NBBO updates per session: four heavily traded names vs. two thin small caps
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 the NBBO? National Best Bid and Offer.
| ticker | sessions | avg_updates_per_session | avg_updates_per_session_m | multiple_of_quietest |
|---|---|---|---|---|
| SPY | 5 | 3392792 | 3.393 | 6173 |
| NVDA | 5 | 1811286 | 1.811 | 3296 |
| AAPL | 5 | 725886 | 0.726 | 1321 |
| KO | 5 | 354330 | 0.354 | 645 |
| SENEA | 5 | 4122 | 0.004 | 8 |
| NATH | 5 | 550 | 0.001 | 1 |
- Rows × columns
- 6 × 5
- 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 (AAPL, KO, NATH…) | |
sessions |
number | every row is 5 | |
avg_updates_per_session |
number | 550 to 3,392,792 | |
avg_updates_per_session_m |
number | 0.001 to 3.393 | |
multiple_of_quietest |
number | 1 to 6,173 |
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 ticker,
uniqExact(toDate(toTimeZone(sip_timestamp, 'America/New_York'))) AS sessions,
round(count() / uniqExact(toDate(toTimeZone(sip_timestamp, 'America/New_York')))) AS avg_updates_per_session,
round(count() / uniqExact(toDate(toTimeZone(sip_timestamp, 'America/New_York'))) / 1e6, 3) AS avg_updates_per_session_m,
round((count() / uniqExact(toDate(toTimeZone(sip_timestamp, 'America/New_York')))) / min(count() / uniqExact(toDate(toTimeZone(sip_timestamp, 'America/New_York')))) OVER (), 0) AS multiple_of_quietest
FROM global_markets.cache_stocks_quotes
WHERE ticker IN ('SPY', 'NVDA', 'AAPL', 'KO', 'SENEA', 'NATH')
AND sip_timestamp >= toDateTime(today() - 10)
AND sip_timestamp < toDateTime(today() - 3)
AND toDate(toTimeZone(sip_timestamp, 'America/New_York')) IN (
SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS session_date
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY'
AND window_start >= toDateTime(today() - 10)
AND window_start < toDateTime(today() - 3)
GROUP BY session_date
HAVING countIf((toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959) = 390
)
GROUP BY ticker
ORDER BY indexOf(['SPY', 'NVDA', 'AAPL', 'KO', 'SENEA', 'NATH'], ticker)
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