US session milestones in ET, UTC and German local time
Answered against 22 years of US equities and 12 years of US options data and published with the query that produced it. This result is stored as of 2026-11-07, from US Market Hours in German Time (CET/CEST).
| milestone | et_clock | utc_us_winter | german_cet | utc_us_summer | german_cest | et_minutes |
|---|---|---|---|---|---|---|
| Premarket opens | 04:00 | 09:January | 10:January | 08:July | 10:July | 240 |
| Regular session opens | 09:30 | 14:January | 15:January | 13:July | 15:July | 570 |
| Half-day early close | 13:00 | 18:January | 19:January | 17:July | 19:July | 780 |
| Regular session closes | 16:00 | 21:January | 22:January | 20:July | 22:July | 960 |
| After-hours ends | 20:00 | 01:January | 02:January | 00:July | 02:July | 1200 |
- Rows × columns
- 5 × 7
- Computed
- Completeness
- No missing values
- Source
- US exchange, SIP and OPRA market data
- Licence
- Strasmore terms · free, no signup
What each column holds
| Column | Type | Range | Notes |
|---|---|---|---|
milestone |
text | 5 distinct values | |
et_clock |
text | 5 distinct values (04:00, 09:30, 13:00…) | |
utc_us_winter |
text | 5 distinct values (01:January, 09:January, 14:January…) | |
german_cet |
text | 5 distinct values (02:January, 10:January, 15:January…) | |
utc_us_summer |
text | 5 distinct values (00:July, 08:July, 13:July…) | |
german_cest |
text | 5 distinct values (02:July, 10:July, 15:July…) | |
et_minutes |
number | 240 to 1,200 |
Computed from Strasmore's warehouse of US exchange, SIP and OPRA market data. Equity prices are delayed; options greeks and implied volatility are end-of-day. This result is stored, not recomputed on load — it is exactly the numbers that were returned on , and the query below is what returned them.
Run it yourself
This is the exact query behind the result above. Change a ticker, a date or a column and run it against the warehouse — no account, no key. The no-signup tier is smaller than the one this page was computed on; a query that reaches past it comes back saying which plan runs it.
SELECT
tupleElement(m, 1) AS milestone,
tupleElement(m, 2) AS et_clock,
formatDateTime(toTimeZone(et_winter, 'UTC'), '%H:%M') AS utc_us_winter,
formatDateTime(toTimeZone(et_winter, 'Europe/Berlin'), '%H:%M') AS german_cet,
formatDateTime(toTimeZone(et_summer, 'UTC'), '%H:%M') AS utc_us_summer,
formatDateTime(toTimeZone(et_summer, 'Europe/Berlin'), '%H:%M') AS german_cest,
tupleElement(m, 3) AS et_minutes
FROM
(
SELECT
m,
toDateTime(concat(toString(toYear(today())), '-01-15 ', tupleElement(m, 2), ':00'), 'America/New_York') AS et_winter,
toDateTime(concat(toString(toYear(today())), '-07-15 ', tupleElement(m, 2), ':00'), 'America/New_York') AS et_summer
FROM
(
SELECT arrayJoin([
('Premarket opens', '04:00', 240),
('Regular session opens', '09:30', 570),
('Half-day early close', '13:00', 780),
('Regular session closes', '16:00', 960),
('After-hours ends', '20:00', 1200)
]) AS m
)
)
ORDER BY et_minutes
Work with this data in your AI assistant
Opens ready to query, with this page's data. Free, no account.