us_open_gap

Name: us_open_gap
Creator: Strasmore
Published: 2026-10-09
License: https://www.strasmore.com/terms/

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 2026-10-09 table 8×5read in context →

us_open_gap — 8 rows by 5 columns, computed 2026-10-09 from US exchange, SIP and OPRA data.
ticker	session_count	gap_over_0_5_pct	gap_over_1_pct	avg_gap_pct
NVDA	500	69.8	47.4	1.22
AMZN	500	54.4	30.2	0.93
XOM	500	49.4	21.4	0.69
MSFT	500	48.4	21.2	0.73
AAPL	500	39.6	16.2	0.63
JPM	500	39.8	14.8	0.57
JNJ	500	28.8	9.2	0.44
KO	500	26.4	8.4	0.43

Rows × columns: 8 × 5
Computed: 2026-10-09
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.
Column	Type	Range	Notes
`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 2026-10-09, 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

SQL to run

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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