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MU, the biggest-volume session of June 2026: time-adjusted vs. naive RVOL, plus the full-day figure

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 2026-08-22, from What Is RVOL (Relative Volume)? How to Read It.

as of scalar 1×8read in context →
session date
2026-06-25
vol by 1030 m
32.8
avg vol by 1030 m
17.3
rvol 1030 adjusted
1.9
rvol 1030 naive
0.64
session volume m
77.2
trailing adv m
51
rvol full day
1.5
Rows × columns
1 × 8
Period covered
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 MU, the biggest-volume session of June 2026: time-adjusted vs. naive RVOL, plus the full-day figure, derived from the stored result.
ColumnTypeRangeNotes
session_date date 2026-06-25
vol_by_1030_m number every row is 32.8
avg_vol_by_1030_m number every row is 17.3
rvol_1030_adjusted number every row is 1.9
rvol_1030_naive number every row is 0.64
session_volume_m number every row is 77.2 count
trailing_adv_m number every row is 51
rvol_full_day number every row is 1.5

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
WITH mu_daily AS (
    SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS et_date,
           sum(toFloat64(volume)) AS day_volume,
           sumIf(toFloat64(volume), formatDateTime(toTimeZone(window_start, 'America/New_York'), '%H:%i') < '10:30') AS vol_by_1030
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'MU'
      AND window_start >= toDateTime('2026-04-15 00:00:00', 'America/New_York')
      AND window_start < toDateTime('2026-07-01 00:00:00', 'America/New_York')
    GROUP BY et_date
    HAVING day_volume > 1000000
),
biggest AS (
    SELECT et_date, day_volume, vol_by_1030
    FROM mu_daily
    WHERE et_date >= toDate('2026-06-01') AND et_date <= toDate('2026-06-30')
    ORDER BY day_volume DESC
    LIMIT 1
),
trailing AS (
    SELECT sum(day_volume) / 20 AS adv, sum(vol_by_1030) / 20 AS avg_by_1030
    FROM (
        SELECT day_volume, vol_by_1030
        FROM mu_daily
        WHERE et_date < (SELECT et_date FROM biggest)
        ORDER BY et_date DESC
        LIMIT 20
    )
)
SELECT formatDateTime((SELECT et_date FROM biggest), '%Y-%m-%d') AS session_date,
       round((SELECT vol_by_1030 FROM biggest) / 1e6, 1) AS vol_by_1030_m,
       round((SELECT avg_by_1030 FROM trailing) / 1e6, 1) AS avg_vol_by_1030_m,
       round((SELECT vol_by_1030 FROM biggest) / (SELECT avg_by_1030 FROM trailing), 1) AS rvol_1030_adjusted,
       round((SELECT vol_by_1030 FROM biggest) / (SELECT adv FROM trailing), 2) AS rvol_1030_naive,
       round((SELECT day_volume FROM biggest) / 1e6, 1) AS session_volume_m,
       round((SELECT adv FROM trailing) / 1e6, 1) AS trailing_adv_m,
       round((SELECT day_volume FROM biggest) / (SELECT adv FROM trailing), 1) AS rvol_full_day

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