STRASMORE/EXPLORE 3,293 QUERIES

dst_shift

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.

as of series 10×5read in context →
dst_shift — 10 rows by 5 columns, computed from US exchange, SIP and OPRA data.
monthmonth_labelbusiest_30min_watbusiest_30min_etlagos_minus_ny_hours
2025-12Dec 202522:0016:006
2026-01Jan 202621:3015:306
2026-02Feb 202621:3015:306
2026-03Mar 202620:3015:305
2026-04Apr 202620:3015:305
2026-05May 202620:3015:305
2026-06Jun 202620:3015:305
2026-07Jul 202620:3015:305
2026-08Aug 202620:3015:305
2026-09Sep 202620:3015:305
Rows × columns
10 × 5
Computed
Completeness
No missing values
Source
US exchange, SIP and OPRA market data
Licence
Strasmore terms · free, no signup
Formats
JSON · CSV · the SQL below

What each column holds

Column definitions for dst_shift, derived from the stored result.
ColumnTypeRangeNotes
month text 10 distinct values (2025-12, 2026-01, 2026-02…)
month_label text 10 distinct values (Apr 2026, Aug 2026, Dec 2025…)
busiest_30min_wat text 3 distinct values (20:30, 21:30, 22:00)
busiest_30min_et text 2 distinct values (15:30, 16:00)
lagos_minus_ny_hours number 5 to 6

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 buckets AS
(
    SELECT
        toStartOfInterval(window_start, INTERVAL 30 MINUTE) AS bucket,
        sum(volume)                                         AS bucket_volume
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= '2025-12-01 00:00:00'
      AND window_start <  '2026-10-01 00:00:00'
    GROUP BY bucket
),
monthly AS
(
    SELECT
        toStartOfMonth(bucket)        AS month_start,
        argMax(bucket, bucket_volume) AS top_bucket,
        max(bucket_volume)            AS top_volume
    FROM buckets
    GROUP BY month_start
)
SELECT
    formatDateTime(month_start, '%Y-%m')                                AS month,
    formatDateTime(month_start, '%b %Y')                                AS month_label,
    formatDateTime(toTimeZone(top_bucket, 'Africa/Lagos'), '%H:%i')     AS busiest_30min_wat,
    formatDateTime(toTimeZone(top_bucket, 'America/New_York'), '%H:%i') AS busiest_30min_et,
    modulo(toHour(toTimeZone(top_bucket, 'Africa/Lagos'))
         - toHour(toTimeZone(top_bucket, 'America/New_York')) + 24, 24) AS lagos_minus_ny_hours
FROM monthly
ORDER BY month_start
⌘/Ctrl + Enter

Work with this data in your AI assistant

Opens ready to query, with this page's data. Free, no account.