Every mega-cap ex-dividend event of the past six months: price path from the pre-ex close

Name: Every mega-cap ex-dividend event of the past six months: price path from the pre-ex close
Creator: Strasmore
Published: 2026-08-25
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 2026-08-25, from Upcoming Ex-Dividend Dates: Stocks This Week.

as of 2026-08-25 table 5×6read in context →

Every mega-cap ex-dividend event of the past six months: price path from the pre-ex close — 5 rows by 6 columns, computed 2026-08-25 from US exchange, SIP and OPRA data.
checkpoint	events	avg_dividend_pct	avg_move_pct	median_move_pct	pct_back_above_pre_ex
1 ex-day open	68	0.67	-0.42	-0.43	27.9
2 ex-day close	68	0.67	-0.63	-0.26	41.2
3 one session later	68	0.67	-0.86	-0.76	39.7
4 five sessions later	68	0.67	-0.33	0.39	55.9
5 ten sessions later	68	0.67	1.53	0.84	55.9

Rows × columns: 5 × 6
Computed: 2026-08-25
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 Every mega-cap ex-dividend event of the past six months: price path from the pre-ex close, derived from the stored result.
Column	Type	Range	Notes
`checkpoint`	text	5 distinct values
`events`	number	every row is 68
`avg_dividend_pct`	number	every row is 0.67	percent
`avg_move_pct`	number	-0.86 to 1.53	percent
`median_move_pct`	number	-0.76 to 0.84	percent
`pct_back_above_pre_ex`	number	27.9 to 55.9	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 2026-08-25, and the query below is what returned them.

the exact SQL behind every number

WITH rth AS (
    SELECT ticker,
           toDate(toTimeZone(window_start, 'America/New_York')) AS d,
           argMaxIf(toFloat64(close), window_start, (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959) AS close_px,
           argMinIf(toFloat64(open), window_start, (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959) AS open_px,
           countIf((toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959) AS bars
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('AAPL', 'MSFT', 'JNJ', 'KO', 'PG', 'XOM', 'CVX', 'JPM', 'HD', 'MCD',
                     'PEP', 'ABBV', 'MRK', 'PFE', 'VZ', 'T', 'CSCO', 'IBM', 'WMT', 'CAT',
                     'BAC', 'WFC', 'C', 'GS', 'MS', 'UNH', 'LLY', 'AMGN', 'BMY', 'GILD',
                     'TXN', 'QCOM', 'AVGO', 'ADP', 'LMT', 'RTX', 'HON', 'GE', 'MMM', 'UPS',
                     'LOW', 'TGT', 'COST', 'SBUX', 'NKE', 'DIS', 'CMCSA', 'DUK', 'SO', 'NEE')
      AND window_start >= toDateTime(today() - 190)
    GROUP BY ticker, d
    HAVING bars > 200
),
seq AS (
    SELECT ticker, d, open_px,
           lagInFrame(close_px, 1) OVER w AS pre_close,
           close_px AS ex_close,
           leadInFrame(close_px, 1) OVER w AS c1,
           leadInFrame(close_px, 5) OVER w AS c5,
           leadInFrame(close_px, 10) OVER w AS c10
    FROM rth
    WINDOW w AS (PARTITION BY ticker ORDER BY d ROWS BETWEEN 1 PRECEDING AND 10 FOLLOWING)
),
ev AS (
    SELECT s.ticker AS ticker, s.d AS ex_d, s.pre_close AS pre_close, s.open_px AS ex_open,
           s.ex_close AS ex_close, s.c1 AS c1, s.c5 AS c5, s.c10 AS c10,
           max(dv.cash_amount) AS div_amt
    FROM seq s
    JOIN global_markets.stocks_dividends dv ON dv.ticker = s.ticker AND dv.ex_dividend_date = s.d
    WHERE dv.cash_amount > 0
      AND dv.distribution_type = 'recurring'
      AND s.d >= today() - 160
      AND s.pre_close > 0 AND s.c1 > 0 AND s.c5 > 0 AND s.c10 > 0
    GROUP BY s.ticker, s.d, s.pre_close, s.open_px, s.ex_close, s.c1, s.c5, s.c10
),
paths AS (
    SELECT ticker, ex_d, pre_close, div_amt,
           arrayJoin([('1 ex-day open', ex_open),
                      ('2 ex-day close', ex_close),
                      ('3 one session later', c1),
                      ('4 five sessions later', c5),
                      ('5 ten sessions later', c10)]) AS chk
    FROM ev
)
SELECT chk.1 AS checkpoint,
       count() AS events,
       round(avg(100 * div_amt / pre_close), 2) AS avg_dividend_pct,
       round(avg(100 * (chk.2 - pre_close) / pre_close), 2) AS avg_move_pct,
       round(quantileDeterministic(0.5)(100 * (chk.2 - pre_close) / pre_close, cityHash64(ticker, ex_d)), 2) AS median_move_pct,
       round(100 * countIf(chk.2 >= pre_close) / count(), 1) AS pct_back_above_pre_ex
FROM paths
GROUP BY checkpoint
ORDER BY checkpoint

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