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QQQ and SPY: June 29 ranked against the trailing month of sessions (rank 1 = biggest absolute move)

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 Market Recap: June 29, 2026, The Day in Numbers.

as of scalar 1×10read in context →
qqq close over close pct
2.57
qqq abs move rank
5
qqq sessions compared
21
qqq biggest move of month pct
4.76
qqq up sessions
10
spy close over close pct
1.62
spy abs move rank
4
spy sessions compared
21
spy open to close pct
0.59
first session
May 29, 2026
Rows × columns
1 × 10
Period covered
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 QQQ and SPY: June 29 ranked against the trailing month of sessions (rank 1 = biggest absolute move), derived from the stored result.
ColumnTypeRangeNotes
qqq_close_over_close_pct number every row is 2.57 percent
qqq_abs_move_rank number every row is 5
qqq_sessions_compared number every row is 21
qqq_biggest_move_of_month_pct number every row is 4.76 percent
qqq_up_sessions number every row is 10
spy_close_over_close_pct number every row is 1.62 percent
spy_abs_move_rank number every row is 4
spy_sessions_compared number every row is 21
spy_open_to_close_pct number every row is 0.59 percent
first_session date May 29, 20

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
    round(anyIf(cc_pct, ticker = 'QQQ' AND d = toDate('2026-06-29')), 2) AS qqq_close_over_close_pct,
    arrayCount(x -> x > abs(anyIf(cc_pct, ticker = 'QQQ' AND d = toDate('2026-06-29'))), groupArrayIf(abs(cc_pct), ticker = 'QQQ' AND d != toDate('2026-06-29'))) + 1 AS qqq_abs_move_rank,
    countIf(ticker = 'QQQ') AS qqq_sessions_compared,
    round(max(if(ticker = 'QQQ', abs(cc_pct), 0)), 2) AS qqq_biggest_move_of_month_pct,
    countIf(ticker = 'QQQ' AND cc_pct > 0) AS qqq_up_sessions,
    round(anyIf(cc_pct, ticker = 'SPY' AND d = toDate('2026-06-29')), 2) AS spy_close_over_close_pct,
    arrayCount(x -> x > abs(anyIf(cc_pct, ticker = 'SPY' AND d = toDate('2026-06-29'))), groupArrayIf(abs(cc_pct), ticker = 'SPY' AND d != toDate('2026-06-29'))) + 1 AS spy_abs_move_rank,
    countIf(ticker = 'SPY') AS spy_sessions_compared,
    round(anyIf(oc_pct, ticker = 'SPY' AND d = toDate('2026-06-29')), 2) AS spy_open_to_close_pct,
    concat(monthName(min(d)), ' ', toString(toDayOfMonth(min(d))), ', ', toString(toYear(min(d)))) AS first_session
FROM (
    SELECT ticker, d,
           (close_px / lagInFrame(close_px) OVER (PARTITION BY ticker ORDER BY d) - 1) * 100 AS cc_pct,
           oc_pct
    FROM (
        SELECT ticker,
               toDate(toTimeZone(window_start, 'America/New_York')) AS d,
               argMax(toFloat64(close), window_start) AS close_px,
               (argMax(toFloat64(close), window_start) / argMin(toFloat64(open), window_start) - 1) * 100 AS oc_pct
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker IN ('SPY', 'QQQ')
          AND window_start >= toDateTime('2026-05-28 00:00:00')
          AND window_start < toDateTime('2026-06-30 00:00:00')
          AND (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199
        GROUP BY ticker, d
    )
)
WHERE isFinite(cc_pct)

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