AAPL average print size across the February 2026 boundary
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 2026-08-12, from How Fractional Shares Hit the Tape.
| session_date | session_label | shares_per_print | volume_millions |
|---|---|---|---|
| 2026-02-09 | Feb 9 | 61.3 | 44.6 |
| 2026-02-10 | Feb 10 | 66.6 | 34.4 |
| 2026-02-11 | Feb 11 | 65.8 | 51.9 |
| 2026-02-12 | Feb 12 | 78.4 | 81.1 |
| 2026-02-13 | Feb 13 | 73.2 | 56.3 |
| 2026-02-17 | Feb 17 | 74.8 | 58.5 |
| 2026-02-18 | Feb 18 | 62.5 | 34.2 |
| 2026-02-19 | Feb 19 | 60.5 | 30.8 |
| 2026-02-20 | Feb 20 | 66.6 | 42.1 |
| 2026-02-23 | Feb 23 | 55.9 | 37.3 |
| 2026-02-24 | Feb 24 | 72.2 | 47 |
| 2026-02-25 | Feb 25 | 57.7 | 33.7 |
| 2026-02-26 | Feb 26 | 53.3 | 32.3 |
| 2026-02-27 | Feb 27 | 94.2 | 72.4 |
| 2026-03-02 | Mar 2 | 59.3 | 41.8 |
| 2026-03-03 | Mar 3 | 61.5 | 38.6 |
| 2026-03-04 | Mar 4 | 62.4 | 39.8 |
| 2026-03-05 | Mar 5 | 65.5 | 49.7 |
| 2026-03-06 | Mar 6 | 66.2 | 41.1 |
- Rows × columns
- 19 × 4
- Period covered
- to
- Computed
- Completeness
- No missing values
- Source
- US exchange, SIP and OPRA market data
- Licence
- Strasmore terms · free, no signup
What each column holds
| Column | Type | Range | Notes |
|---|---|---|---|
session_date |
date | 2026-02-09 to 2026-03-06 | |
session_label |
text | 19 distinct values (Feb 10, Feb 11, Feb 12…) | |
shares_per_print |
number | 53.3 to 94.2 | count |
volume_millions |
number | 30.8 to 81.1 | 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.
the exact SQL behind every number
SELECT
toString(date) AS session_date,
formatDateTime(date, '%b %e') AS session_label,
round(sum(toFloat64(volume)) / sum(transactions), 1) AS shares_per_print,
round(sum(toFloat64(volume)) / 1000000, 1) AS volume_millions
FROM global_markets.stocks_daily_aggs
WHERE ticker = 'AAPL'
AND date >= '2026-02-09'
AND date <= '2026-03-06'
GROUP BY date
HAVING sum(transactions) > 0
ORDER BY date
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