decalage_mensuel
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 2026-10-09, from us-stock-market-hours-paris-time.
| month | ouverture_15h30 | ouverture_decalee | cumul_decalee |
|---|---|---|---|
| 2025-09-01 | 19 | 0 | 0 |
| 2025-10-01 | 18 | 5 | 5 |
| 2025-11-01 | 19 | 0 | 5 |
| 2025-12-01 | 22 | 0 | 5 |
| 2026-01-01 | 20 | 0 | 5 |
| 2026-02-01 | 19 | 0 | 5 |
| 2026-03-01 | 7 | 15 | 20 |
| 2026-04-01 | 21 | 0 | 20 |
| 2026-05-01 | 20 | 0 | 20 |
| 2026-06-01 | 21 | 0 | 20 |
| 2026-07-01 | 22 | 0 | 20 |
| 2026-08-01 | 21 | 0 | 20 |
| 2026-09-01 | 21 | 0 | 20 |
| 2026-10-01 | 4 | 0 | 20 |
- Rows × columns
- 14 × 4
- Period covered
- to
- 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 |
|---|---|---|---|
month |
date | 2025-09-01 to 2026-10-01 | |
ouverture_15h30 |
number | 4 to 22 | |
ouverture_decalee |
number | 0 to 15 | |
cumul_decalee |
number | 0 to 20 |
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
toString(m.mois) AS month,
m.ouverture_15h30 AS ouverture_15h30,
m.ouverture_decalee AS ouverture_decalee,
sum(m.ouverture_decalee) OVER (ORDER BY m.mois) AS cumul_decalee
FROM
(
SELECT
toStartOfMonth(toDate(toTimeZone(window_start, 'America/New_York'))) AS mois,
countDistinctIf(toDate(toTimeZone(window_start, 'America/New_York')),
formatDateTime(toTimeZone(window_start, 'Europe/Paris'), '%H:%i') = '15:30') AS ouverture_15h30,
countDistinctIf(toDate(toTimeZone(window_start, 'America/New_York')),
formatDateTime(toTimeZone(window_start, 'Europe/Paris'), '%H:%i') != '15:30') AS ouverture_decalee
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY'
AND window_start >= today() - 400
AND window_start < today() - 2
AND formatDateTime(toTimeZone(window_start, 'America/New_York'), '%H:%i') = '09:30'
GROUP BY mois
) AS m
ORDER BY m.mois
Travaillez ces données dans votre assistant IA
S'ouvre prêt à interroger, avec les données de cette page. Gratuit, sans compte.