One company, two tickers: share class volume split, June 2026
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 2026-09-28, from Market Data Skills for AI Agents.
| ticker | company | avg_daily_volume_m | share_of_pair_pct |
|---|---|---|---|
| GOOGL | Alphabet | 30.15 | 59.6 |
| GOOG | Alphabet | 20.45 | 40.4 |
| FOXA | Fox | 7.49 | 78.8 |
| FOX | Fox | 2.02 | 21.2 |
| NWSA | News Corp | 4.26 | 74.5 |
| NWS | News Corp | 1.46 | 25.5 |
- Rows × columns
- 6 × 4
- 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 | 6 distinct values (FOX, FOXA, GOOG…) | |
company |
text | 3 distinct values (Alphabet, Fox, News Corp) | |
avg_daily_volume_m |
number | 1.46 to 30.15 | count |
share_of_pair_pct |
number | 21.2 to 78.8 | 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 daily AS (
SELECT ticker,
multiIf(ticker IN ('GOOGL', 'GOOG'), 'Alphabet',
ticker IN ('FOXA', 'FOX'), 'Fox',
'News Corp') AS company,
toDate(toTimeZone(window_start, 'America/New_York')) AS session_date,
sum(volume) AS day_volume
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('GOOGL', 'GOOG', 'FOXA', 'FOX', 'NWSA', 'NWS')
AND toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2026-06-01')
AND toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-06-30')
GROUP BY ticker, company, session_date
),
per_ticker AS (
SELECT ticker,
company,
round(avg(day_volume) / 1e6, 2) AS avg_daily_volume_m
FROM daily
GROUP BY ticker, company
),
pair_totals AS (
SELECT company, sum(avg_daily_volume_m) AS pair_volume_m
FROM per_ticker
GROUP BY company
)
SELECT p.ticker AS ticker,
p.company AS company,
p.avg_daily_volume_m AS avg_daily_volume_m,
round(100 * p.avg_daily_volume_m / t.pair_volume_m, 1) AS share_of_pair_pct
FROM per_ticker AS p
INNER JOIN pair_totals AS t ON p.company = t.company
ORDER BY p.company, share_of_pair_pct DESC
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