US Stock Prices & Daily History: NYSE, Nasdaq, ETFs

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

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

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

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.

A real dataset item:

{
    "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

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

One year of daily ETF history

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

A calendar year for a backtest

{
    "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.