Finance.Foundation
finance.foundation / Markets / Deutsche Börse Xetra
Market · XETR · Germany

Deutsche Börse Xetra

Reference market for German equities; DAX index family.

MIC (ISO 10383)
XETR
Country
Germany
Type
Stock exchange
Trading currency
EUR
Timezone
Europe/Berlin
Operator
Deutsche Börse Group
Operator LEI
529900G3SW56SHYNPR95 (GLEIF)

Trading session local time · Europe/Berlin

Session hours and the settlement cycle are compiled by Finance Foundation from the venue’s own published trading calendar. These are exact and change-prone — an extended session or a moved auction dates a figure like this quickly — so each row below carries what two independently maintained open calendars say about the same venue. Verify against the exchange before relying on any of it operationally. Sources.

Two independently maintained open calendars return the same hours as we hold. Cross-check from exchange_calendars (Apache 2.0) and pandas_market_calendars (MIT); neither endorses this site.

Regular session
09:00–17:30
Lunch break
none
Settlement cycle
T+2

Ownership

Operating entity
Deutsche Börse Aktiengesellschaft DE
529900G3SW56SHYNPR95
Not the name this venue trades under. Deutsche Börse Group is the group; the entity above is the one the ISO 10383 registry binds XETR to, and the one that legally runs this market.
Ultimate owner
None above it — Deutsche Börse Aktiengesellschaft is the top of its own ownership chain.
GLEIF records no parent for this entity (NO_KNOWN_PERSON), so the operator is itself the top of the tree
Sibling venues
Eurex Deutschland — run by the same group
Owner listed
DB1 on Deutsche Börse Xetra
Self-listed — its own shares trade on a market it operates.
Who holds it
Effectively 100% free float — the company's own disclosure as at 31 December 2025 splits the register 90% institutional / 10% retail (Germany 20%, UK 24%, North America 35%, other 21%) and names no shareholder above 3%.

Segment MICs 4 venues under XETR

MICSegment / venue
XETAXetra - Regulierter Markt
XETBXetra - Freiverkehr
XETSXetra - Scale
XEMAXetra Midpoint Regulated Market

Operating MIC vs segment MIC per ISO 10383: the operating code identifies the exchange, segment codes identify its individual order books, growth markets and derivatives venues. Every code was checked line by line against the official ISO 10383 registry file (SWIFT is the registration authority) — codes that were expired or belonged to a separate operating venue were rejected.

Assets tied to this venue

DAX 40 calculated on · EURO STOXX 50 calculated across, derivatives listed on

Covered assets whose relationship to this venue is recorded in the dataset — an index calculated on it, or a contract listed on it. Companies listed here are in the table above; this is the non-equity side.

Benchmark indices

DAX · MDAX · SDAX · TecDAX

1 of these 4 are covered as assets here and link through; the rest are named because the venue publishes them, not because we track them. A linked index is a real relationship in the dataset, not a name that happened to match.

Top companies by market cap covered set · 6

CompanyTickerSectorMkt cap ≈
SAPEnterprise SoftwareSAPTechnology$273.7bn
SiemensIndustrial TechnologySIEIndustrials$263.9bn
AllianzInsurance and asset managementALVFinancials$200.6bn
Deutsche TelekomTelecommunicationsDTECommunication Services$161bn
Munich ReReinsuranceMUV2Financials$76.6bn
RheinmetallDefense and armamentsRHMIndustrials$62.7bn

Approximate reference values from public sources · seed-0.7 · marketcap-1 · 2026-08-30 · not real-time. See data & methodology.

# this page as data GET https://finance.foundation/api/v1/markets/xetra

JSONCSV No key, CORS enabled — paste any of these straight into a notebook.

Code to fetch it
curl
curl -s https://finance.foundation/api/v1/markets/xetra
Python
import requests r = requests.get("https://finance.foundation/api/v1/markets/xetra", timeout=30) r.raise_for_status() data = r.json()
JavaScript
const r = await fetch("https://finance.foundation/api/v1/markets/xetra"); if (!r.ok) throw new Error(r.status); const data = await r.json();
pandas
import pandas as pd df = pd.read_csv("https://finance.foundation/api/v1/markets/xetra.csv")