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Median and 90th percentile full day range, eight names, H1 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 2026-08-01, from Pattern Day Trader Rule: What Replaced It.

as of ranking 8×3read in context →
Median and 90th percentile full day range, eight names, H1 2026 — 8 rows by 3 columns, computed from US exchange, SIP and OPRA data.
tickermedian_range_pctp90_range_pct
TSLA3.936
NVDA3.375.72
MSFT2.634.96
AAPL2.443.95
JNJ1.943.15
QQQ1.783.2
KO1.762.68
SPY1.182.31
Rows × columns
8 × 3
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 Median and 90th percentile full day range, eight names, H1 2026, derived from the stored result.
ColumnTypeRangeNotes
ticker text 8 distinct values (AAPL, JNJ, KO…)
median_range_pct number 1.18 to 3.93 percent
p90_range_pct number 2.31 to 6 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.

the exact SQL behind every number 
WITH daily AS (
    SELECT ticker,
           toDate(toTimeZone(window_start, 'America/New_York')) AS session_date,
           toFloat64(max(high)) AS day_high,
           toFloat64(min(low)) AS day_low,
           toFloat64(argMin(open, window_start)) AS day_open
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('SPY', 'QQQ', 'AAPL', 'MSFT', 'NVDA', 'TSLA', 'KO', 'JNJ')
      AND window_start >= toDateTime('2026-01-01 05:00:00')
      AND window_start < toDateTime('2026-07-01 04:00:00')
    GROUP BY ticker, session_date
)
SELECT ticker,
       round(quantileDeterministic(0.5)(100 * (day_high - day_low) / day_open, cityHash64(session_date)), 2) AS median_range_pct,
       round(quantileDeterministic(0.9)(100 * (day_high - day_low) / day_open, cityHash64(session_date)), 2) AS p90_range_pct
FROM daily
WHERE day_open > 0
GROUP BY ticker
ORDER BY median_range_pct DESC

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