STRASMORE/EXPLORE 3,127 QUERIES

One US split session, hour by hour, in both time zones

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 2026-10-06, from US Stock Splits for Chinese Investors.

as of series 16×3read in context →
One US split session, hour by hour, in both time zones — 16 rows by 3 columns, computed from US exchange, SIP and OPRA data.
et_timebeijing_clockavg_price_usd
04:00Jun 10, 16:00120.07
05:00Jun 10, 17:00120.14
06:00Jun 10, 18:00120.68
07:00Jun 10, 19:00120.56
08:00Jun 10, 20:00120.32
09:00Jun 10, 21:00119.52
10:00Jun 10, 22:00119.91
11:00Jun 10, 23:00122.16
12:00Jun 11, 00:00122.4
13:00Jun 11, 01:00122.58
14:00Jun 11, 02:00121.63
15:00Jun 11, 03:00121.95
16:00Jun 11, 04:00121.62
17:00Jun 11, 05:00121.74
18:00Jun 11, 06:00121.73
19:00Jun 11, 07:00121.72
Rows × columns
16 × 3
Computed
Completeness
No missing values
Source
US exchange, SIP and OPRA market data
Licence
Strasmore terms · free, no signup
Formats
JSON · CSV · the SQL below

What each column holds

Column definitions for One US split session, hour by hour, in both time zones, derived from the stored result.
ColumnTypeRangeNotes
et_time text 16 distinct values (04:00, 05:00, 06:00…)
beijing_clock text 16 distinct values
avg_price_usd number 119.52 to 122.58 US dollars

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
    formatDateTime(toTimeZone(bucket, 'America/New_York'), '%H:%i')      AS et_time,
    formatDateTime(toTimeZone(bucket, 'Asia/Shanghai'), '%b %e, %H:%i')  AS beijing_clock,
    round(toFloat64(avg(close)), 2)                                      AS avg_price_usd
FROM
(
    SELECT
        toStartOfHour(window_start) AS bucket,
        close
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'NVDA'
      AND window_start >= toDateTime('2024-06-10 08:00:00', 'UTC')
      AND window_start <  toDateTime('2024-06-11 00:00:00', 'UTC')
)
GROUP BY bucket
ORDER BY bucket
⌘/Ctrl + Enter

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