STRASMORE/EXPLORE 2,170 QUERIES

AAPL median shares per traded minute, and the share of minutes that traded at all (ET)

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 2026-08-22, from Premarket and After-Hours Trading Hours (ET).

as of series 32×3read in context →
AAPL median shares per traded minute, and the share of minutes that traded at all (ET) — 32 rows by 3 columns, computed from US exchange, SIP and OPRA data.
et_timemedian_minute_volumepct_minutes_traded
04:00107284.1
04:3050970.6
05:0050671.6
05:3054272.9
06:0068776.7
06:3077082.1
07:00188995.9
07:30162295.7
08:00185797.3
08:30248398.4
09:00343598.7
09:30144809100
10:00103684100
10:3084408100
11:0070432100
11:3056141100
12:0050169100
12:3045187100
13:004137795.2
13:304207395.2
14:004496395.2
14:304988695.2
15:006240395.2
15:3010741195.2
16:00217193
16:30124986.3
17:0068481.4
17:3050578.7
18:0052278.1
18:3049378.7
19:0052174.1
19:3064484.1
Rows × columns
32 × 3
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 AAPL median shares per traded minute, and the share of minutes that traded at all (ET), derived from the stored result.
ColumnTypeRangeNotes
et_time date 04:00 to 19:30
median_minute_volume number 493 to 144,809 count
pct_minutes_traded number 70.6 to 100 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.

the exact SQL behind every number 
WITH full_sessions AS (
    SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS session_date
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'AAPL'
      AND window_start >= now() - INTERVAL 30 DAY
      AND toDate(toTimeZone(window_start, 'America/New_York')) < toDate(toTimeZone(now(), 'America/New_York'))
    GROUP BY session_date
    HAVING max(toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) >= 1140
)
SELECT formatDateTime(toStartOfInterval(toTimeZone(window_start, 'America/New_York'), INTERVAL 30 MINUTE), '%H:%i') AS et_time,
       round(quantileDeterministic(0.5)(toFloat64(volume), toUInt64(window_start))) AS median_minute_volume,
       round(100 * count() / (30 * max(uniqExact(toDate(toTimeZone(window_start, 'America/New_York')))) OVER ()), 1) AS pct_minutes_traded
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'AAPL'
  AND window_start >= now() - INTERVAL 30 DAY
  AND toDate(toTimeZone(window_start, 'America/New_York')) IN (SELECT session_date FROM full_sessions)
  AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 240 AND 1199
GROUP BY et_time
ORDER BY et_time

Run your own version of this

The same 22 years of US equities and 12 years of options data are queryable in SQL or plain English. A free account runs 100 queries a day and takes no card.

More from this analysisPremarket and After-Hours Trading Hours (ET)
AAPL median quoted spread: regular session vs extended hours (past week, full sessions) series 2×3 → Stock headlines by ET hour of publication (last 30 days, all days) ranking 24×3 → Share of a month's volume by clock window: SPY, AAPL, NVDA (full sessions only) table 3×5 → The session envelope, read from SPY minute bars (last two weeks, ET) scalar 1×7 → Upcoming US stock market holidays and early closes series 12×6 → Upcoming US stock market holidays and early closes, from the exchange calendar series 12×6 → See all 2,170 queries →