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Venues quoting and printing the same stock in one 15-minute window

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 2026-08-13, from Self-Match Prevention and Wash Trades.

as of ranking 6×3read in context →
Venues quoting and printing the same stock in one 15-minute window — 6 rows by 3 columns, computed from US exchange, SIP and OPRA data.
tickerquoting_venuesprinting_venues
AAPL1617
MSFT1617
NVDA1617
JNJ1416
SPY1417
KO1117
Rows × columns
6 × 3
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 Venues quoting and printing the same stock in one 15-minute window, derived from the stored result.
ColumnTypeRangeNotes
ticker text 6 distinct values (AAPL, JNJ, KO…)
quoting_venues number 11 to 16
printing_venues number 16 to 17

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
    q.ticker          AS ticker,
    q.quoting_venues  AS quoting_venues,
    t.printing_venues AS printing_venues
FROM
(
    SELECT
        ticker,
        countDistinct(bid_exchange) AS quoting_venues
    FROM global_markets.cache_stocks_quotes
    WHERE ticker IN ('AAPL', 'MSFT', 'NVDA', 'SPY', 'KO', 'JNJ')
      AND sip_timestamp >= toDateTime('2026-06-10 14:00:00', 'UTC')
      AND sip_timestamp <  toDateTime('2026-06-10 14:15:00', 'UTC')
      AND bid_price > 0
    GROUP BY ticker
) AS q
INNER JOIN
(
    SELECT
        ticker,
        countDistinct(exchange) AS printing_venues
    FROM global_markets.stocks_trades
    WHERE ticker IN ('AAPL', 'MSFT', 'NVDA', 'SPY', 'KO', 'JNJ')
      AND sip_timestamp >= toDateTime('2026-06-10 14:00:00', 'UTC')
      AND sip_timestamp <  toDateTime('2026-06-10 14:15:00', 'UTC')
    GROUP BY ticker
) AS t ON t.ticker = q.ticker
ORDER BY quoting_venues DESC, ticker

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