mkondo_wa_siku
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 2026-11-07, from us-stock-market-hours-east-africa-time.
| saa_eat | volume_mln | share_pct |
|---|---|---|
| 12:00 | 0.05 | 0.12 |
| 13:00 | 0.06 | 0.16 |
| 14:00 | 0.19 | 0.48 |
| 15:00 | 0.39 | 0.96 |
| 16:00 | 4.01 | 9.87 |
| 17:00 | 5.14 | 12.67 |
| 18:00 | 4.52 | 11.13 |
| 19:00 | 3.39 | 8.34 |
| 20:00 | 3.12 | 7.69 |
| 21:00 | 3.88 | 9.56 |
| 22:00 | 9.8 | 24.14 |
| 23:00 | 5.4 | 13.31 |
| 00:00 | 0.39 | 0.95 |
| 01:00 | 0.11 | 0.27 |
| 02:00 | 0.05 | 0.11 |
| 11:00 | 0.1 | 0.24 |
- Rows × columns
- 16 × 3
- 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 |
|---|---|---|---|
saa_eat |
text | 16 distinct values (00:00, 01:00, 02:00…) | |
volume_mln |
number | 0.05 to 9.8 | count |
share_pct |
number | 0.11 to 24.14 | 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 baa AS
(
SELECT
toHour(toTimeZone(window_start, 'Africa/Nairobi')) AS saa,
toDate(toTimeZone(window_start, 'America/New_York')) AS siku,
volume
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY'
AND window_start >= toDateTime(today() - 100)
AND window_start < toDateTime(today() - 2)
AND volume > 0
)
SELECT
concat(leftPad(toString(h.saa), 2, '0'), ':00') AS saa_eat,
round(toFloat64(h.ujazo) / h.vikao / 1000000, 2) AS volume_mln,
round(100 * toFloat64(h.ujazo) / toFloat64(t.jumla), 2) AS share_pct
FROM
(
SELECT
saa,
sum(volume) AS ujazo,
countDistinct(siku) AS vikao
FROM baa
GROUP BY saa
) AS h
CROSS JOIN
(
SELECT sum(volume) AS jumla FROM baa
) AS t
ORDER BY if(h.saa >= 12, h.saa, h.saa + 24)
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