sessiebeweging
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 2026-09-27, from aex-index-options-expiry-and-settlement.
| et_time | asml_beweging_bps | spy_beweging_bps |
|---|---|---|
| 09:00 | 15.93 | 3.14 |
| 10:00 | 9.82 | 2.52 |
| 11:00 | 7.03 | 1.96 |
| 12:00 | 5.6 | 1.58 |
| 13:00 | 4.68 | 1.4 |
| 14:00 | 4.61 | 1.4 |
| 15:00 | 6.28 | 1.57 |
- Rows × columns
- 7 × 3
- 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 |
|---|---|---|---|
et_time |
text | 7 distinct values (09:00, 10:00, 11:00…) | |
asml_beweging_bps |
number | 4.61 to 15.93 | |
spy_beweging_bps |
number | 1.4 to 3.14 |
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
concat(leftPad(toString(toHour(toTimeZone(window_start, 'America/New_York'))), 2, '0'), ':00') AS et_time,
round(avgIf(10000 * abs(toFloat64(close) - toFloat64(open)) / toFloat64(open), ticker = 'ASML'), 2) AS asml_beweging_bps,
round(avgIf(10000 * abs(toFloat64(close) - toFloat64(open)) / toFloat64(open), ticker = 'SPY'), 2) AS spy_beweging_bps
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('ASML', 'SPY')
AND window_start >= today() - 100
AND window_start < today() - 2
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
+ toMinute(toTimeZone(window_start, 'America/New_York'))) >= 570
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
+ toMinute(toTimeZone(window_start, 'America/New_York'))) < 960
GROUP BY et_time
HAVING countIf(ticker = 'ASML') > 0 AND countIf(ticker = 'SPY') > 0
ORDER BY et_time
Work with this data in your AI assistant
Opens ready to query, with this page's data. Free, no account.