STRASMORE/EXPLORE 3,256 QUERIES

Conagra (CAG): price, quarterly dividend, and yield, month-end 2023-07 to 2026-06

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 2026-10-04, from What Is Dividend Yield? What's Normal in 2026.

as of series 36×5read in context →
Conagra (CAG): price, quarterly dividend, and yield, month-end 2023-07 to 2026-06 — 36 rows by 5 columns, computed from US exchange, SIP and OPRA data.
monthmonth_labelpricequarterly_dividend_usddividend_yield_pct
2023-07July 202332.820.354.27
2023-08August 202329.880.354.69
2023-09September 202327.430.355.1
2023-10October 202327.350.355.12
2023-11November 202328.30.354.95
2023-12December 202328.670.354.88
2024-01January 202429.140.354.8
2024-02February 202428.080.354.99
2024-03March 202429.640.354.72
2024-04April 202430.780.354.55
2024-05May 202429.870.354.69
2024-06June 202428.430.354.92
2024-07July 202430.310.354.62
2024-08August 202431.190.354.49
2024-09September 202432.520.354.31
2024-10October 202428.950.354.84
2024-11November 202427.550.355.08
2024-12December 202427.760.355.04
2025-01January 202525.880.355.41
2025-02February 202525.540.355.48
2025-03March 202526.680.355.25
2025-04April 202524.690.355.67
2025-05May 202522.880.356.12
2025-06June 202520.460.356.84
2025-07July 202518.260.357.67
2025-08August 202519.130.357.32
2025-09September 202518.280.357.66
2025-10October 202517.190.358.15
2025-11November 202517.850.357.84
2025-12December 202517.320.358.09
2026-01January 202618.510.357.56
2026-02February 202619.250.357.27
2026-03March 202615.710.358.91
2026-04April 202614.350.359.76
2026-05May 202613.280.3510.54
2026-06June 202613.450.3510.41
Rows × columns
36 × 5
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 Conagra (CAG): price, quarterly dividend, and yield, month-end 2023-07 to 2026-06, derived from the stored result.
ColumnTypeRangeNotes
month text 36 distinct values (2023-07, 2023-08, 2023-09…)
month_label text 36 distinct values (April 2024, April 2025, April 2026…)
price number 13.28 to 32.82 US dollars
quarterly_dividend_usd number every row is 0.35 US dollars
dividend_yield_pct number 4.27 to 10.54 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 px AS (
    SELECT toStartOfMonth(toDate(toTimeZone(window_start, 'America/New_York'))) AS month_start,
           argMax(close, window_start) AS price,
           max(toDate(toTimeZone(window_start, 'America/New_York'))) AS last_day
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'CAG'
      AND toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2023-07-01')
      AND toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-06-30')
      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
           + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
    GROUP BY month_start
),
dv AS (
    SELECT ex_dividend_date, cash_amount
    FROM global_markets.stocks_dividends
    WHERE ticker = 'CAG'
      AND distribution_type = 'recurring'
      AND frequency = 4
      AND cash_amount > 0
      AND ex_dividend_date >= toDate('2022-06-01')
)
SELECT formatDateTime(px.month_start, '%Y-%m') AS month,
       formatDateTimeInJodaSyntax(px.month_start, 'MMMM yyyy') AS month_label,
       round(any(px.price), 2) AS price,
       round(argMax(dv.cash_amount, dv.ex_dividend_date), 2) AS quarterly_dividend_usd,
       round(argMax(dv.cash_amount, dv.ex_dividend_date) * 4 / any(px.price) * 100, 2) AS dividend_yield_pct
FROM px, dv
WHERE dv.ex_dividend_date <= px.last_day
GROUP BY px.month_start
ORDER BY px.month_start
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