Overnight gap versus intraday run: what the next session did

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,
        max(toFloat64(open))   AS o,
        max(toFloat64(close))  AS c,
        max(toFloat64(volume)) AS vol
    FROM global_markets.stocks_daily_aggs
    WHERE date >= today() - 1095
      AND date <= today() - 2
      AND ifNull(otc, 0) = 0
      AND ticker NOT IN ('SPCX')
    GROUP BY ticker, date
),
seq AS
(
    SELECT
        ticker,
        date,
        o,
        c,
        vol,
        lagInFrame(c)     OVER (PARTITION BY ticker ORDER BY date ASC ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS prev_c,
        leadInFrame(o)    OVER (PARTITION BY ticker ORDER BY date ASC ROWS BETWEEN 1 FOLLOWING AND 1 FOLLOWING) AS next_o,
        leadInFrame(c)    OVER (PARTITION BY ticker ORDER BY date ASC ROWS BETWEEN 1 FOLLOWING AND 1 FOLLOWING) AS next_c,
        leadInFrame(date) OVER (PARTITION BY ticker ORDER BY date ASC ROWS BETWEEN 1 FOLLOWING AND 1 FOLLOWING) AS next_date
    FROM bars
),
movers AS
(
    SELECT
        date,
        ticker,
        100 * (c / prev_c - 1)                        AS gain_pct,
        (o / prev_c - 1) / (c / prev_c - 1)           AS gap_share,
        100 * (next_c / next_o - 1)                   AS next_oc_pct,
        100 * (next_c / c - 1)                        AS next_cc_pct,
        row_number() OVER (PARTITION BY date ORDER BY c / prev_c DESC, ticker ASC) AS rnk
    FROM seq
    WHERE prev_c >= 5
      AND next_o > 0
      AND next_c > 0
      AND c * vol >= 5000000
      AND dateDiff('day', date, next_date) <= 6
)
SELECT
    multiIf(gap_share >= 0.7, 'mostly overnight gap',
            gap_share >= 0.3, 'mixed',
                              'mostly intraday')                                     AS move_shape,
    count()                                                                          AS observations,
    round(quantileDeterministic(0.5)(next_cc_pct, cityHash64(ticker, toString(date))), 2) AS median_next_cc_pct,
    round(quantileDeterministic(0.5)(next_oc_pct, cityHash64(ticker, toString(date))), 2) AS median_next_oc_pct,
    round(avg(next_cc_pct), 2)                                                       AS mean_next_cc_pct
FROM movers
WHERE rnk <= 20
  AND gain_pct >= 5
GROUP BY move_shape
ORDER BY min(gap_share) ASC