Share count, per share earnings and revenue across a split
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 2026-10-07, from The Real Disadvantages of a Stock Split.
| quarter_end_date | period_label | diluted_shares_bn | revenue_bn_usd | diluted_eps_usd |
|---|---|---|---|---|
| 2023-10-29 | Oct 2023 | 24.94 | 18.12 | 0.37 |
| 2024-01-28 | Jan 2024 | 24.94 | 22.1 | 0.49 |
| 2024-04-28 | Apr 2024 | 24.89 | 26.04 | 0.6 |
| 2024-07-28 | Jul 2024 | 24.85 | 30.04 | 0.67 |
| 2024-10-27 | Oct 2024 | 24.77 | 35.08 | 0.78 |
| 2025-01-26 | Jan 2025 | 24.8 | 39.33 | 0.9 |
| 2025-04-27 | Apr 2025 | 24.61 | 44.06 | 0.76 |
- Rows × columns
- 7 × 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 |
|---|---|---|---|
quarter_end_date |
date | 2023-10-29 to 2025-04-27 | |
period_label |
text | 7 distinct values (Apr 2024, Apr 2025, Jan 2024…) | |
diluted_shares_bn |
number | 24.61 to 24.94 | count |
revenue_bn_usd |
number | 18.12 to 44.06 | US dollars |
diluted_eps_usd |
number | 0.37 to 0.9 | 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(period_end) AS quarter_end_date,
formatDateTime(period_end, '%b %Y') AS period_label,
round(argMax(toFloat64(diluted_shares_outstanding), (filing_date, period_end)) / 1e9, 2) AS diluted_shares_bn,
round(argMax(toFloat64(revenue), (filing_date, period_end)) / 1e9, 2) AS revenue_bn_usd,
round(argMax(toFloat64(diluted_earnings_per_share), (filing_date, period_end)), 2) AS diluted_eps_usd
FROM global_markets.stocks_income_statements
WHERE has(tickers, 'NVDA')
AND timeframe = 'quarterly'
AND period_end BETWEEN '2023-10-01' AND '2025-06-30'
GROUP BY period_end, period_label
ORDER BY period_end
Work with this data in your AI assistant
Opens ready to query, with this page's data. Free, no account.