STRASMORE/EXPLORE 2,985 QUERIES

session_split

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 2026-10-03, from us-stock-market-hours-lagos-time.

as of ranking 3×4read in context →
session_split — 3 rows by 4 columns, computed from US exchange, SIP and OPRA data.
segmentvolume_millionsshare_pctavg_thousand_per_minute
Regular session1655.283.890.3
After-hours273.513.829.5
Premarket47.32.43.5
Rows × columns
3 × 4
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 session_split, derived from the stored result.
ColumnTypeRangeNotes
segment text 3 distinct values (After-hours, Premarket, Regular session)
volume_millions number 47.3 to 1,655.2 count
share_pct number 2.4 to 83.8 percent
avg_thousand_per_minute number 3.5 to 90.3

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
        toHour(toTimeZone(window_start, 'America/New_York')) * 60
            + toMinute(toTimeZone(window_start, 'America/New_York')) AS et_min,
        toFloat64(volume)                                            AS volume
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= today() - 70
      AND window_start <  today() - 2
      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
           + toMinute(toTimeZone(window_start, 'America/New_York'))) >= 240
      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
           + toMinute(toTimeZone(window_start, 'America/New_York'))) <  1200
)
SELECT
    multiIf(et_min < 570, 'Premarket',
            et_min < 960, 'Regular session',
                          'After-hours')                            AS segment,
    round(sum(volume) / 1e6, 1)                                      AS volume_millions,
    round(100 * sum(volume) / (SELECT sum(volume) FROM bars), 1)      AS share_pct,
    round(avg(volume) / 1000, 1)                                     AS avg_thousand_per_minute
FROM bars
GROUP BY segment
ORDER BY share_pct DESC
⌘/Ctrl + Enter

Use dis data for your AI assistant

E go open ready to query, with dis page data. Free, no account.