Germany Xetra Stock Quotes: DAX Prices & Performance

What does Germany Xetra Stock Quotes: DAX Prices & Performance do?

Germany Xetra Stock Quotes returns one row per stock traded on Xetra, from public Deutsche Börse market data. Each row has the last price in euro, change and percent change, previous close, open, day range, volume and turnover when available, the 52-week range and where the price sits in it, and the price performance over 1 month, 3 months, 6 months, 1 year and 3 years with the 1-year high and low. It knows about 50 major German tickers such as SAP, SIE, ALV and BMW, and accepts any 12-character ISIN, which also works for many international shares that trade on Xetra.

Why use Germany Xetra Stock Quotes: DAX Prices & Performance?

• Momentum features built in: performance from 1 month to 3 years and range position.
• DAX constituents by ticker and any Xetra security by ISIN.
• Reads the official exchange data, in euro.
• Slow or missing fields never stop a run: the core price and performance still return.
• No API key or login, bulk tickers per run, billed only for rows returned.

What makes this different

German stock data is scattered across broker pages and paid feeds, and the exchange identifies shares by ISIN rather than ticker. This Actor maps common tickers for you, accepts ISINs, and returns price plus multi-horizon performance in one tidy row.

Who can use the Germany Xetra Stock Quotes and how?

• Quant researchers: add German momentum features to models.
• Retail investors: screen DAX stocks by range position and performance.
• Newsletter writers: publish a daily DAX table.
• Fintech apps: show German quotes without a data contract.
• Advisers: track client holdings in euro.
• AI agent builders: let an assistant answer what a DAX stock trades at.
• Analysts: compare performance across horizons.
• Students: free German market data for coursework.

How it works

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

What data can you extract?

The dataset has 34 fields per row:

Field	Type	Description
record_type	string	quote or bar.
ticker	string	Ticker symbol.
isin	string	ISIN.
name	string	Company or fund name.
exchange	string	Exchange.
currency	string	Trading currency.
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.
open	number	Open.
day_low	number	Day low.
day_high	number	Day high.
volume	number	Volume in shares.
turnover_eur	number	Turnover in euro.
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.
performance_1m_pct	number	1-month performance, percent.
performance_3m_pct	number	3-month performance, percent.
performance_6m_pct	number	6-month performance, percent.
performance_1y_pct	number	1-year performance, percent.
performance_3y_pct	number	3-year performance, percent.
high_1y	number	1-year high.
low_1y	number	1-year low.
bid	number	Best bid.
ask	number	Best ask.
trading_status	string	Trading status.
last_trade_time	string	Time of the last trade.
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.

How to use Germany Xetra Stock Quotes: DAX Prices & Performance

1. Open the Actor and go to the Input tab.
2. Enter Tickers (for example SAP, SIE, ALV, BMW) or 12-character ISINs and run. Schedule it after the close 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	["SAP","SIE","ALV"]	German tickers such as SAP, SIE, ALV, BMW, or any 12-character ISIN, one per line.
mode	string	No	"quotes"	quotes returns one row per stock. history returns about the last month of daily bars per stock (ticker only, not ISIN), read from a public secondary source (not Deutsche Börse's own chart feed, which needs a market-data access token this Actor does not have).
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

price, change_pct, previous_close, open, day_low, day_high, volume and turnover_eur describe trading (volume and day range can be empty when the exchange's detailed feed is slow). week52_low, week52_high and range_position_52w_pct show the range. performance_1m_pct, performance_3m_pct, performance_6m_pct, performance_1y_pct and performance_3y_pct are price changes over those horizons, with high_1y and low_1y. History rows (record_type: "bar") have date, open, high, low, close and volume for about the last month of trading days.

A real dataset item:

{
    "record_type": "bar",
    "ticker": "ADS",
    "isin": "DE000A1EWWW0",
    "date": "2026-09-25",
    "open": 143.9,
    "close": 146.5,
    "high": 146.5,
    "low": 143.9,
    "volume": 439249,
    "as_of": "2026-09-27T09:08:39.733Z",
    "fetch_path": "deutsche_boerse_public_api",
    "source": "deutsche_boerse_public_market_data",
    "scraped_at": "2026-09-27T09:08:39.733Z",
    "actor_version": "1.0.0"
}

How to read and use the results

1. Read price and change_pct.
2. Use range_position_52w_pct for where the price sits in its year.
3. Compare performance_3m_pct and performance_1y_pct for momentum.
4. Pass ISINs for shares not in the built-in list.
5. Schedule runs to build history.
6. Watch the log for unknown tickers.

Usage Examples

DAX heavyweights

{
    "tickers": ["SAP", "SIE", "ALV", "BMW", "MBG", "DTE"]
}

By ISIN

{
    "tickers": ["DE0007164600", "NL0000235190"]
}

Consumer and e-commerce

{
    "tickers": ["ADS", "PUM", "ZAL", "HFG"]
}

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 performance_3m_pct against performance_1y_pct for momentum versus long-run trend.
• Unknown tickers can be passed as ISINs.
• 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
Price, change, performance	✅	No	Public Deutsche Börse data.
Volume, day range, turnover	🟡	No	Empty when the detailed feed is slow.
Daily price history (about 1 month)	🟡	No	From a public secondary source (Google Finance's own chart data), not the exchange's own feed.
Real-time tick data	❌	-	End-of-day and delayed snapshots.

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

Known Limitations

• This Actor returns quotes only; daily history is not available from the public data it reads.
• Prices are delayed or end-of-day snapshots, not real-time ticks.
• Volume, day range and turnover can be empty when the exchange's detailed price feed is slow; price and performance still return.
• Only securities traded on Xetra are covered.
• This is information, not financial advice.
• Daily bars are read from Google Finance's own embedded chart data, a secondary source; treat the most recent day's close as provisional and prefer the quote row for the current price.

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 Deutsche Börse market data for securities traded on Xetra.

Does it need an API key or account?

No.

Can I get daily price history?

Yes, switch Mode to history for about the last month of daily bars, read from a public secondary source since the exchange's own chart feed needs an access token this Actor does not have.

How fresh are the prices?

Snapshots of the last trade; outside trading hours it is the last session.

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 Deutsche Börse 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 Deutsche Börse 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 Deutsche Börse.