Compound dividend growth over 5, 10 and 25 year windows
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 2026-10-08, from KO Dividend History: Coca-Cola Payouts by Year.
| label | window_from | window_through | start_per_share | end_per_share | year_steps | years_increased | cagr_pct |
|---|---|---|---|---|---|---|---|
| Last 5 years | 2020 | 2025 | 1.64 | 2.04 | 5 | 5 | 4.46 |
| Last 10 years | 2015 | 2025 | 1.32 | 2.04 | 10 | 10 | 4.45 |
| Last 25 years | 2003 | 2025 | 0.33 | 2.04 | 22 | 22 | 8.63 |
| Full record | 2003 | 2025 | 0.33 | 2.04 | 22 | 22 | 8.63 |
- Rows × columns
- 4 × 8
- 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 | |
window_from |
text | 3 distinct values (2003, 2015, 2020) | |
window_through |
text | 1 distinct value (2025) | |
start_per_share |
number | 0.33 to 1.64 | |
end_per_share |
number | every row is 2.04 | |
year_steps |
number | 5 to 22 | |
years_increased |
number | 5 to 22 | |
cagr_pct |
number | 4.45 to 8.63 | 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 payments AS
(
SELECT
id,
any(ex_dividend_date) AS ex_date,
any(split_adjusted_cash_amount) AS adj_amount
FROM global_markets.stocks_dividends
WHERE ticker = 'KO'
AND toYear(ex_dividend_date) < toYear(today())
GROUP BY id
),
yearly AS
(
SELECT
toYear(ex_date) AS yr,
round(sum(toFloat64(adj_amount)), 4) AS annual
FROM payments
GROUP BY yr
),
steps AS
(
SELECT
a.yr AS yr,
a.annual AS annual,
b.annual AS prior
FROM yearly AS a
LEFT JOIN yearly AS b ON b.yr = a.yr - 1
),
span AS
(
SELECT min(yr) AS first_yr, max(yr) AS last_yr FROM yearly
),
windows AS
(
SELECT
tupleElement(w, 1) AS ord,
tupleElement(w, 2) AS window_label,
tupleElement(w, 3) AS lookback
FROM
(
SELECT arrayJoin([(1, 'Last 5 years', 5), (2, 'Last 10 years', 10), (3, 'Last 25 years', 25), (4, 'Full record', 200)]) AS w
)
)
SELECT
w.window_label AS label,
toString(min(s.yr)) AS window_from,
toString(max(s.yr)) AS window_through,
round(argMin(s.annual, s.yr), 4) AS start_per_share,
round(argMax(s.annual, s.yr), 4) AS end_per_share,
max(s.yr) - min(s.yr) AS year_steps,
countIf(s.annual > s.prior AND s.prior > 0 AND s.yr > greatest(p.last_yr - w.lookback, p.first_yr)) AS years_increased,
round(100 * (pow(argMax(s.annual, s.yr) / argMin(s.annual, s.yr), 1.0 / (max(s.yr) - min(s.yr))) - 1), 2) AS cagr_pct
FROM steps AS s
CROSS JOIN span AS p
CROSS JOIN windows AS w
WHERE s.yr >= greatest(p.last_yr - w.lookback, p.first_yr)
GROUP BY w.ord, w.window_label
ORDER BY w.ord
Work with this data in your AI assistant
Opens ready to query, with this page's data. Free, no account.