STRASMORE/EXPLORE 2,401 QUERIES

sweep_day_peak

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 2026-09-19, from what-is-a-liquidity-sweep.

as of ranking 3×2read in context →
sweep_day_peak — 3 rows by 2 columns, computed from US exchange, SIP and OPRA data.
labelvolume_millions
Fifteen minutes that printed the session high2.48
Median fifteen-minute slice of the session4.63
Busiest fifteen-minute slice of the session12.88
Rows × columns
3 × 2
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 sweep_day_peak, derived from the stored result.
ColumnTypeRangeNotes
label text 3 distinct values
volume_millions number 2.48 to 12.88 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.

the exact SQL behind every number
SELECT
    tupleElement(entry, 1) AS label,
    tupleElement(entry, 2) AS volume_millions
FROM
(
    SELECT
        arrayJoin([
            ('Fifteen minutes that printed the session high', peak_slice),
            ('Median fifteen-minute slice of the session',    median_slice),
            ('Busiest fifteen-minute slice of the session',   busiest_slice)
        ]) AS entry
    FROM
    (
        SELECT
            round(argMax(volume_mm, (slice_high, slice_start)), 2) AS peak_slice,
            round(quantileExact(0.5)(volume_mm), 2)                AS median_slice,
            round(max(volume_mm), 2)                               AS busiest_slice
        FROM
        (
            SELECT
                toStartOfFifteenMinutes(toTimeZone(window_start, 'America/New_York')) AS slice_start,
                toFloat64(max(high))                                                  AS slice_high,
                toFloat64(sum(volume)) / 1e6                                          AS volume_mm
            FROM global_markets.delayed_stocks_minute_aggs
            WHERE ticker = 'SPY'
              AND window_start >= '2025-01-01'
              AND window_start <  '2026-01-02'
              AND toDate(toTimeZone(window_start, 'America/New_York')) =
              (
                  SELECT toDate(date)
                  FROM
                  (
                      SELECT
                          date,
                          hi,
                          cl,
                          lagInFrame(hi) OVER (ORDER BY date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prior_hi
                      FROM
                      (
                          SELECT
                              date,
                              argMax(high,  _ingest_time) AS hi,
                              argMax(close, _ingest_time) AS cl
                          FROM global_markets.stocks_daily_aggs
                          WHERE ticker = 'SPY'
                            AND date >= '2024-12-31'
                            AND date <  '2026-01-01'
                          GROUP BY date
                      )
                  )
                  WHERE date >= '2025-01-01'
                    AND prior_hi > 0
                    AND hi > prior_hi
                    AND cl < prior_hi
                  ORDER BY (toFloat64(hi) - toFloat64(prior_hi)) / toFloat64(prior_hi) DESC, date DESC
                  LIMIT 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 slice_start
        )
    )
)

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