STRASMORE/EXPLORE 2,500 QUERIES

gawio_aapl

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 how-to-buy-us-stocks-from-kenya.

as of series 31×4read in context →
gawio_aapl — 31 rows by 4 columns, computed from US exchange, SIP and OPRA data.
ex_datekipindigawio_ghafi_usdgawio_baada_ya_kodi_usd
2019-02-08Feb 20190.730.511
2019-05-10May 20190.770.539
2019-08-09Aug 20190.770.539
2019-11-07Nov 20190.770.539
2020-02-07Feb 20200.770.539
2020-05-08May 20200.820.574
2020-08-07Aug 20200.820.574
2020-11-06Nov 20200.2050.1435
2021-02-05Feb 20210.2050.1435
2021-05-07May 20210.220.154
2021-08-06Aug 20210.220.154
2021-11-05Nov 20210.220.154
2022-02-04Feb 20220.220.154
2022-05-06May 20220.230.161
2022-08-05Aug 20220.230.161
2022-11-04Nov 20220.230.161
2023-02-10Feb 20230.230.161
2023-05-12May 20230.240.168
2023-08-11Aug 20230.240.168
2023-11-10Nov 20230.240.168
2024-02-09Feb 20240.240.168
2024-05-10May 20240.250.175
2024-08-12Aug 20240.250.175
2024-11-08Nov 20240.250.175
2025-02-10Feb 20250.250.175
2025-05-12May 20250.260.182
2025-08-11Aug 20250.260.182
2025-11-10Nov 20250.260.182
2026-02-09Feb 20260.260.182
2026-05-11May 20260.270.189
2026-08-10Aug 20260.270.189
Rows × columns
31 × 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 gawio_aapl, derived from the stored result.
ColumnTypeRangeNotes
ex_date date 2019-02-08 to 2026-08-10
kipindi text 31 distinct values (Aug 2019, Aug 2020, Aug 2021…)
gawio_ghafi_usd number 0.205 to 0.82 US dollars
gawio_baada_ya_kodi_usd number 0.1435 to 0.574 US dollars

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.

SELECT
    toString(toDate(ex_dividend_date))                  AS ex_date,
    formatDateTime(toDate(ex_dividend_date), '%b %Y')   AS kipindi,
    round(toFloat64(any(cash_amount)), 4)               AS gawio_ghafi_usd,
    round(toFloat64(any(cash_amount)) * 0.70, 4)        AS gawio_baada_ya_kodi_usd
FROM global_markets.stocks_dividends
WHERE ticker = 'AAPL'
  AND ex_dividend_date >= '2019-01-01'
  AND ex_dividend_date <= today()
GROUP BY ex_dividend_date
ORDER BY ex_dividend_date
⌘/Ctrl + Enter

Work with this data in your AI assistant

Opens ready to query, with this page's data. Free, no account.

Claude ChatGPT Gemini Muse Your own agent