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Quarter-end (June 30) vs. mid-month (June 16, 2026): the same three closing auctions

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 What Is the Closing Auction? (Closing Cross).

as of table 3×8read in context →
Quarter-end (June 30) vs. mid-month (June 16, 2026): the same three closing auctions — 3 rows by 8 columns, computed from US exchange, SIP and OPRA data.
tickerjun16_auction_print_countjun30_auction_print_countjun16_auction_shares_mjun30_auction_shares_mjun30_vs_jun16_xjun16_auction_pctjun30_auction_pct
SPY111.8421.12.73.6
AAPL117.4921.712.918.833.2
NVDA1123.4741.141.818.524.7
Rows × columns
3 × 8
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 Quarter-end (June 30) vs. mid-month (June 16, 2026): the same three closing auctions, derived from the stored result.
ColumnTypeRangeNotes
ticker text 3 distinct values (AAPL, NVDA, SPY)
jun16_auction_print_count number every row is 1 count
jun30_auction_print_count number every row is 1 count
jun16_auction_shares_m number 1.84 to 23.47 count
jun30_auction_shares_m number 2 to 41.14 count
jun30_vs_jun16_x number 1.1 to 2.9
jun16_auction_pct number 2.7 to 18.8 percent
jun30_auction_pct number 3.6 to 33.2 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.

the exact SQL behind every number 
SELECT
    ticker,
    countIf(has(conditions, 8) AND sip_timestamp < '2026-06-17 00:00:00') AS jun16_auction_print_count,
    countIf(has(conditions, 8) AND sip_timestamp >= '2026-06-30 00:00:00') AS jun30_auction_print_count,
    round(toFloat64(maxIf(size, has(conditions, 8) AND sip_timestamp < '2026-06-17 00:00:00')) / 1e6, 2) AS jun16_auction_shares_m,
    round(toFloat64(maxIf(size, has(conditions, 8) AND sip_timestamp >= '2026-06-30 00:00:00')) / 1e6, 2) AS jun30_auction_shares_m,
    round(toFloat64(maxIf(size, has(conditions, 8) AND sip_timestamp >= '2026-06-30 00:00:00')) / toFloat64(maxIf(size, has(conditions, 8) AND sip_timestamp < '2026-06-17 00:00:00')), 1) AS jun30_vs_jun16_x,
    round(100 * toFloat64(maxIf(size, has(conditions, 8) AND sip_timestamp < '2026-06-17 00:00:00')) / toFloat64(sumIf(size, NOT hasAny(conditions, [15, 16, 38]) AND sip_timestamp < '2026-06-17 00:00:00')), 1) AS jun16_auction_pct,
    round(100 * toFloat64(maxIf(size, has(conditions, 8) AND sip_timestamp >= '2026-06-30 00:00:00')) / toFloat64(sumIf(size, NOT hasAny(conditions, [15, 16, 38]) AND sip_timestamp >= '2026-06-30 00:00:00')), 1) AS jun30_auction_pct
FROM global_markets.stocks_trades
WHERE ticker IN ('SPY', 'AAPL', 'NVDA')
  AND ((sip_timestamp >= '2026-06-16 00:00:00' AND sip_timestamp < '2026-06-17 00:00:00')
    OR (sip_timestamp >= '2026-06-30 00:00:00' AND sip_timestamp < '2026-07-01 00:00:00'))
GROUP BY ticker
ORDER BY indexOf(['SPY', 'AAPL', 'NVDA'], ticker)

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More from this analysisWhat Is the Closing Auction? (Closing Cross)
The closing auction vs. everything else: SPY, AAPL, NVDA on July 2, 2026 table 3×10 → The tape's own labels for the close, straight from the code dictionary ranking 4×3 → The receipt: AAPL's auction print vs. its last continuous trade, July 2, 2026 scalar 1×12 → The cost-to-trade ladder: median quoted spread in bps of the midpoint, regular hours, recent completed sessions table 12×5 → The census by name: eight liquid tickers and two thin small caps, recent completed sessions table 10×7 → The one-cent floor: share price, percent of quotes exactly one cent wide, and what a penny costs in bps table 5×6 → See all 2,170 queries →