STRASMORE/EXPLORE 3,171 QUERIES

dong_ho_phien

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 2026-10-07, from us-premarket-and-after-hours-vietnam-time.

as of series 16×3read in context →
dong_ho_phien — 16 rows by 3 columns, computed from US exchange, SIP and OPRA data.
ict_timeet_timeavg_volume_millions
15:0004:000.1
16:0005:000.04
17:0006:000.06
18:0007:000.2
19:0008:000.39
20:0009:004.35
21:0010:005.62
22:0011:004.52
23:0012:003.63
00:0013:003.2
01:0014:004.1
02:0015:0010.65
03:0016:005.25
04:0017:000.31
05:0018:000.13
06:0019:000.04
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 dong_ho_phien, derived from the stored result.
ColumnTypeRangeNotes
ict_time text 16 distinct values (00:00, 01:00, 02:00…)
et_time text 16 distinct values (04:00, 05:00, 06:00…)
avg_volume_millions number 0.04 to 10.65 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.

WITH bars AS
(
    SELECT
        toTimeZone(window_start, 'Asia/Ho_Chi_Minh')              AS ict,
        toTimeZone(window_start, 'America/New_York')              AS et,
        toDate(toTimeZone(window_start, 'America/New_York'))      AS et_date,
        volume
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= toDateTime('2026-07-01 00:00:00')
      AND window_start <  toDateTime('2026-10-01 00:00:00')
      AND toHour(toTimeZone(window_start, 'America/New_York')) >= 4
      AND toHour(toTimeZone(window_start, 'America/New_York')) <  20
)
SELECT
    formatDateTime(ict, '%H:00')                            AS ict_time,
    formatDateTime(et, '%H:00')                             AS et_time,
    round(sum(volume) / countDistinct(et_date) / 1e6, 2)    AS avg_volume_millions
FROM bars
GROUP BY ict_time, et_time
ORDER BY et_time
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