SPY daily bar volume vs. the regular-session slice (trailing month)

Name: SPY daily bar volume vs. the regular-session slice (trailing month)
Creator: Strasmore
Published: 2026-09-20
License: https://www.strasmore.com/terms/

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 2026-09-20, from US Stocks 23/5 Trading: The December 2026 Plan.

as of 2026-09-20 series 19×5read in context →

SPY daily bar volume vs. the regular-session slice (trailing month) — 19 rows by 5 columns, computed 2026-09-20 from US exchange, SIP and OPRA data.
session_date	session_label	daily_bar_millions	regular_session_millions	outside_regular_pct
2026-08-21	Aug 21	39.2	33.7	14.06
2026-08-24	Aug 24	32.4	27.2	16.01
2026-08-25	Aug 25	27.4	24	12.45
2026-08-26	Aug 26	28.8	22.9	20.41
2026-08-27	Aug 27	34.6	28.8	16.74
2026-08-28	Aug 28	36.7	31.6	13.96
2026-08-31	Aug 31	38.8	29.8	23.25
2026-09-01	Sep 1	41.1	32.2	21.78
2026-09-02	Sep 2	29.6	22.4	24.22
2026-09-03	Sep 3	43.5	35.5	18.41
2026-09-04	Sep 4	34.1	26.8	21.39
2026-09-08	Sep 8	44.7	31.8	28.85
2026-09-09	Sep 9	32.8	27.5	16.23
2026-09-10	Sep 10	42.7	37.3	12.82
2026-09-11	Sep 11	45.5	36.9	18.93
2026-09-14	Sep 14	44	38.4	12.61
2026-09-15	Sep 15	46.2	35.9	22.35
2026-09-16	Sep 16	59.2	49.4	16.63
2026-09-17	Sep 17	49.7	34.8	29.93

Rows × columns: 19 × 5
Period covered: 2026-08-21 to 2026-09-17
Computed: 2026-09-20
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 SPY daily bar volume vs. the regular-session slice (trailing month), derived from the stored result.
Column	Type	Range	Notes
`session_date`	date	2026-08-21 to 2026-09-17
`session_label`	text	19 distinct values (Aug 21, Aug 24, Aug 25…)
`daily_bar_millions`	number	27.4 to 59.2
`regular_session_millions`	number	22.4 to 49.4
`outside_regular_pct`	number	12.45 to 29.93	percent

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 2026-09-20, 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(daily.date)                                                                AS session_date,
    concat(formatDateTime(daily.date, '%b'), ' ', toString(toDayOfMonth(daily.date)))   AS session_label,
    round(toFloat64(daily.day_volume) / 1e6, 1)                                         AS daily_bar_millions,
    round(toFloat64(intraday.regular_volume) / 1e6, 1)                                  AS regular_session_millions,
    round(100 * (toFloat64(daily.day_volume) - toFloat64(intraday.regular_volume))
              / toFloat64(daily.day_volume), 2)                                         AS outside_regular_pct
FROM
(
    SELECT
        date,
        max(volume) AS day_volume
    FROM global_markets.stocks_daily_aggs
    WHERE ticker = 'SPY'
      AND date >= today() - 30
      AND date <  today() - 2
    GROUP BY date
) AS daily
INNER JOIN
(
    SELECT
        toDate(toTimeZone(window_start, 'America/New_York')) AS et_date,
        sum(volume)                                          AS regular_volume
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= today() - 30
      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_date
) AS intraday ON intraday.et_date = daily.date
ORDER BY daily.date

SQL to run

SELECT
    toString(daily.date)                                                                AS session_date,
    concat(formatDateTime(daily.date, '%b'), ' ', toString(toDayOfMonth(daily.date)))   AS session_label,
    round(toFloat64(daily.day_volume) / 1e6, 1)                                         AS daily_bar_millions,
    round(toFloat64(intraday.regular_volume) / 1e6, 1)                                  AS regular_session_millions,
    round(100 * (toFloat64(daily.day_volume) - toFloat64(intraday.regular_volume))
              / toFloat64(daily.day_volume), 2)                                         AS outside_regular_pct
FROM
(
    SELECT
        date,
        max(volume) AS day_volume
    FROM global_markets.stocks_daily_aggs
    WHERE ticker = 'SPY'
      AND date >= today() - 30
      AND date <  today() - 2
    GROUP BY date
) AS daily
INNER JOIN
(
    SELECT
        toDate(toTimeZone(window_start, 'America/New_York')) AS et_date,
        sum(volume)                                          AS regular_volume
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= today() - 30
      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_date
) AS intraday ON intraday.et_date = daily.date
ORDER BY daily.date

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