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Weekend gaps: prior close to next open, six widely held names, August 2024 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 2026-08-01, from How Risky Is Options Trading? The Mechanics.

as of table 6×5read in context →
Weekend gaps: prior close to next open, six widely held names, August 2024 to July 2026 — 6 rows by 5 columns, computed from US exchange, SIP and OPRA data.
tickergap_countmedian_weekend_gap_pctp95_weekend_gap_pctlargest_weekend_gap_pct
TSLA1041.446.4610.81
NVDA1041.174.2914.19
AAPL1040.442.589.42
MSFT1040.511.94.73
SPY1040.381.514
KO1040.240.985.3
Rows × columns
6 × 5
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 Weekend gaps: prior close to next open, six widely held names, August 2024 to July 2026, derived from the stored result.
ColumnTypeRangeNotes
ticker text 6 distinct values (AAPL, KO, MSFT…)
gap_count number every row is 104 count
median_weekend_gap_pct number 0.24 to 1.44 percent
p95_weekend_gap_pct number 0.98 to 6.46 percent
largest_weekend_gap_pct number 4 to 14.19 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 sessions AS (
    SELECT ticker,
           toDate(toTimeZone(window_start, 'America/New_York')) AS session_date,
           argMin(toFloat64(open), window_start) AS session_open,
           argMax(toFloat64(close), window_start) AS session_close
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('AAPL', 'MSFT', 'NVDA', 'TSLA', 'KO', 'SPY')
      AND window_start >= toDateTime('2024-08-01 00:00:00')
      AND window_start < toDateTime('2026-08-01 00:00:00')
      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
           + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
    GROUP BY ticker, session_date
),
linked AS (
    SELECT ticker,
           session_date,
           session_open,
           any(session_close) OVER (PARTITION BY ticker ORDER BY session_date
                                    ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS prev_close,
           any(session_date) OVER (PARTITION BY ticker ORDER BY session_date
                                   ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS prev_date
    FROM sessions
),
gaps AS (
    SELECT ticker,
           session_date,
           abs(session_open / prev_close - 1) * 100 AS gap_pct
    FROM linked
    WHERE prev_close > 0
      AND dateDiff('day', prev_date, session_date) >= 3
)
SELECT ticker,
       count() AS gap_count,
       round(quantileDeterministic(0.5)(gap_pct, cityHash64(session_date)), 2) AS median_weekend_gap_pct,
       round(quantileDeterministic(0.95)(gap_pct, cityHash64(session_date)), 2) AS p95_weekend_gap_pct,
       round(max(gap_pct), 2) AS largest_weekend_gap_pct
FROM gaps
GROUP BY ticker
ORDER BY p95_weekend_gap_pct DESC

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