STRASMORE/EXPLORE 3,293 QUERIES
Full options quote history: clean NBBO bid/ask snapshots for any US option contract at the interval you choose, by SQL API, $79 a month. See the options quotes plan

The regular session, half hour by half hour, on both clocks

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 2026-11-07, from US Stock Market Hours in Mountain Time.

as of series 13×3read in context →
The regular session, half hour by half hour, on both clocks — 13 rows by 3 columns, computed from US exchange, SIP and OPRA data.
et_timedenver_timeavg_volume_millions
09:3007:303.8
10:0008:002.66
10:3008:302.36
11:0009:002.12
11:3009:301.88
12:0010:001.63
12:3010:301.62
13:0011:001.58
13:3011:301.57
14:0012:001.84
14:3012:302.01
15:0013:002.43
15:3013:309.42
Rows × columns
13 × 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 The regular session, half hour by half hour, on both clocks, derived from the stored result.
ColumnTypeRangeNotes
et_time text 13 distinct values (09:30, 10:00, 10:30…)
denver_time text 13 distinct values (07:30, 08:00, 08:30…)
avg_volume_millions number 1.57 to 9.42 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
    (
        SELECT sum(closing_print)
        FROM
        (
            SELECT toDate(toTimeZone(sip_timestamp, 'America/New_York')) AS trade_date,
                   toFloat64(maxIf(size, has(conditions, 8)))            AS closing_print
            FROM global_markets.stocks_trades
            WHERE ticker = 'SPY'
              AND sip_timestamp >= today() - 45
              AND sip_timestamp <  today() - 2
            GROUP BY trade_date
        )
    ) AS closing_prints_total
SELECT
    formatDateTime(toStartOfInterval(toTimeZone(window_start, 'America/New_York'), INTERVAL 30 MINUTE), '%H:%i') AS et_time,
    formatDateTime(toStartOfInterval(toTimeZone(window_start, 'America/Denver'),   INTERVAL 30 MINUTE), '%H:%i') AS denver_time,
    round((toFloat64(sum(volume)) + if(et_time = '15:30', closing_prints_total, 0))
          / uniqExact(toDate(toTimeZone(window_start, 'America/New_York')))
          / 1e6, 2) AS avg_volume_millions
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY'
  AND window_start >= today() - 45
  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_time, denver_time
ORDER BY et_time
⌘/Ctrl + Enter

Work with this data in your AI assistant

Opens ready to query, with this page's data. Free, no account.

Claude ChatGPT Gemini Muse Your own agent
More from this analysisUS Stock Market Hours in Mountain Time
The 9:30 a.m. Eastern open, read on three clocks, by month series 14×6 → Upcoming market closures, with early-close times in Mountain Time series 12×8 → Sessions grouped by the local time the open landed ranking 2×3 → Sydney open and close of the first US session each week series 58×5 → The German clock time of the US open, week by week series 58×4 → SPY volume by Singapore half hour: US winter month vs US summer month series 34×3 → See all 3,293 queries →