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Dividend adjustment factors on every KO ex-date since 2019

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 2026-08-22, from How split-adjusted price history works.

as of series 30×4read in context →
Dividend adjustment factors on every KO ex-date since 2019 — 30 rows by 4 columns, computed from US exchange, SIP and OPRA data.
ex_dateex_labeldividend_pctcumulative_pct
2019-03-14Mar 14, 20190.8650.87
2019-06-13Jun 13, 20190.7751.63
2019-09-13Sep 13, 20190.7262.35
2019-11-29Nov 29, 20190.7413.07
2020-03-13Mar 13, 20200.8693.91
2020-06-12Jun 12, 20200.94.78
2020-09-14Sep 14, 20200.8035.54
2020-11-30Nov 30, 20200.7786.28
2021-03-12Mar 12, 20210.8257.05
2021-06-14Jun 14, 20210.7487.75
2021-09-14Sep 14, 20210.7498.44
2021-11-30Nov 30, 20210.779.14
2022-03-14Mar 14, 20220.769.83
2022-06-14Jun 14, 20220.71710.48
2022-09-15Sep 15, 20220.72411.13
2022-11-30Nov 30, 20220.70411.75
2023-03-16Mar 16, 20230.76112.43
2023-06-15Jun 15, 20230.75613.09
2023-09-14Sep 14, 20230.78713.77
2023-11-30Nov 30, 20230.7914.45
2024-03-14Mar 14, 20240.79415.13
2024-06-14Jun 14, 20240.7715.78
2024-09-13Sep 13, 20240.68116.36
2024-11-29Nov 29, 20240.75316.99
2025-03-14Mar 14, 20250.73317.6
2025-06-13Jun 13, 20250.70618.18
2025-09-15Sep 15, 20250.76118.8
2025-12-01Dec 1, 20250.69719.37
2026-03-13Mar 13, 20260.68319.92
2026-06-15Jun 15, 20260.64120.43
Rows × columns
30 × 4
Period covered
to
Computed
Completeness
No missing values
Source
US exchange, SIP and OPRA market data
Licence
Strasmore terms · free, no signup
Formats
JSON · CSV · the SQL below

What each column holds

Column definitions for Dividend adjustment factors on every KO ex-date since 2019, derived from the stored result.
ColumnTypeRangeNotes
ex_date date 2019-03-14 to 2026-06-15
ex_label text 30 distinct values (Dec 1, 2025, Jun 12, 2020, Jun 13, 2019…)
dividend_pct number 0.641 to 0.9 percent
cumulative_pct number 0.87 to 20.43 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.

the exact SQL behind every number
WITH
px AS (
    SELECT
        date,
        toFloat64(any(close)) AS c
    FROM global_markets.stocks_daily_aggs
    WHERE ticker = 'KO'
      AND date >= '2018-10-01'
      AND date < today()
    GROUP BY date
),
lagged AS (
    SELECT
        date,
        lagInFrame(c) OVER (ORDER BY date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prior_close
    FROM px
),
divs AS (
    SELECT
        ex_dividend_date            AS d_date,
        toFloat64(max(cash_amount)) AS cash
    FROM global_markets.stocks_dividends
    WHERE ticker = 'KO'
      AND ex_dividend_date >= '2019-01-01'
      AND ex_dividend_date < today()
      AND cash_amount > 0
    GROUP BY ex_dividend_date
)
SELECT
    toString(divs.d_date)                           AS ex_date,
    formatDateTime(divs.d_date, '%b %e, %Y')        AS ex_label,
    round(100 * divs.cash / lagged.prior_close, 3)  AS dividend_pct,
    round(100 * (1 - exp(sum(log(1 - divs.cash / lagged.prior_close))
        OVER (ORDER BY divs.d_date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW))), 2) AS cumulative_pct
FROM divs
INNER JOIN lagged ON lagged.date = divs.d_date
WHERE lagged.prior_close > 0
ORDER BY divs.d_date

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