What Is a Trade-Through? ISO Orders Explained
Where 30 minutes of AAPL prints landed, by venueranking ·
2026-08-20 · 12×3
Distinct venues printing AAPL inside the same second, minute by minuteseries ·
2026-08-20 · 30×3
Share of prints by trade size: AAPL against KOranking ·
2026-08-20 · 5×4
Sale conditions that mark protection-rule exceptionstable ·
2026-08-20 · 11×3
Where 30 minutes of AAPL prints landed, by venue
Where 30 minutes of AAPL prints landed, by venue
| venue | print_count | share_pct |
|---|---|---|
| FINRA Alternative Display Facility | 48670 | 51 |
| Nasdaq | 20051 | 21 |
| NYSE Arca, Inc. | 10923 | 11.4 |
| Cboe BZX | 4694 | 4.9 |
| Investors Exchange | 2893 | 3 |
| Cboe EDGX | 2377 | 2.5 |
| Members Exchange | 2317 | 2.4 |
| New York Stock Exchange | 1455 | 1.5 |
| Cboe EDGA | 473 | 0.5 |
| Nasdaq Texas, Inc. | 455 | 0.5 |
| Cboe BYX | 450 | 0.5 |
| MIAX Pearl | 202 | 0.2 |
the exact SQL behind every number
WITH
prints AS
(
SELECT
toString(exchange) AS venue_id,
count() AS print_count
FROM global_markets.stocks_trades
WHERE ticker = 'AAPL'
AND sip_timestamp >= '2026-06-10 14:00:00'
AND sip_timestamp < '2026-06-10 14:30:00'
GROUP BY venue_id
),
venues AS
(
SELECT
toString(id) AS venue_id,
any(name) AS venue_name
FROM global_markets.stocks_exchanges
GROUP BY venue_id
)
SELECT
if(empty(v.venue_name), concat('Venue ', p.venue_id), v.venue_name) AS venue,
p.print_count AS print_count,
round(100 * p.print_count / sum(p.print_count) OVER (), 1) AS share_pct
FROM prints AS p
LEFT JOIN venues AS v USING (venue_id)
ORDER BY print_count DESC
LIMIT 12
More from this analysisWhat Is a Trade-Through? ISO Orders Explained
Share of prints by trade size: AAPL against KO
ranking 5×4
→
Distinct venues printing AAPL inside the same second, minute by minute
series 30×3
→
Sale conditions that mark protection-rule exceptions
table 11×3
→
Where AAPL trades printed, June 17 2026, 10:00 to 11:30 ET
ranking 17×3
→
See all 2,173 queries →