Session coverage behind the long-run panels
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 2026-09-26, from The 10:00 AM Rule in Stocks, Tested.
| symbol | sample_size | avg_bar_count | min_bar_count |
|---|---|---|---|
| KO | 752 | 388.1 | 211 |
| MSFT | 752 | 388.1 | 211 |
| SPY | 752 | 388.1 | 211 |
| AAPL | 752 | 388.1 | 211 |
| QQQ | 752 | 388.1 | 211 |
| NVDA | 752 | 388.1 | 211 |
- 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 |
|---|---|---|---|
symbol |
text | 6 distinct values (AAPL, KO, MSFT…) | |
sample_size |
number | every row is 752 | |
avg_bar_count |
number | every row is 388.1 | count |
min_bar_count |
number | every row is 211 | 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 bars AS (
SELECT
ticker,
toDate(toTimeZone(window_start, 'America/New_York')) AS trade_day,
toHour(toTimeZone(window_start, 'America/New_York')) * 60
+ toMinute(toTimeZone(window_start, 'America/New_York')) AS et_minute
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('SPY', 'QQQ', 'AAPL', 'MSFT', 'NVDA', 'KO')
AND window_start >= '2023-01-01'
AND window_start < '2026-01-01'
),
per_day AS (
SELECT
ticker,
trade_day,
count() AS bar_count
FROM bars
WHERE et_minute >= 570 AND et_minute < 960
GROUP BY ticker, trade_day
)
SELECT
ticker AS symbol,
count() AS sample_size,
round(avg(bar_count), 1) AS avg_bar_count,
min(bar_count) AS min_bar_count
FROM per_day
GROUP BY ticker
ORDER BY sample_size DESC
Work with this data in your AI assistant
Opens ready to query, with this page's data. Free, no account.