Distance between trailing and forward dividend yield, by payment 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 2026-10-04, from Trailing vs Forward Dividend Yield Explained.
| schedule | payers | median_trailing_pct | median_forward_pct | median_gap_pp | p90_gap_pp | pct_gap_over_half_point |
|---|---|---|---|---|---|---|
| quarterly | 1111 | 2.09 | 2.14 | 0.02 | 0.208 | 5.1 |
| monthly | 20 | 6.34 | 6.14 | 0.027 | 0.786 | 15 |
| semi-annual | 19 | 1.02 | 1.02 | 0.003 | 0.514 | 15.8 |
| annual | 10 | 0.62 | 0.62 | 0 | 0 | 0 |
- Rows × columns
- 4 × 7
- 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 |
|---|---|---|---|
schedule |
text | 4 distinct values (annual, monthly, quarterly…) | |
payers |
number | 10 to 1,111 | |
median_trailing_pct |
number | 0.62 to 6.34 | percent |
median_forward_pct |
number | 0.62 to 6.14 | percent |
median_gap_pp |
number | 0 to 0.027 | |
p90_gap_pp |
number | 0 to 0.786 | |
pct_gap_over_half_point |
number | 0 to 15.8 | 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 universe AS (
SELECT ticker,
argMax(price, date) AS last_price
FROM global_markets.stocks_ratios
WHERE date = (SELECT max(date) FROM global_markets.stocks_ratios)
AND price >= 5
AND market_cap >= 1000000000
GROUP BY ticker
),
paid AS (
SELECT ticker,
sum(cash_amount) AS ttm_cash,
argMax(cash_amount, ex_dividend_date) AS latest_cash,
argMax(frequency, ex_dividend_date) AS pay_frequency
FROM global_markets.stocks_dividends
WHERE distribution_type = 'recurring'
AND cash_amount > 0
AND frequency IN (1, 2, 4, 12)
AND ex_dividend_date > today() - INTERVAL 1 YEAR
AND ex_dividend_date <= today()
GROUP BY ticker
)
SELECT multiIf(d.pay_frequency = 12, 'monthly',
d.pay_frequency = 4, 'quarterly',
d.pay_frequency = 2, 'semi-annual',
'annual') AS schedule,
count() AS payers,
round(quantileDeterministic(0.5)(toFloat64(d.ttm_cash) / toFloat64(u.last_price) * 100,
cityHash64(u.ticker)), 2) AS median_trailing_pct,
round(quantileDeterministic(0.5)(toFloat64(d.latest_cash) * d.pay_frequency / toFloat64(u.last_price) * 100,
cityHash64(u.ticker)), 2) AS median_forward_pct,
round(quantileDeterministic(0.5)(abs(toFloat64(d.latest_cash) * d.pay_frequency - toFloat64(d.ttm_cash))
/ toFloat64(u.last_price) * 100,
cityHash64(u.ticker)), 3) AS median_gap_pp,
round(quantileDeterministic(0.9)(abs(toFloat64(d.latest_cash) * d.pay_frequency - toFloat64(d.ttm_cash))
/ toFloat64(u.last_price) * 100,
cityHash64(u.ticker)), 3) AS p90_gap_pp,
round(100 * countIf(abs(toFloat64(d.latest_cash) * d.pay_frequency - toFloat64(d.ttm_cash))
/ toFloat64(u.last_price) * 100 >= 0.5) / count(), 1) AS pct_gap_over_half_point
FROM universe AS u
INNER JOIN paid AS d ON u.ticker = d.ticker
GROUP BY schedule
ORDER BY payers DESC
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