The exact quarters behind each buyback 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 2026-10-04, from Dividends vs Buybacks: Shareholder Yield.
| ticker | prior_quarter_end | recent_quarter_end | shares_prior_millions | shares_recent_millions |
|---|---|---|---|---|
| AAPL | 2024-12-28 | 2025-12-27 | 15151 | 14810 |
| CSCO | 2025-01-25 | 2026-01-24 | 4005 | 3984 |
| CVX | 2024-12-31 | 2025-12-31 | 1817 | 1856 |
| HD | 2025-08-03 | 2026-08-02 | 994 | 996 |
| JNJ | 2024-12-29 | 2025-12-28 | 2429 | 2429 |
| KO | 2025-06-27 | 2026-07-03 | 4315 | 4313 |
| MSFT | 2024-12-31 | 2025-12-31 | 7468 | 7460 |
| PEP | 2025-06-14 | 2026-06-13 | 1373 | 1369 |
- Rows × columns
- 8 × 5
- Period covered
- to
- Computed
- Completeness
- No missing values
- Source
- US exchange, SIP and OPRA market data
- Licence
- Strasmore terms · free, no signup
What each column holds
| Column | Type | Range | Notes |
|---|---|---|---|
ticker |
text | 8 distinct values (AAPL, CSCO, CVX…) | |
prior_quarter_end |
date | 2024-12-28 to 2025-08-03 | |
recent_quarter_end |
date | 2025-12-27 to 2026-08-02 | |
shares_prior_millions |
number | 994 to 15,151 | count |
shares_recent_millions |
number | 996 to 14,810 | count |
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
quarters AS
(
SELECT
arrayJoin(tickers) AS ticker,
period_end,
argMax(toFloat64(diluted_shares_outstanding), filing_date) AS shares
FROM global_markets.stocks_income_statements
WHERE timeframe = 'quarterly'
AND diluted_shares_outstanding > 0
AND period_end > today() - 800
AND hasAny(tickers, ['AAPL', 'MSFT', 'KO', 'PEP', 'CVX', 'CSCO', 'HD', 'JNJ'])
GROUP BY ticker, period_end
HAVING ticker IN ('AAPL', 'MSFT', 'KO', 'PEP', 'CVX', 'CSCO', 'HD', 'JNJ')
),
latest AS
(
SELECT
ticker,
max(period_end) AS recent_period,
argMax(shares, period_end) AS shares_recent
FROM quarters
GROUP BY ticker
HAVING recent_period > today() - 400
),
share_pairs AS
(
SELECT
r.ticker AS ticker,
any(r.recent_period) AS recent_period,
any(r.shares_recent) AS shares_recent,
argMin(q.period_end, abs(dateDiff('day', q.period_end, r.recent_period - 365))) AS prior_period,
argMin(q.shares, abs(dateDiff('day', q.period_end, r.recent_period - 365))) AS shares_prior
FROM latest AS r
INNER JOIN quarters AS q ON q.ticker = r.ticker
WHERE q.period_end BETWEEN r.recent_period - 400 AND r.recent_period - 330
GROUP BY r.ticker
)
SELECT
ticker,
toString(prior_period) AS prior_quarter_end,
toString(recent_period) AS recent_quarter_end,
round(shares_prior / 1e6, 0) AS shares_prior_millions,
round(shares_recent / 1e6, 0) AS shares_recent_millions
FROM share_pairs
ORDER BY ticker
Work with this data in your AI assistant
Opens ready to query, with this page's data. Free, no account.