gap_buckets

Name: gap_buckets
Creator: Strasmore
Published: 2026-10-16
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 2026-10-16, from tase-vs-us-trading-days.

as of 2026-10-16 ranking 5×4read in context →

gap_buckets — 5 rows by 4 columns, computed 2026-10-16 from US exchange, SIP and OPRA data.
gap_bucket	spy_rate	qqq_rate	aapl_rate
0.0-0.5%	70.9	62.1	46.7
0.5-1%	18.3	24.8	28.7
1-2%	8.1	10.4	16.5
2-3%	1.4	1.3	4.9
3%+	1.2	1.4	3.2

Rows × columns: 5 × 4
Computed: 2026-10-16
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_buckets, derived from the stored result.
Column	Type	Range	Notes
`gap_bucket`	text	5 distinct values (0.0-0.5%, 0.5-1%, 1-2%…)
`spy_rate`	number	1.2 to 70.9	ratio or rate
`qqq_rate`	number	1.3 to 62.1	ratio or rate
`aapl_rate`	number	3.2 to 46.7	ratio or rate

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 2026-10-16, 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 deduped AS
(
    SELECT
        ticker,
        date,
        max(toFloat64(open))  AS open_px,
        max(toFloat64(close)) AS close_px
    FROM global_markets.stocks_daily_aggs
    WHERE ticker IN ('SPY', 'QQQ', 'AAPL')
    GROUP BY ticker, date
),
chained AS
(
    SELECT
        ticker,
        date,
        open_px,
        lagInFrame(close_px) OVER (PARTITION BY ticker ORDER BY date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prev_close,
        lagInFrame(date)     OVER (PARTITION BY ticker ORDER BY date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prev_date
    FROM deduped
),
weekend AS
(
    SELECT
        ticker,
        abs(100 * (open_px / prev_close - 1)) AS abs_gap_pct
    FROM chained
    WHERE prev_close > 0
      AND open_px > 0
      AND toDayOfWeek(prev_date) = 5
      AND toDayOfWeek(date) = 1
),
bucketed AS
(
    SELECT
        ticker,
        multiIf(abs_gap_pct < 0.5, 1,
                abs_gap_pct < 1,   2,
                abs_gap_pct < 2,   3,
                abs_gap_pct < 3,   4,
                5) AS bucket_order,
        multiIf(abs_gap_pct < 0.5, '0.0-0.5%',
                abs_gap_pct < 1,   '0.5-1%',
                abs_gap_pct < 2,   '1-2%',
                abs_gap_pct < 3,   '2-3%',
                '3%+') AS gap_bucket
    FROM weekend
),
counted AS
(
    SELECT
        ticker,
        bucket_order,
        gap_bucket,
        count() AS n
    FROM bucketed
    GROUP BY ticker, bucket_order, gap_bucket
),
shares AS
(
    SELECT
        ticker,
        bucket_order,
        gap_bucket,
        round(100 * n / sum(n) OVER (PARTITION BY ticker), 1) AS share_pct
    FROM counted
)
SELECT
    gap_bucket,
    maxIf(share_pct, ticker = 'SPY')  AS spy_rate,
    maxIf(share_pct, ticker = 'QQQ')  AS qqq_rate,
    maxIf(share_pct, ticker = 'AAPL') AS aapl_rate
FROM shares
GROUP BY gap_bucket, bucket_order
ORDER BY bucket_order

SQL to run

WITH deduped AS
(
    SELECT
        ticker,
        date,
        max(toFloat64(open))  AS open_px,
        max(toFloat64(close)) AS close_px
    FROM global_markets.stocks_daily_aggs
    WHERE ticker IN ('SPY', 'QQQ', 'AAPL')
    GROUP BY ticker, date
),
chained AS
(
    SELECT
        ticker,
        date,
        open_px,
        lagInFrame(close_px) OVER (PARTITION BY ticker ORDER BY date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prev_close,
        lagInFrame(date)     OVER (PARTITION BY ticker ORDER BY date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prev_date
    FROM deduped
),
weekend AS
(
    SELECT
        ticker,
        abs(100 * (open_px / prev_close - 1)) AS abs_gap_pct
    FROM chained
    WHERE prev_close > 0
      AND open_px > 0
      AND toDayOfWeek(prev_date) = 5
      AND toDayOfWeek(date) = 1
),
bucketed AS
(
    SELECT
        ticker,
        multiIf(abs_gap_pct < 0.5, 1,
                abs_gap_pct < 1,   2,
                abs_gap_pct < 2,   3,
                abs_gap_pct < 3,   4,
                5) AS bucket_order,
        multiIf(abs_gap_pct < 0.5, '0.0-0.5%',
                abs_gap_pct < 1,   '0.5-1%',
                abs_gap_pct < 2,   '1-2%',
                abs_gap_pct < 3,   '2-3%',
                '3%+') AS gap_bucket
    FROM weekend
),
counted AS
(
    SELECT
        ticker,
        bucket_order,
        gap_bucket,
        count() AS n
    FROM bucketed
    GROUP BY ticker, bucket_order, gap_bucket
),
shares AS
(
    SELECT
        ticker,
        bucket_order,
        gap_bucket,
        round(100 * n / sum(n) OVER (PARTITION BY ticker), 1) AS share_pct
    FROM counted
)
SELECT
    gap_bucket,
    maxIf(share_pct, ticker = 'SPY')  AS spy_rate,
    maxIf(share_pct, ticker = 'QQQ')  AS qqq_rate,
    maxIf(share_pct, ticker = 'AAPL') AS aapl_rate
FROM shares
GROUP BY gap_bucket, bucket_order
ORDER BY bucket_order

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