wat_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 2026-10-16, from us-market-volume-by-hour-lagos-time.
| wat_time | et_time | share_of_volume_pct | avg_volume_m |
|---|---|---|---|
| 09:00 | 04:00 | 0.48 | 1.1 |
| 10:00 | 05:00 | 0.15 | 0.3 |
| 11:00 | 06:00 | 0.17 | 0.4 |
| 12:00 | 07:00 | 0.65 | 1.4 |
| 13:00 | 08:00 | 0.97 | 2.2 |
| 14:00 | 09:00 | 15.41 | 34.4 |
| 15:00 | 10:00 | 16 | 35.7 |
| 16:00 | 11:00 | 12.04 | 26.9 |
| 17:00 | 12:00 | 9.92 | 22.2 |
| 18:00 | 13:00 | 8.65 | 19.3 |
| 19:00 | 14:00 | 9.22 | 20.6 |
| 20:00 | 15:00 | 19.34 | 43.2 |
| 21:00 | 16:00 | 5.64 | 12.6 |
| 22:00 | 17:00 | 0.86 | 1.9 |
| 23:00 | 18:00 | 0.3 | 0.7 |
| 00:00 | 19:00 | 0.19 | 0.4 |
- Rows × columns
- 16 × 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 |
|---|---|---|---|
wat_time |
text | 16 distinct values (00:00, 09:00, 10:00…) | |
et_time |
text | 16 distinct values (04:00, 05:00, 06:00…) | |
share_of_volume_pct |
number | 0.15 to 19.34 | percent |
avg_volume_m |
number | 0.3 to 43.2 | 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
toDate(toTimeZone(window_start, 'America/New_York')) AS session_date,
toHour(toTimeZone(window_start, 'America/New_York')) AS et_hour,
toStartOfHour(window_start) AS bucket_ts,
volume
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('SPY', 'AAPL', 'MSFT', 'NVDA')
AND window_start >= '2026-06-01 00:00:00'
AND window_start < '2026-10-01 00:00:00'
),
tape_day AS
(
SELECT sum(volume) AS full_day_volume FROM bars
)
SELECT
formatDateTime(toTimeZone(min(bucket_ts), 'Africa/Lagos'), '%H:%i') AS wat_time,
formatDateTime(toTimeZone(min(bucket_ts), 'America/New_York'), '%H:%i') AS et_time,
round(sum(volume) / (SELECT full_day_volume FROM tape_day) * 100, 2) AS share_of_volume_pct,
round(sum(volume) / countDistinct(session_date) / 1000000, 1) AS avg_volume_m
FROM bars
GROUP BY et_hour
ORDER BY et_hour
Use dis data for your AI assistant
E go open ready to query, with dis page data. Free, no account.