Most repeated price and size pairings, AAPL, June 17, 2026
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 2026-08-06, from Iceberg Orders Explained: Hidden Liquidity.
| level_and_size | prints | first_et | last_et | hours_spanned |
|---|---|---|---|---|
| 300 shares at $300.54 | 67 | 09:34 | 09:58 | 0.4 |
| 200 shares at $295.15 | 49 | 15:06 | 15:53 | 0.8 |
| 300 shares at $300.93 | 46 | 09:33 | 09:34 | 0 |
| 200 shares at $295.1 | 41 | 14:56 | 15:54 | 1 |
| 200 shares at $295 | 36 | 14:57 | 15:53 | 0.9 |
| 200 shares at $295.09 | 34 | 14:55 | 15:53 | 1 |
| 200 shares at $295.17 | 27 | 14:56 | 15:54 | 1 |
| 200 shares at $297.92 | 23 | 11:03 | 11:19 | 0.3 |
| 200 shares at $295.27 | 21 | 15:08 | 15:54 | 0.8 |
| 200 shares at $295.89 | 20 | 14:11 | 15:59 | 1.8 |
| 200 shares at $295.2 | 20 | 14:55 | 15:49 | 0.9 |
| 200 shares at $295.13 | 20 | 14:56 | 15:52 | 0.9 |
- Rows × columns
- 12 × 5
- 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 |
|---|---|---|---|
level_and_size |
text | 12 distinct values | |
prints |
number | 20 to 67 | |
first_et |
text | 9 distinct values (09:33, 09:34, 11:03…) | |
last_et |
text | 8 distinct values (09:34, 09:58, 11:19…) | |
hours_spanned |
number | 0 to 1.8 |
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
concat(toString(size), ' shares at $', toString(round(toFloat64(price), 2))) AS level_and_size,
count() AS prints,
formatDateTime(toTimeZone(min(sip_timestamp), 'America/New_York'), '%H:%i') AS first_et,
formatDateTime(toTimeZone(max(sip_timestamp), 'America/New_York'), '%H:%i') AS last_et,
round(dateDiff('minute', min(sip_timestamp), max(sip_timestamp)) / 60.0, 1) AS hours_spanned
FROM global_markets.stocks_trades
WHERE ticker = 'AAPL'
AND sip_timestamp >= toDateTime('2026-06-17 04:00:00', 'UTC')
AND sip_timestamp < toDateTime('2026-06-18 04:00:00', 'UTC')
AND size >= 200
GROUP BY price, size
ORDER BY prints DESC
LIMIT 12
Work with this data in your AI assistant
Opens ready to query, with this page's data. Free, no account.