STRASMORE/EXPLORE 2,170 QUERIES

AAPL 25-session moves since January 2021, by size

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 2026-08-13, from Ratio Spreads: Breakevens and Naked Risk.

as of ranking 6×3read in context →
AAPL 25-session moves since January 2021, by size — 6 rows by 3 columns, computed from US exchange, SIP and OPRA data.
move_bucketwindow_countshare_of_windows_pct
down more than 5%29921.7
down 0 to 5%27219.8
up 0 to 5%29221.2
up 5 to 10%28320.6
up 10 to 15%14910.8
up more than 15%805.8
Rows × columns
6 × 3
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 AAPL 25-session moves since January 2021, by size, derived from the stored result.
ColumnTypeRangeNotes
move_bucket text 6 distinct values
window_count number 80 to 299 count
share_of_windows_pct number 5.8 to 21.7 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.

the exact SQL behind every number
WITH
    daily AS
    (
        SELECT
            date,
            toFloat64(max(close)) AS close_px
        FROM global_markets.stocks_daily_aggs
        WHERE ticker = 'AAPL'
          AND date >= '2021-01-04'
          AND date <= '2026-07-31'
        GROUP BY date
    ),
    indexed AS
    (
        SELECT
            date,
            close_px,
            row_number() OVER (ORDER BY date) AS n
        FROM daily
    ),
    moves AS
    (
        SELECT 100 * (b.close_px / a.close_px - 1) AS fwd_move_pct
        FROM indexed AS a
        INNER JOIN indexed AS b ON b.n = a.n + 25
    ),
    totals AS
    (
        SELECT count() AS all_windows FROM moves
    )
SELECT
    multiIf(
        fwd_move_pct < -5,  'down more than 5%',
        fwd_move_pct <  0,  'down 0 to 5%',
        fwd_move_pct <  5,  'up 0 to 5%',
        fwd_move_pct < 10,  'up 5 to 10%',
        fwd_move_pct < 15,  'up 10 to 15%',
                            'up more than 15%')  AS move_bucket,
    count()                                       AS window_count,
    round(100 * count() / any(t.all_windows), 1)  AS share_of_windows_pct
FROM moves AS m
CROSS JOIN totals AS t
GROUP BY move_bucket
ORDER BY min(m.fwd_move_pct)

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