What followed each kind of session: next-day outcome by the prior day's move, same twelve names

WITH daily AS (
    SELECT ticker,
           toDate(toTimeZone(window_start, 'America/New_York')) AS dt,
           argMax(toFloat64(close), window_start) AS close_px
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('SPY','AAPL','MSFT','KO','JNJ','XOM','JPM','WMT','NVDA','TSLA','PG','HD')
      AND toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2021-07-01')
      AND toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-06-30')
      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
           + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
    GROUP BY ticker, dt
),
returns AS (
    SELECT ticker, dt,
           close_px / lagInFrame(close_px) OVER (PARTITION BY ticker ORDER BY dt) - 1 AS ret
    FROM daily
),
paired AS (
    SELECT ticker, ret * 100 AS ret_pct,
           lagInFrame(ret) OVER (PARTITION BY ticker ORDER BY dt) * 100 AS prev_pct
    FROM returns
    WHERE ret IS NOT NULL AND ret > -0.5 AND ret < 0.5
)
SELECT multiIf(prev_pct <= -3, '1. down 3% or more',
               prev_pct <= -1, '2. down 1 to 3%',
               prev_pct < 1,  '3. flat, within 1%',
               prev_pct < 3,  '4. up 1 to 3%',
               '5. up 3% or more') AS prior_day_move,
       count() AS observations,
       round(median(ret_pct), 3) AS next_day_median_pct,
       round(100 * countIf(ret_pct > 0) / count(), 1) AS next_day_up_share_pct
FROM paired
WHERE prev_pct IS NOT NULL
GROUP BY prior_day_move
ORDER BY prior_day_move