payout_trend

Name: payout_trend
Creator: Strasmore
Published: 2026-09-26
License: https://www.strasmore.com/terms/

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 jnj-dividend-increase-history.

as of 2026-09-26 table 8×5read in context →

payout_trend — 8 rows by 5 columns, computed 2026-09-26 from US exchange, SIP and OPRA data.
year	dividends_per_share	diluted_eps	eps_payout_pct	cash_payout_pct
2018	3.54	5.61	63.1	42.8
2019	3.75	5.63	66.6	42.4
2020	3.98	5.51	72.2	42.5
2021	4.19	7.81	53.6	47.1
2022	4.45	6.73	66.1	55.1
2023	4.7	13.72	34.3	51.6
2024	4.91	5.79	84.8	48.7
2025	5.14	11.03	46.6	50.5

Rows × columns: 8 × 5
Computed: 2026-09-26
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 payout_trend, derived from the stored result.
Column	Type	Range	Notes
`year`	text	8 distinct values (2018, 2019, 2020…)
`dividends_per_share`	number	3.54 to 5.14
`diluted_eps`	number	5.51 to 13.72
`eps_payout_pct`	number	34.3 to 84.8	percent
`cash_payout_pct`	number	42.4 to 55.1	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 2026-09-26, 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
    per_share AS
    (
        SELECT
            toYear(ex_date) AS fy,
            round(sum(amount), 4) AS dividends_per_share,
            count() AS payments
        FROM
        (
            SELECT
                ex_dividend_date AS ex_date,
                max(toFloat64(cash_amount)) AS amount
            FROM global_markets.stocks_dividends
            WHERE ticker = 'JNJ'
              AND frequency = 4
              AND ex_dividend_date >= '2018-01-01'
              AND ex_dividend_date <  '2026-01-01'
            GROUP BY ex_dividend_date
        )
        GROUP BY fy
        HAVING payments = 4
    ),
    eps_annual AS
    (
        SELECT
            toYear(period_end - 7) AS fy,
            argMax(toFloat64(diluted_earnings_per_share), (filing_date, period_end)) AS diluted_eps
        FROM global_markets.stocks_income_statements
        WHERE has(tickers, 'JNJ')
          AND timeframe = 'annual'
          AND period_end >= '2018-01-01'
          AND period_end <  '2026-06-01'
        GROUP BY fy
    ),
    cash AS
    (
        SELECT
            toYear(period_end - 7) AS fy,
            argMax(toFloat64(dividends), (filing_date, period_end)) AS dividends_paid,
            argMax(toFloat64(net_cash_from_operating_activities), (filing_date, period_end)) AS operating_cash
        FROM global_markets.stocks_cash_flow_statements
        WHERE has(tickers, 'JNJ')
          AND timeframe = 'annual'
          AND period_end >= '2018-01-01'
          AND period_end <  '2026-06-01'
        GROUP BY fy
    )
SELECT
    toString(p.fy) AS year,
    p.dividends_per_share AS dividends_per_share,
    round(e.diluted_eps, 2) AS diluted_eps,
    round(p.dividends_per_share / e.diluted_eps * 100, 1) AS eps_payout_pct,
    round(abs(c.dividends_paid) / c.operating_cash * 100, 1) AS cash_payout_pct
FROM per_share AS p
INNER JOIN eps_annual AS e ON e.fy = p.fy
INNER JOIN cash AS c ON c.fy = p.fy
ORDER BY p.fy

SQL to run

WITH
    per_share AS
    (
        SELECT
            toYear(ex_date) AS fy,
            round(sum(amount), 4) AS dividends_per_share,
            count() AS payments
        FROM
        (
            SELECT
                ex_dividend_date AS ex_date,
                max(toFloat64(cash_amount)) AS amount
            FROM global_markets.stocks_dividends
            WHERE ticker = 'JNJ'
              AND frequency = 4
              AND ex_dividend_date >= '2018-01-01'
              AND ex_dividend_date <  '2026-01-01'
            GROUP BY ex_dividend_date
        )
        GROUP BY fy
        HAVING payments = 4
    ),
    eps_annual AS
    (
        SELECT
            toYear(period_end - 7) AS fy,
            argMax(toFloat64(diluted_earnings_per_share), (filing_date, period_end)) AS diluted_eps
        FROM global_markets.stocks_income_statements
        WHERE has(tickers, 'JNJ')
          AND timeframe = 'annual'
          AND period_end >= '2018-01-01'
          AND period_end <  '2026-06-01'
        GROUP BY fy
    ),
    cash AS
    (
        SELECT
            toYear(period_end - 7) AS fy,
            argMax(toFloat64(dividends), (filing_date, period_end)) AS dividends_paid,
            argMax(toFloat64(net_cash_from_operating_activities), (filing_date, period_end)) AS operating_cash
        FROM global_markets.stocks_cash_flow_statements
        WHERE has(tickers, 'JNJ')
          AND timeframe = 'annual'
          AND period_end >= '2018-01-01'
          AND period_end <  '2026-06-01'
        GROUP BY fy
    )
SELECT
    toString(p.fy) AS year,
    p.dividends_per_share AS dividends_per_share,
    round(e.diluted_eps, 2) AS diluted_eps,
    round(p.dividends_per_share / e.diluted_eps * 100, 1) AS eps_payout_pct,
    round(abs(c.dividends_paid) / c.operating_cash * 100, 1) AS cash_payout_pct
FROM per_share AS p
INNER JOIN eps_annual AS e ON e.fy = p.fy
INNER JOIN cash AS c ON c.fy = p.fy
ORDER BY p.fy

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