STRASMORE/EXPLORE 2,707 QUERIES

ttm_yield

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 2026-09-27, from aapl-dividend-for-pakistani-investors.

as of series 14×4read in context →
ttm_yield — 14 rows by 4 columns, computed from US exchange, SIP and OPRA data.
monthmonth_labelavg_close_usdttm_yield_pct
2025-08-01Aug 2025230.330.46
2025-09-01Sep 2025242.490.44
2025-10-01Oct 2025258.30.41
2025-11-01Nov 2025271.660.39
2025-12-01Dec 2025276.310.38
2026-01-01Jan 2026257.650.41
2026-02-01Feb 2026269.180.39
2026-03-01Mar 2026254.910.42
2026-04-01Apr 2026264.690.4
2026-05-01May 2026297.540.36
2026-06-01Jun 2026296.420.36
2026-07-01Jul 2026322.290.33
2026-08-01Aug 2026310.190.34
2026-09-01Sep 2026330.630.32
Rows × columns
14 × 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 ttm_yield, derived from the stored result.
ColumnTypeRangeNotes
month date 2025-08-01 to 2026-09-01
month_label text 14 distinct values (Apr 2026, Aug 2025, Aug 2026…)
avg_close_usd number 230.33 to 330.63 US dollars
ttm_yield_pct number 0.32 to 0.46 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.

SELECT
    toString(toStartOfMonth(d.date))                              AS month,
    formatDateTime(toStartOfMonth(d.date), '%b %Y')               AS month_label,
    round(avg(toFloat64(d.close)), 2)                             AS avg_close_usd,
    round(100 * any(t.ttm_dividend) / avg(toFloat64(d.close)), 2) AS ttm_yield_pct
FROM global_markets.stocks_daily_aggs AS d
CROSS JOIN
(
    SELECT sum(amt) AS ttm_dividend
    FROM
    (
        SELECT toFloat64(max(cash_amount)) AS amt
        FROM global_markets.stocks_dividends
        WHERE ticker = 'AAPL'
          AND ex_dividend_date > today() - 370
          AND ex_dividend_date <= today()
        GROUP BY ex_dividend_date
    )
) AS t
WHERE d.ticker = 'AAPL'
  AND d.date >= today() - 400
GROUP BY toStartOfMonth(d.date)
ORDER BY toStartOfMonth(d.date)
⌘/Ctrl + Enter

Work with this data in your AI assistant

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