Leave empty for today.             |
| `lookbackDays`       | integer | No       | `30`                      | Used in history mode when no start date is set.                            |
| `newestFirst`        | boolean | No       | `true`                    | History order. Turn off for chronological.                                 |
| `maxItems`           | integer | No       | `0`                       | Cap on returned rows. Set 0 for no limit.                                  |
| `proxyConfiguration` | object  | No       | `{"useApifyProxy":false}` | Optional proxy. The data works without one.                                |

### Output Data

![US Stock Prices & Daily History: NYSE, Nasdaq, ETFs dataset table](https://api.apify.com/v2/key-value-stores/kE36venAoVchGsE6b/records/us-stock-price-history--output.png)

Quote rows have `price`, `change_pct`, `previous_close`, `volume`, `week52_low`, `week52_high` and `range_position_52w_pct`, plus `market_cap`, `sector`, `industry`, `one_year_target`, `dividend_annualized`, `dividend_yield_pct` and the after-hours fields when the market has an extended session. `market_status` and `is_real_time` say how fresh the price is. History rows have `date`, `open`, `high`, `low`, `close`, `volume`, `daily_return_pct` (versus the previous bar in the range) and `range_pct`.

![US Stock Prices & Daily History: NYSE, Nasdaq, ETFs field map of one record](https://api.apify.com/v2/key-value-stores/kE36venAoVchGsE6b/records/us-stock-price-history--fields.png)

A real dataset item:

```json
{
    "record_type": "bar",
    "ticker": "MSFT",
    "date": "2026-09-25",
    "open": 499.035,
    "high": 519.4,
    "low": 497.25,
    "close": 516.17,
    "volume": 38193110,
    "daily_return_pct": 3.663,
    "range_pct": 4.454,
    "as_of": "2026-09-27T05:06:19.340Z",
    "fetch_path": "nasdaq_public_api",
    "source": "nasdaq_public_market_data",
    "scraped_at": "2026-09-27T05:06:19.340Z",
    "actor_version": "1.0.0"
}
```

### How to read and use the results

1. **Read price, change\_pct and market\_status** for the current picture.
2. **Use range\_position\_52w\_pct** to see momentum or stretched prices.
3. **Check dividend and ex-dividend fields** for income screens.
4. **Use history mode** for OHLCV and daily returns.
5. **Schedule runs** to build your own history.
6. **Watch the log** for tickers that returned nothing.

### Usage Examples

#### Big tech quotes

```json
{
    "tickers": ["AAPL", "MSFT", "NVDA", "AMZN", "GOOGL"]
}
```

#### One year of daily ETF history

```json
{
    "mode": "history",
    "tickers": ["SPY", "QQQ"],
    "lookbackDays": 365
}
```

#### A calendar year for a backtest

```json
{
    "mode": "history",
    "tickers": ["TSLA"],
    "startDate": "2020-01-01",
    "endDate": "2020-12-31",
    "newestFirst": false
}
```

### Tips for Best Results

- Schedule the Actor after the close and keep each run to build your own price history.
- range\_position\_52w\_pct is 0 at the 52-week low and 100 at the high, a quick momentum and mean-reversion feature.
- Keep tickers in one run: many tickers per run cost less than many runs.
- Use history mode with a long lookback once, then a short lookback on a schedule to append.
- Default is 5 results for a fast test. Set the max to 0 to return everything available.

### Reliability by mode

| Mode                 | Status | Needs login or key? | Notes                                    |
| -------------------- | ------ | ------------------- | ---------------------------------------- |
| Stock and ETF quotes | ✅     | No                  | Public Nasdaq market data.               |
| Daily history        | ✅     | No                  | Stocks and ETFs.                         |
| After-hours price    | 🟡     | No                  | Only when an extended session is active. |
| Real-time tick data  | ❌     | -                   | End-of-day and delayed snapshots.        |

✅ works as described, 🟡 works with caveats, ❌ not supported.

