AAPL 25-session moves since January 2021, by size

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
    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)