STRASMORE/EXPLORE 2,433 QUERIES

print_sizes

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 2026-09-20, from is-cross-trading-legal.

as of ranking 4×4read in context →
print_sizes — 4 rows by 4 columns, computed from US exchange, SIP and OPRA data.
bucketprint_countprints_pctvolume_pct
1. under 100 (odd lot)89480790.0630.53
2. 100 to 999969409.7627.43
3. 1,000 to 9,99917560.185.77
4. 10,000 shares and up880.0136.27
Rows × columns
4 × 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 print_sizes, derived from the stored result.
ColumnTypeRangeNotes
bucket text 4 distinct values
print_count number 88 to 894,807 count
prints_pct number 0.01 to 90.06 percent
volume_pct number 5.77 to 36.27 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.

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.

SELECT
    bucket,
    print_count,
    round(100 * print_count / sum(print_count) OVER (), 2) AS prints_pct,
    round(100 * shares / sum(shares) OVER (), 2)           AS volume_pct
FROM
(
    SELECT
        multiIf(size >= 10000, '4. 10,000 shares and up',
                size >= 1000,  '3. 1,000 to 9,999',
                size >= 100,   '2. 100 to 999',
                               '1. under 100 (odd lot)') AS bucket,
        count()                                          AS print_count,
        toFloat64(sum(size))                             AS shares
    FROM global_markets.stocks_trades
    WHERE ticker = 'AAPL'
      AND sip_timestamp >= toDateTime('2026-06-10 08:00:00', 'UTC')
      AND sip_timestamp <  toDateTime('2026-06-11 00:00:00', 'UTC')
    GROUP BY bucket
)
ORDER BY bucket
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