STRASMORE/EXPLORE 2,749 QUERIES

volume_by_beijing_hour

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 2026-09-28, from us-daylight-saving-switch-in-beijing-time.

as of series 16×5read in context →
volume_by_beijing_hour — 16 rows by 5 columns, computed from US exchange, SIP and OPRA data.
et_timebeijing_summerbeijing_wintersummer_volume_mnwinter_volume_mn
04:0016:0017:000.40.7
05:0017:0018:000.20.7
06:0018:0019:000.60.8
07:0019:0020:001.11.6
08:0020:0021:002.73
09:0021:0022:0043.347.3
10:0022:0023:0044.761.3
11:0023:0000:0036.940.9
12:0000:0001:0029.835.2
13:0001:0002:0027.229.2
14:0002:0003:0045.740.7
15:0003:0004:0095.187.2
16:0004:0005:0034.633
17:0005:0006:0011.5
18:0006:0007:000.41
19:0007:0008:000.30.6
Rows × columns
16 × 5
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 volume_by_beijing_hour, derived from the stored result.
ColumnTypeRangeNotes
et_time text 16 distinct values (04:00, 05:00, 06:00…)
beijing_summer text 16 distinct values (00:00, 01:00, 02:00…)
beijing_winter text 16 distinct values (00:00, 01:00, 02:00…)
summer_volume_mn number 0.2 to 95.1 count
winter_volume_mn number 0.6 to 87.2 count

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(window_start, 'America/New_York'), '%H:00') AS et_time,
    anyIf(formatDateTime(toTimeZone(window_start, 'Asia/Shanghai'), '%H:00'),
          toDate(toTimeZone(window_start, 'America/New_York')) < toDate('2025-11-01')) AS beijing_summer,
    anyIf(formatDateTime(toTimeZone(window_start, 'Asia/Shanghai'), '%H:00'),
          toDate(toTimeZone(window_start, 'America/New_York')) > toDate('2025-11-01')) AS beijing_winter,
    round(sumIf(volume,
          toDate(toTimeZone(window_start, 'America/New_York')) < toDate('2025-11-01')) / 1e6, 1) AS summer_volume_mn,
    round(sumIf(volume,
          toDate(toTimeZone(window_start, 'America/New_York')) > toDate('2025-11-01')) / 1e6, 1) AS winter_volume_mn
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY'
  AND window_start >= toDateTime('2025-10-27 06:00:00', 'UTC')
  AND window_start <  toDateTime('2025-11-08 06:00:00', 'UTC')
  AND toHour(toTimeZone(window_start, 'America/New_York')) BETWEEN 4 AND 19
GROUP BY et_time
ORDER BY et_time
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