STRASMORE/EXPLORE 3,214 QUERIES

Overnight gap between one close and the next open, year to Sep 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 2026-10-08, from Stock Order Types Explained: The Core Four.

as of ranking 6×4read in context →
Overnight gap between one close and the next open, year to Sep 2026 — 6 rows by 4 columns, computed from US exchange, SIP and OPRA data.
symbolavg_gap_pctworst_gap_pctgap_over_1pct_count
NVDA1.096.3113
MSFT0.8312.1369
AAPL0.518.5829
PG0.485.0425
KO0.465.4126
SPY0.42.617
Rows × columns
6 × 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 Overnight gap between one close and the next open, year to Sep 2026, derived from the stored result.
ColumnTypeRangeNotes
symbol text 6 distinct values (AAPL, KO, MSFT…)
avg_gap_pct number 0.4 to 1.09 percent
worst_gap_pct number 2.6 to 12.13 percent
gap_over_1pct_count number 17 to 113 count

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.

Run it yourself

This is the exact query behind the result above. Change a ticker, a date or a column and run it against the warehouse — no account, no key. The no-signup tier is smaller than the one this page was computed on; a query that reaches past it comes back saying which plan runs it.

WITH sessions AS
(
    SELECT
        ticker,
        date,
        toFloat64(any(open))  AS open_px,
        toFloat64(any(close)) AS close_px
    FROM global_markets.stocks_daily_aggs
    WHERE ticker IN ('SPY', 'AAPL', 'MSFT', 'NVDA', 'KO', 'PG')
      AND date >= '2025-10-01'
      AND date <  '2026-10-01'
    GROUP BY ticker, date
),
gaps AS
(
    SELECT
        ticker,
        abs(open_px / prev_close - 1) * 100 AS gap_pct
    FROM
    (
        SELECT
            ticker,
            open_px,
            lagInFrame(close_px) OVER (
                PARTITION BY ticker
                ORDER BY date ASC
                ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS prev_close
        FROM sessions
    )
    WHERE prev_close > 0
)
SELECT
    ticker                 AS symbol,
    round(avg(gap_pct), 2) AS avg_gap_pct,
    round(max(gap_pct), 2) AS worst_gap_pct,
    countIf(gap_pct >= 1)  AS gap_over_1pct_count
FROM gaps
GROUP BY ticker
ORDER BY avg_gap_pct DESC
⌘/Ctrl + Enter

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