session_clock
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 2026-10-09, from day-trading-strategies-explained.
| et_time | spy_pct | aapl_pct | ko_pct |
|---|---|---|---|
| 09:30 | 11.4 | 16.9 | 15.3 |
| 10:00 | 8.4 | 9.6 | 8.9 |
| 10:30 | 6.9 | 7.7 | 8 |
| 11:00 | 6.7 | 7 | 7 |
| 11:30 | 5.9 | 6.5 | 5.7 |
| 12:00 | 5.3 | 5.7 | 5 |
| 12:30 | 4.5 | 5.1 | 4.5 |
| 13:00 | 4.9 | 4.9 | 4.2 |
| 13:30 | 4.2 | 4.7 | 4.2 |
| 14:00 | 5.5 | 4.9 | 5 |
| 14:30 | 6.2 | 5.3 | 5.4 |
| 15:00 | 7.6 | 6.3 | 6.4 |
| 15:30 | 22.5 | 15.5 | 20.5 |
- Rows × columns
- 13 × 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 |
|---|---|---|---|
et_time |
text | 13 distinct values (09:30, 10:00, 10:30…) | |
spy_pct |
number | 4.2 to 22.5 | percent |
aapl_pct |
number | 4.7 to 16.9 | percent |
ko_pct |
number | 4.2 to 20.5 | 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 bars AS (
SELECT
ticker,
formatDateTime(
toStartOfInterval(toTimeZone(window_start, 'America/New_York'), INTERVAL 30 MINUTE),
'%H:%i'
) AS et_time,
toFloat64(sum(volume)) AS vol
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('SPY', 'AAPL', 'KO')
AND window_start >= today() - 120
AND window_start < today() - 1
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
+ toMinute(toTimeZone(window_start, 'America/New_York'))) >= 570
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
+ toMinute(toTimeZone(window_start, 'America/New_York'))) < 960
GROUP BY ticker, et_time
),
shares AS (
SELECT
ticker,
et_time,
100 * vol / sum(vol) OVER (PARTITION BY ticker) AS pct
FROM bars
)
SELECT
et_time,
round(sumIf(pct, ticker = 'SPY'), 1) AS spy_pct,
round(sumIf(pct, ticker = 'AAPL'), 1) AS aapl_pct,
round(sumIf(pct, ticker = 'KO'), 1) AS ko_pct
FROM shares
GROUP BY et_time
ORDER BY et_time
Use dis data for your AI assistant
E go open ready to query, with dis page data. Free, no account.