gap_size_buckets

Name: gap_size_buckets
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 ranking 5×3read in context →

gap_size_buckets — 5 rows by 3 columns, computed 2026-10-09 from US exchange, SIP and OPRA data.
gap_bucket	session_count	share_pct
0.00-0.25%	1318	33
0.25-0.50%	899	22.5
0.50-1.00%	939	23.5
1.00-2.00%	583	14.6
2.00%+	261	6.5

Rows × columns: 5 × 3
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 gap_size_buckets, derived from the stored result.
Column	Type	Range	Notes
`gap_bucket`	text	5 distinct values (0.00-0.25%, 0.25-0.50%, 0.50-1.00%…)
`session_count`	number	261 to 1,318	count
`share_pct`	number	6.5 to 33	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
        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
),
bucketed AS
(
    SELECT
        multiIf(
            abs(open_px / prev_close - 1) <= 0.0025, '0.00-0.25%',
            abs(open_px / prev_close - 1) <= 0.005,  '0.25-0.50%',
            abs(open_px / prev_close - 1) <= 0.01,   '0.50-1.00%',
            abs(open_px / prev_close - 1) <= 0.02,   '1.00-2.00%',
                                                     '2.00%+') AS gap_bucket,
        count()                                                AS session_count
    FROM gaps
    WHERE prev_close > 0
      AND open_px > 0
    GROUP BY gap_bucket
)
SELECT
    gap_bucket,
    session_count,
    round(100 * session_count / sum(session_count) OVER (), 1) AS share_pct
FROM bucketed
ORDER BY gap_bucket

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
        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
),
bucketed AS
(
    SELECT
        multiIf(
            abs(open_px / prev_close - 1) <= 0.0025, '0.00-0.25%',
            abs(open_px / prev_close - 1) <= 0.005,  '0.25-0.50%',
            abs(open_px / prev_close - 1) <= 0.01,   '0.50-1.00%',
            abs(open_px / prev_close - 1) <= 0.02,   '1.00-2.00%',
                                                     '2.00%+') AS gap_bucket,
        count()                                                AS session_count
    FROM gaps
    WHERE prev_close > 0
      AND open_px > 0
    GROUP BY gap_bucket
)
SELECT
    gap_bucket,
    session_count,
    round(100 * session_count / sum(session_count) OVER (), 1) AS share_pct
FROM bucketed
ORDER BY gap_bucket

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