STRASMORE/EXPLORE 3,256 QUERIES

Intraday range (high minus low, over the open), 2021 to 2025

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 Can You Make $1,000 a Day Day Trading?.

as of table 4×5read in context →
Intraday range (high minus low, over the open), 2021 to 2025 — 4 rows by 5 columns, computed from US exchange, SIP and OPRA data.
tickermedian_range_pctp75_range_pctp90_range_pctsession_count
SPY0.991.452.151255
QQQ1.371.962.721255
NVDA3.434.646.291255
TSLA4.075.467.141255
Rows × columns
4 × 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 Intraday range (high minus low, over the open), 2021 to 2025, derived from the stored result.
ColumnTypeRangeNotes
ticker text 4 distinct values (NVDA, QQQ, SPY…)
median_range_pct number 0.99 to 4.07 percent
p75_range_pct number 1.45 to 5.46 percent
p90_range_pct number 2.15 to 7.14 percent
session_count number every row is 1,255 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.

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.

SELECT
    ticker,
    round(quantileExact(0.5)(range_pct), 2)  AS median_range_pct,
    round(quantileExact(0.75)(range_pct), 2) AS p75_range_pct,
    round(quantileExact(0.9)(range_pct), 2)  AS p90_range_pct,
    count()                                  AS session_count
FROM
(
    SELECT
        ticker,
        date,
        (toFloat64(argMax(high, _ingest_time)) - toFloat64(argMax(low, _ingest_time)))
            / toFloat64(argMax(open, _ingest_time)) * 100 AS range_pct
    FROM global_markets.stocks_daily_aggs
    WHERE ticker IN ('SPY', 'QQQ', 'NVDA', 'TSLA')
      AND date >= '2021-01-01'
      AND date <  '2026-01-01'
    GROUP BY ticker, date
    HAVING toFloat64(argMax(open, _ingest_time)) > 0
)
GROUP BY ticker
ORDER BY indexOf(['SPY', 'QQQ', 'NVDA', 'TSLA'], ticker)
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