STRASMORE/EXPLORE 3,256 QUERIES

Walgreens Boots Alliance (WBA): month-end price, quarterly dividend, and yield, 2022-07 to 2024-06

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 Highest Dividend Yield US Stocks in 2026.

as of series 24×5read in context →
Walgreens Boots Alliance (WBA): month-end price, quarterly dividend, and yield, 2022-07 to 2024-06 — 24 rows by 5 columns, computed from US exchange, SIP and OPRA data.
monthmonth_labelpricequarterly_dividend_usddividend_yield_pct
2022-07July 202239.620.484.82
2022-08August 202235.050.485.48
2022-09September 202231.410.486.11
2022-10October 202236.530.485.26
2022-11November 202241.510.484.63
2022-12December 202237.350.485.14
2023-01January 202336.860.485.21
2023-02February 202335.510.485.41
2023-03March 202334.580.485.55
2023-04April 202335.250.485.45
2023-05May 202330.380.486.32
2023-06June 202328.490.486.74
2023-07July 202329.980.486.4
2023-08August 202325.30.487.59
2023-09September 202322.250.488.63
2023-10October 202321.080.489.11
2023-11November 202319.940.489.63
2023-12December 202326.130.487.35
2024-01January 202422.560.488.51
2024-02February 202421.240.254.71
2024-03March 202421.680.254.61
2024-04April 202417.730.255.64
2024-05May 202416.240.256.16
2024-06June 202412.10.258.27
Rows × columns
24 × 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 Walgreens Boots Alliance (WBA): month-end price, quarterly dividend, and yield, 2022-07 to 2024-06, derived from the stored result.
ColumnTypeRangeNotes
month text 24 distinct values (2022-07, 2022-08, 2022-09…)
month_label text 24 distinct values (April 2023, April 2024, August 2022…)
price number 12.1 to 41.51 US dollars
quarterly_dividend_usd number 0.25 to 0.48 US dollars
dividend_yield_pct number 4.61 to 9.63 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 = 'WBA'
      AND toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2022-07-01')
      AND toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2024-06-30')
      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 = 'WBA'
      AND distribution_type = 'recurring'
      AND frequency = 4
      AND cash_amount > 0
      AND ex_dividend_date >= toDate('2021-06-01')
)
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(toFloat64(argMax(dv.cash_amount, dv.ex_dividend_date)) * 4
             / toFloat64(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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