STRASMORE/EXPLORE 3,127 QUERIES

Medline (MDLN): the 20 sessions before its 180-day mark vs. every session from it, regular-hours volume and daily range

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 2026-07-26, from Stock Float vs. Shares Outstanding Explained.

as of series 2×8read in context →
Medline (MDLN): the 20 sessions before its 180-day mark vs. every session from it, regular-hours volume and daily range — 2 rows by 8 columns, computed from US exchange, SIP and OPRA data.
windowlisted_onshares_offered_msessionsfirst_sessionlast_sessionmedian_daily_volume_mmedian_daily_range_pct
1. 20 sessions beforeDec 17, 2025248.420May 15Jun 128.614.53
2. from the 180-day markDec 17, 2025248.418Jun 15Jul 106.424.14
Rows × columns
2 × 8
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 Medline (MDLN): the 20 sessions before its 180-day mark vs. every session from it, regular-hours volume and daily range, derived from the stored result.
ColumnTypeRangeNotes
window text 2 distinct values
listed_on text 1 distinct value (Dec 17, 2025)
shares_offered_m number every row is 248.4 count
sessions number 18 to 20
first_session text 2 distinct values (Jun 15, May 15)
last_session text 2 distinct values (Jul 10, Jun 12)
median_daily_volume_m number 6.42 to 8.61 count
median_daily_range_pct number 4.14 to 4.53 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 ipo AS (
    SELECT concat(formatDateTime(listing_date, '%b'), ' ', toString(toDayOfMonth(listing_date)), ', ', toString(toYear(listing_date))) AS listed_on,
           round(max_shares_offered / 1e6, 1) AS shares_offered_m
    FROM global_markets.stocks_ipos
    WHERE ticker = 'MDLN'
      AND ipo_status = 'history'
      AND listing_date >= '2025-12-01'
      AND listing_date <= '2025-12-31'
    LIMIT 1
),
daily AS (
    SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS session,
           toFloat64(max(high)) AS hi,
           toFloat64(min(low)) AS lo,
           sum(toFloat64(volume)) AS shares_traded
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'MDLN'
      AND window_start >= toDateTime('2026-05-15 09:30:00', 'America/New_York')
      AND window_start < toDateTime('2026-07-11 00:00:00', 'America/New_York')
      AND toHour(toTimeZone(window_start, 'America/New_York')) >= 9
      AND toHour(toTimeZone(window_start, 'America/New_York')) < 16
      AND NOT (toHour(toTimeZone(window_start, 'America/New_York')) = 9
               AND toMinute(toTimeZone(window_start, 'America/New_York')) < 30)
    GROUP BY session
    HAVING lo > 0
)
SELECT if(session < toDate('2026-06-15'), '1. 20 sessions before', '2. from the 180-day mark') AS window,
       any(listed_on) AS listed_on,
       any(shares_offered_m) AS shares_offered_m,
       count() AS sessions,
       concat(formatDateTime(min(session), '%b'), ' ', toString(toDayOfMonth(min(session)))) AS first_session,
       concat(formatDateTime(max(session), '%b'), ' ', toString(toDayOfMonth(max(session)))) AS last_session,
       round(quantileDeterministic(0.5)(shares_traded, cityHash64(session)) / 1e6, 2) AS median_daily_volume_m,
       round(quantileDeterministic(0.5)(100 * (hi - lo) / lo, cityHash64(session)), 2) AS median_daily_range_pct
FROM daily
CROSS JOIN ipo
GROUP BY window
ORDER BY window
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