The XOM dividend streak, counted two ways, plus the years with no increase
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 XOM Dividend Increase History: Every Raise.
| basis | years_counted | starting_year |
|---|---|---|
| Annual total per share above the prior year | 19 | run from 2007 |
| Calendar years with an increase declared | 5 | run from 2021 |
| Calendar years with no increase declared | 1 | latest 2020 |
- Rows × columns
- 3 × 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 |
|---|---|---|---|
basis |
text | 3 distinct values | |
years_counted |
number | 1 to 19 | |
starting_year |
text | 3 distinct values |
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 quarterly AS
(
SELECT
ex_dividend_date AS ex_date,
toFloat64(max(cash_amount)) AS rate
FROM global_markets.stocks_dividends
WHERE ticker = 'XOM'
AND frequency = 4
AND ex_dividend_date >= '2005-01-01'
AND ex_dividend_date <= today()
GROUP BY ex_dividend_date
),
stepped AS
(
SELECT
ex_date,
rate,
lagInFrame(rate) OVER (ORDER BY ex_date ASC
ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS prev_rate
FROM quarterly
),
yearly AS
(
SELECT
toYear(ex_date) AS y,
sum(rate) AS total,
countIf(prev_rate > 0 AND rate > prev_rate) AS raises
FROM stepped
WHERE toYear(ex_date) >= 2006
AND toYear(ex_date) < toYear(today())
GROUP BY y
),
framed AS
(
SELECT
y,
total,
raises,
lagInFrame(total) OVER (ORDER BY y ASC
ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS prev_total
FROM yearly
),
marks AS
(
SELECT
max(y) AS last_year,
greatest(maxIf(y, prev_total > 0 AND total <= prev_total), min(y)) AS last_total_break,
greatest(maxIf(y, raises = 0), min(y)) AS last_rate_break,
countIf(raises = 0) AS flat_years,
maxIf(y, raises = 0) AS latest_flat_year
FROM framed
)
SELECT
tupleElement(t, 1) AS basis,
toUInt32(tupleElement(t, 2)) AS years_counted,
tupleElement(t, 3) AS starting_year
FROM marks
ARRAY JOIN
[
(toString('Annual total per share above the prior year'),
toInt32(last_year - last_total_break),
concat('run from ', toString(last_total_break + 1))),
(toString('Calendar years with an increase declared'),
toInt32(last_year - last_rate_break),
concat('run from ', toString(last_rate_break + 1))),
(toString('Calendar years with no increase declared'),
toInt32(flat_years),
if(flat_years = 0, 'none in window', concat('latest ', toString(latest_flat_year))))
] AS t
Work with this data in your AI assistant
Opens ready to query, with this page's data. Free, no account.