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Friday close to Monday's first minute: absolute overnight move, 2023 to July 2026

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 2026-08-04, from What Happens If an Option Expires In the Money.

as of ranking 8×4read in context →
Friday close to Monday's first minute: absolute overnight move, 2023 to July 2026 — 8 rows by 4 columns, computed from US exchange, SIP and OPRA data.
tickerweekends_countmedian_weekend_gap_pctp90_weekend_gap_pct
NVDA1571.053.04
CVX1570.491.59
AAPL1570.491.71
MSFT1570.411.36
T1570.351.15
KO1570.310.68
JNJ1570.280.88
SPY1570.280.99
Rows × columns
8 × 4
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 Friday close to Monday's first minute: absolute overnight move, 2023 to July 2026, derived from the stored result.
ColumnTypeRangeNotes
ticker text 8 distinct values (AAPL, CVX, JNJ…)
weekends_count number every row is 157 count
median_weekend_gap_pct number 0.28 to 1.05 percent
p90_weekend_gap_pct number 0.68 to 3.04 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
WITH session_marks AS (
    SELECT ticker,
           toDate(toTimeZone(window_start, 'America/New_York')) AS session,
           argMax(toFloat64(close), window_start) AS close_px,
           argMin(toFloat64(close), window_start) AS first_minute_px,
           count() AS session_bars
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('SPY', 'AAPL', 'MSFT', 'NVDA', 'JNJ', 'CVX', 'KO', 'T')
      AND toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2023-01-02')
      AND toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-07-31')
      AND toDayOfWeek(toDate(toTimeZone(window_start, 'America/New_York'))) IN (1, 5)
      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
           + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
    GROUP BY ticker, session
    HAVING session_bars > 300
),
weekends AS (
    SELECT ticker,
           subtractDays(toMonday(session), if(toDayOfWeek(session) = 1, 7, 0)) AS weekend_id,
           argMaxIf(close_px, session, toDayOfWeek(session) = 5) AS friday_close,
           argMaxIf(first_minute_px, session, toDayOfWeek(session) = 1) AS monday_first_px
    FROM session_marks
    GROUP BY ticker, weekend_id
    HAVING countIf(toDayOfWeek(session) = 5) = 1
       AND countIf(toDayOfWeek(session) = 1) = 1
       AND friday_close > 0
)
SELECT ticker,
       count() AS weekends_count,
       round(quantileDeterministic(0.5)(abs(monday_first_px / friday_close - 1) * 100,
                                        cityHash64(toString(weekend_id))), 2) AS median_weekend_gap_pct,
       round(quantileDeterministic(0.9)(abs(monday_first_px / friday_close - 1) * 100,
                                        cityHash64(toString(weekend_id))), 2) AS p90_weekend_gap_pct
FROM weekends
GROUP BY ticker
ORDER BY median_weekend_gap_pct DESC

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