### Known Limitations

- Prices are delayed exchange data, not real-time ticks; market\_status and is\_real\_time say what you got.
- The first bar of a history range has no daily return because the previous day is outside the range.
- Fundamental fields exist only for common stocks; ETFs return fewer fields.
- History covers the days the exchange data provides; very old data for delisted symbols may be missing.
- This is information, not financial advice.

### Integrations

Run it from the Apify API, on a schedule, or from a webhook. Send results straight to Google Sheets, Make, Zapier, Slack or your own database with Apify's built-in integrations.

### Export Formats

Download the dataset as JSON, CSV, Excel, XML, HTML table or RSS from the **Output** tab or the API.

### Frequently Asked Questions

#### Where does the data come from?

Public Nasdaq market data for US-listed stocks and ETFs.

#### Does it need an API key or account?

No.

#### How fresh are the prices?

Quotes are delayed exchange data, and the row says whether the price is real time.

#### What if a ticker is wrong?

It is skipped and named in the log; the other tickers still return.

#### Can I run it on a schedule?

Yes. Schedule it and store each run to build your own price history.

#### Am I charged for tickers that return nothing?

No, only for rows returned.

#### Do I need an account or login?

No. The Actor reads public Nasdaq market data and needs no account or API key.

#### Am I charged for failed runs or empty results?

You are only charged for results that are actually written to the dataset.

#### Can I run it on a schedule?

Yes. Create a Task with your input and add a schedule in Apify Console. With monitor mode on, each scheduled run returns only what changed since the previous one.

### Changelog

- **2026-09-27:** First release.

### Enterprise and custom work

Need higher volumes, a custom output schema, dedicated scheduling or a no-breaking-changes commitment for a production pipeline? Open an issue on the Actor page and describe your use case. Bulk terms and custom builds are available.

### Support

Questions or a missing field? Open an issue from the **Issues** tab on this Actor's page and it will be looked at.

### Legal / Responsible Use

This Actor reads publicly available Nasdaq market data. You are responsible for how you use it and for complying with the source's terms. It is not financial advice and not affiliated with Nasdaq.

# Actor input Schema

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

US stock or ETF symbols, one per line, for example AAPL, MSFT, SPY, BRK.B.

## `mode` (type: `string`):

quotes returns one row per stock; history returns one row per trading day.

## `startDate` (type: `string`):

First date for history mode, YYYY-MM-DD. Leave empty to use the lookback.

## `endDate` (type: `string`):

Last date for history mode, YYYY-MM-DD. Leave empty for today.

## `lookbackDays` (type: `integer`):

Used in history mode when no start date is set.

## `newestFirst` (type: `boolean`):

History order. Turn off for chronological.

## `maxItems` (type: `integer`):

Cap on returned rows. Set 0 for no limit.

## `proxyConfiguration` (type: `object`):

Optional proxy. The data works without one.

## Actor input object example

```json
{
  "tickers": [
    "AAPL",
    "MSFT",
    "SPY"
  ],
  "mode": "quotes",
  "lookbackDays": 30,
  "newestFirst": true,
  "maxItems": 0,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

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

// Prepare Actor input
const input = {
    "tickers": [
        "AAPL",
        "MSFT",
        "SPY"
    ],
    "proxyConfiguration": {
        "useApifyProxy": false
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("mrdoe/us-stock-price-history").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": [
        "AAPL",
        "MSFT",
        "SPY",
    ],
    "proxyConfiguration": { "useApifyProxy": False },
}

# Run the Actor and wait for it to finish
run = client.actor("mrdoe/us-stock-price-history").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": [
    "AAPL",
    "MSFT",
    "SPY"
  ],
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}' |
apify call mrdoe/us-stock-price-history --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,mrdoe/us-stock-price-history"
        }
    }
}
```

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/RaK6DJRATu3neECpN/builds/UlXcXuPhsbyVQKZKE/openapi.json