Nasdaq Closing Cross Explained: NOII and MOC
AAPL trade size by hour of the day (ET), September 10, 2026ranking ·
2026-09-17 · 16×4
Closing cross print as a share of full-day volume, eight Nasdaq-listed names, September 10, 2026series ·
2026-09-17 · 8×4
The six largest AAPL prints in the ten seconds from 4:00:00 p.m. ET, September 10, 2026table ·
2026-09-17 · 6×6
AAPL trades per second around the 4:00 p.m. close, September 10, 2026series ·
2026-09-17 · 20×4
Close-related sale condition codes in the exchange condition dictionaryranking ·
2026-09-17 · 4×3
What Is the Closing Auction? (Closing Cross)
Quarter-end (June 30) vs. mid-month (June 16, 2026): the same three closing auctionstable ·
2026-07-26 · 3×8
The tape's own labels for the close, straight from the code dictionaryranking ·
2026-07-26 · 4×3
The closing auction vs. everything else: SPY, AAPL, NVDA on July 2, 2026table ·
2026-07-26 · 3×10
The receipt: AAPL's auction print vs. its last continuous trade, July 2, 2026scalar ·
2026-07-26 · 1×12390
AAPL trade size by hour of the day (ET), September 10, 2026
AAPL trade size by hour of the day (ET), September 10, 2026
| et_hour | trades_k | median_trade_shares | avg_trade_shares |
|---|---|---|---|
| 04:00 | 9.1 | 8 | 30 |
| 05:00 | 3.6 | 6 | 27 |
| 06:00 | 4.3 | 10 | 33 |
| 07:00 | 6.5 | 9 | 39 |
| 08:00 | 10.1 | 10 | 42 |
| 09:00 | 185.1 | 20 | 62 |
| 10:00 | 196.9 | 4 | 40 |
| 11:00 | 231.9 | 5 | 44 |
| 12:00 | 161.1 | 18 | 56 |
| 13:00 | 135.2 | 19 | 52 |
| 14:00 | 101.5 | 12 | 49 |
| 15:00 | 170.3 | 20 | 52 |
| 16:00 | 5.6 | 6 | 2859 |
| 17:00 | 2.1 | 5 | 43 |
| 18:00 | 1.8 | 4 | 25 |
| 19:00 | 1.9 | 5 | 29 |
the exact SQL behind every number
SELECT
concat(if(cal.h < 10, '0', ''), toString(cal.h), ':00') AS et_hour,
round(ifNull(t.trade_count, 0) / 1000, 1) AS trades_k,
toUInt32(round(ifNull(t.median_trade_shares, 0), 0)) AS median_trade_shares,
toUInt32(round(ifNull(t.avg_trade_shares, 0), 0)) AS avg_trade_shares
FROM
(
SELECT toUInt8(4 + arrayJoin(range(16))) AS h
) AS cal
LEFT JOIN
(
SELECT
toHour(toTimeZone(sip_timestamp, 'America/New_York')) AS h,
count() AS trade_count,
quantileExact(0.5)(toFloat64(size)) AS median_trade_shares,
avg(toFloat64(size)) AS avg_trade_shares
FROM global_markets.stocks_trades
WHERE ticker = 'AAPL'
AND sip_timestamp >= toDateTime('2026-09-10 08:00:00', 'UTC')
AND sip_timestamp < toDateTime('2026-09-11 00:00:00', 'UTC')
GROUP BY h
) AS t ON t.h = cal.h
ORDER BY cal.h
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