The ten busiest minutes of the trade tape (millions of prints)
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 2026-07-26, from Microstructure Deep-Dive: June 29, 2026.
| et_minute | trades_m |
|---|---|
| 15:59 | 3.98 |
| 15:58 | 2.29 |
| 09:30 | 1.81 |
| 15:57 | 1.59 |
| 15:55 | 1.36 |
| 15:56 | 1.24 |
| 15:54 | 1.01 |
| 15:50 | 1 |
| 10:15 | 0.88 |
| 15:53 | 0.8 |
- Rows × columns
- 10 × 2
- 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 |
|---|---|---|---|
et_minute |
text | 10 distinct values (09:30, 10:15, 15:50…) | |
trades_m |
number | 0.8 to 3.98 | 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.
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
formatDateTime(toTimeZone(toStartOfMinute(sip_timestamp), 'America/New_York'), '%H:%i') AS et_minute,
round(count() / 1e6, 2) AS trades_m
FROM global_markets.stocks_trades
WHERE sip_timestamp >= '2026-06-29 00:00:00' AND sip_timestamp < '2026-06-30 00:00:00'
GROUP BY et_minute
ORDER BY trades_m DESC
LIMIT 10
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