STRASMORE/EXPLORE 3,022 QUERIES

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

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 2026-10-04, from US Stocks 23/5 Trading: The December 2026 Plan.

as of series 19×5read in context →
SPY daily bar volume vs. the regular-session slice (trailing month) — 19 rows by 5 columns, computed from US exchange, SIP and OPRA data.
session_datesession_labeldaily_bar_millionsregular_session_millionsoutside_regular_pct
2026-09-04Sep 434.127.519.35
2026-09-08Sep 844.734.123.77
2026-09-09Sep 932.828.513.09
2026-09-10Sep 1042.738.69.64
2026-09-11Sep 1145.53816.42
2026-09-14Sep 144439.89.5
2026-09-15Sep 1546.237.219.39
2026-09-16Sep 1659.251.612.88
2026-09-17Sep 1749.736.127.31
2026-09-18Sep 1865.473.7-12.7
2026-09-21Sep 2150.543.513.93
2026-09-22Sep 2234.829.614.85
2026-09-23Sep 2354.939.328.48
2026-09-24Sep 244433.723.44
2026-09-25Sep 2536.731.214.95
2026-09-28Sep 2842.73713.4
2026-09-29Sep 2936.931.614.4
2026-09-30Sep 3062.145.926.14
2026-10-01Oct 147.740.914.22
Rows × columns
19 × 5
Period covered
to
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 SPY daily bar volume vs. the regular-session slice (trailing month), derived from the stored result.
ColumnTypeRangeNotes
session_date date 2026-09-04 to 2026-10-01
session_label text 19 distinct values (Oct 1, Sep 10, Sep 11…)
daily_bar_millions number 32.8 to 65.4
regular_session_millions number 27.5 to 73.7
outside_regular_pct number -12.7 to 28.48 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 , 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(sip_timestamp, 'America/New_York')) AS et_date,
        sumIf(toFloat64(size), has(conditions, 8)
              OR (toHour(toTimeZone(sip_timestamp, 'America/New_York')) * 60
                  + toMinute(toTimeZone(sip_timestamp, 'America/New_York'))) BETWEEN 570 AND 959) AS regular_volume
    FROM global_markets.stocks_trades
    WHERE ticker = 'SPY'
      AND sip_timestamp >= today() - 30
      AND sip_timestamp <  today() - 2
      AND NOT hasAny(conditions, [15, 16, 38])
    GROUP BY et_date
    HAVING countIf(has(conditions, 8)) > 0
) AS intraday ON intraday.et_date = daily.date
ORDER BY daily.date
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