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Daily high-low range and dollar volume by shares-outstanding tier: US common stocks, regular-hours sessions, June 11 to July 10, 2026

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 table 5×5read in context →
Daily high-low range and dollar volume by shares-outstanding tier: US common stocks, regular-hours sessions, June 11 to July 10, 2026 — 5 rows by 5 columns, computed from US exchange, SIP and OPRA data.
share_count_tiercompaniesmedian_daily_range_pctp90_daily_range_pctmedian_daily_dollar_volume_m
under 20M shares10934.8213.280.49
20-50M shares9713.949.64.89
50-200M shares15323.648.1619.94
200M-1B shares8042.727.0775.22
over 1B shares2211.684.6599.47
Rows × columns
5 × 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 Daily high-low range and dollar volume by shares-outstanding tier: US common stocks, regular-hours sessions, June 11 to July 10, 2026, derived from the stored result.
ColumnTypeRangeNotes
share_count_tier text 5 distinct values
companies number 221 to 1,532
median_daily_range_pct number 1.68 to 4.82 percent
p90_daily_range_pct number 4.65 to 13.28 percent
median_daily_dollar_volume_m number 0.49 to 99.47 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
WITH latest AS (
    SELECT tk AS ticker,
           argMax(basic_shares_outstanding, (filing_date, period_end)) AS shares
    FROM global_markets.stocks_income_statements
    ARRAY JOIN tickers AS tk
    WHERE timeframe = 'quarterly'
      AND filing_date >= '2025-10-01'
      AND filing_date <= '2026-07-10'
      AND basic_shares_outstanding > 0
    GROUP BY tk
),
daily AS (
    SELECT ticker,
           toDate(toTimeZone(window_start, 'America/New_York')) AS session,
           toFloat64(max(high)) AS hi,
           toFloat64(min(low)) AS lo,
           toFloat64(argMax(close, window_start)) AS last_price,
           sum(toFloat64(volume) * toFloat64(close)) AS dollar_volume
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE window_start >= toDateTime('2026-06-11 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 ticker, session
    HAVING lo > 0 AND last_price >= 1
)
SELECT multiIf(l.shares < 20e6, 'under 20M shares',
               l.shares < 50e6, '20-50M shares',
               l.shares < 200e6, '50-200M shares',
               l.shares < 1000e6, '200M-1B shares',
               'over 1B shares') AS share_count_tier,
       uniqExact(d.ticker) AS companies,
       round(quantileDeterministic(0.5)(100 * (hi - lo) / lo, cityHash64(d.ticker, d.session)), 2) AS median_daily_range_pct,
       round(quantileDeterministic(0.9)(100 * (hi - lo) / lo, cityHash64(d.ticker, d.session)), 2) AS p90_daily_range_pct,
       round(quantileDeterministic(0.5)(dollar_volume, cityHash64(d.ticker, d.session)) / 1e6, 2) AS median_daily_dollar_volume_m
FROM daily AS d
INNER JOIN latest AS l ON d.ticker = l.ticker
GROUP BY share_count_tier
ORDER BY min(l.shares)

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