STRASMORE/EXPLORE 3,256 QUERIES

us_open_gap

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 2026-10-09, from nse-pre-open-session-explained.

as of table 8×5read in context →
us_open_gap — 8 rows by 5 columns, computed from US exchange, SIP and OPRA data.
tickersession_countgap_over_0_5_pctgap_over_1_pctavg_gap_pct
NVDA50069.847.41.22
AMZN50054.430.20.93
XOM50049.421.40.69
MSFT50048.421.20.73
AAPL50039.616.20.63
JPM50039.814.80.57
JNJ50028.89.20.44
KO50026.48.40.43
Rows × columns
8 × 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 us_open_gap, derived from the stored result.
ColumnTypeRangeNotes
ticker text 8 distinct values (AAPL, AMZN, JNJ…)
session_count number every row is 500 count
gap_over_0_5_pct number 26.4 to 69.8 percent
gap_over_1_pct number 8.4 to 47.4 percent
avg_gap_pct number 0.43 to 1.22 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.

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 bars AS
(
    SELECT
        ticker,
        date,
        argMax(toFloat64(open), _ingest_time)  AS open_px,
        argMax(toFloat64(close), _ingest_time) AS close_px
    FROM global_markets.stocks_daily_aggs
    WHERE ticker IN ('AAPL', 'MSFT', 'NVDA', 'AMZN', 'JPM', 'JNJ', 'KO', 'XOM')
      AND date >= '2024-10-01'
      AND date <  '2026-10-01'
    GROUP BY ticker, date
),
gaps AS
(
    SELECT
        ticker,
        date,
        open_px,
        lagInFrame(close_px, 1) OVER (PARTITION BY ticker ORDER BY date ASC
            ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prev_close
    FROM bars
)
SELECT
    ticker,
    count()                                                                  AS session_count,
    round(100 * countIf(abs(open_px / prev_close - 1) > 0.005) / count(), 1) AS gap_over_0_5_pct,
    round(100 * countIf(abs(open_px / prev_close - 1) > 0.01) / count(), 1)  AS gap_over_1_pct,
    round(100 * avg(abs(open_px / prev_close - 1)), 2)                       AS avg_gap_pct
FROM gaps
WHERE prev_close > 0
  AND open_px > 0
GROUP BY ticker
ORDER BY gap_over_1_pct DESC
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