STRASMORE/EXPLORE 2,500 QUERIES

dividendos

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 2026-09-23, from nke-stock-price-in-euros.

as of series 43×4read in context →
dividendos — 43 rows by 4 columns, computed from US exchange, SIP and OPRA data.
datedividendo_usdacumulado_en_dolares_pctacumulado_en_euros_pct
2016-01-040.3200
2016-04-040.16-50-52
2016-07-050.16-50-50.7
2016-10-030.16-50-50.4
2017-01-030.18-43.8-42.1
2017-04-030.18-43.8-42.4
2017-07-050.18-43.8-46.4
2017-10-020.18-43.8-47.3
2018-01-020.2-37.5-43.4
2018-04-020.2-37.5-43.7
2018-07-050.2-37.5-40.7
2018-10-010.2-37.5-39.5
2019-01-020.22-31.2-33
2019-04-010.22-31.2-31.7
2019-07-010.22-31.2-31.5
2019-09-300.22-31.2-30.1
2020-01-020.245-23.4-22.6
2020-04-010.245-23.4-20.8
2020-07-010.245-23.4-24.8
2020-10-010.245-23.4-26.5
2020-12-290.275-14.1-20.1
2021-04-010.275-14.1-18.6
2021-07-010.275-14.1-17.3
2021-10-010.275-14.1-15.4
2021-12-280.305-4.7-3.6
2022-04-010.305-4.71.3
2022-07-010.305-4.77.8
2022-10-030.305-4.711.6
2022-12-280.346.215.7
2023-04-030.346.211.6
2023-07-050.346.210.6
2023-10-020.346.215.8
2024-01-020.3715.622.2
2024-04-010.3715.624.1
2024-07-010.3715.622.8
2024-10-010.3715.622.2
2025-01-020.42539
2025-04-010.42528.4
2025-07-010.42523.4
2025-10-010.42523.8
2026-01-020.4128.125.7
2026-04-010.4128.126.2
2026-07-010.4128.129.2
Rows × columns
43 × 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 dividendos, derived from the stored result.
ColumnTypeRangeNotes
date date 2016-01-04 to 2026-07-01
dividendo_usd number 0.16 to 0.41 US dollars
acumulado_en_dolares_pct number -50 to 28.1 percent
acumulado_en_euros_pct number -52 to 39 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 pagos AS
(
    SELECT
        pay_date                    AS d,
        toFloat64(max(cash_amount)) AS usd
    FROM global_markets.stocks_dividends
    WHERE ticker = 'NKE'
      AND pay_date >= '2016-01-01'
      AND pay_date <= today()
      AND cash_amount > 0
    GROUP BY pay_date
),
euro_mes AS
(
    SELECT
        toStartOfMonth(date)  AS m,
        avg(toFloat64(close)) AS fx
    FROM global_markets.stocks_daily_aggs
    WHERE ticker = 'FXE'
      AND date >= '2015-12-01'
    GROUP BY m
),
convertido AS
(
    SELECT
        p.d          AS d,
        p.usd        AS usd,
        p.usd / e.fx AS eur
    FROM pagos AS p
    INNER JOIN euro_mes AS e ON e.m = toStartOfMonth(p.d)
),
base AS
(
    SELECT
        argMin(usd, d) AS usd0,
        argMin(eur, d) AS eur0
    FROM convertido
)
SELECT
    toString(c.d)                          AS date,
    round(c.usd, 4)                        AS dividendo_usd,
    round((c.usd / b.usd0 - 1) * 100, 1)   AS acumulado_en_dolares_pct,
    round((c.eur / b.eur0 - 1) * 100, 1)   AS acumulado_en_euros_pct
FROM convertido AS c
CROSS JOIN base AS b
ORDER BY c.d
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