Every mega-cap ex-dividend event of the past six months: price path from the pre-ex close
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 2026-09-26, from Upcoming Ex-Dividend Dates: Stocks This Week.
| checkpoint | events | avg_dividend_pct | avg_move_pct | median_move_pct | pct_back_above_pre_ex |
|---|---|---|---|---|---|
| 1 ex-day open | 85 | 0.65 | -0.49 | -0.46 | 23.5 |
| 2 ex-day close | 85 | 0.65 | -0.62 | -0.27 | 37.6 |
| 3 one session later | 85 | 0.65 | -0.71 | -0.74 | 38.8 |
| 4 five sessions later | 85 | 0.65 | -0.61 | -0.05 | 49.4 |
| 5 ten sessions later | 85 | 0.65 | 0.2 | -0.28 | 47.1 |
- Rows × columns
- 5 × 6
- Computed
- Completeness
- No missing values
- Source
- US exchange, SIP and OPRA market data
- Licence
- Strasmore terms · free, no signup
What each column holds
| Column | Type | Range | Notes |
|---|---|---|---|
checkpoint |
text | 5 distinct values | |
events |
number | every row is 85 | |
avg_dividend_pct |
number | every row is 0.65 | percent |
avg_move_pct |
number | -0.71 to 0.2 | percent |
median_move_pct |
number | -0.74 to -0.05 | percent |
pct_back_above_pre_ex |
number | 23.5 to 49.4 | 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.
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 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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