Average days between consecutive ex-dividend dates, by schedule
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 2026-10-05, from US Dividend Frequency: Quarterly vs Japan.
| label | avg_days_between | gap_count |
|---|---|---|
| Monthly | 31 | 41825 |
| Quarterly | 94.1 | 33459 |
| Semi-annual | 189.2 | 8313 |
| Annual | 355.3 | 1934 |
- Rows × columns
- 4 × 3
- 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 |
|---|---|---|---|
label |
text | 4 distinct values (Annual, Monthly, Quarterly…) | |
avg_days_between |
number | 31 to 355.3 | |
gap_count |
number | 1,934 to 41,825 | count |
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 dated AS
(
SELECT
ticker,
ex_dividend_date,
max(frequency) AS freq
FROM global_markets.stocks_dividends
WHERE ex_dividend_date >= today() - 800
AND ex_dividend_date < today()
AND frequency IN (1, 2, 4, 12)
AND ticker NOT IN ('SPCX')
GROUP BY ticker, ex_dividend_date
),
gaps AS
(
SELECT
freq,
dateDiff('day',
lagInFrame(ex_dividend_date) OVER (PARTITION BY ticker
ORDER BY ex_dividend_date ASC
ROWS BETWEEN 1 PRECEDING AND CURRENT ROW),
ex_dividend_date) AS days_between
FROM dated
)
SELECT
multiIf(freq = 12, 'Monthly',
freq = 4, 'Quarterly',
freq = 2, 'Semi-annual',
'Annual') AS label,
round(avg(days_between), 1) AS avg_days_between,
count() AS gap_count
FROM gaps
WHERE days_between BETWEEN 10 AND 450
GROUP BY freq
ORDER BY avg_days_between
Work with this data in your AI assistant
Opens ready to query, with this page's data. Free, no account.