hilo_outside_regular

Name: hilo_outside_regular
Creator: Strasmore
Published: 2026-10-08
License: https://www.strasmore.com/terms/

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 2026-10-08, from dse-last-trade-price-vs-closing-price.

as of 2026-10-08 ranking 6×3read in context →

hilo_outside_regular — 6 rows by 3 columns, computed 2026-10-08 from US exchange, SIP and OPRA data.
symbol	high_above_regular_pct	low_below_regular_pct
JNJ	1.6	1.6
KO	1.6	0
MSFT	0	0
SPY	0	1.6
AAPL	0	0
NVDA	0	0

Rows × columns: 6 × 3
Computed: 2026-10-08
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 hilo_outside_regular, derived from the stored result.
Column	Type	Range	Notes
`symbol`	text	6 distinct values (AAPL, JNJ, KO…)
`high_above_regular_pct`	number	0 to 1.6	percent
`low_below_regular_pct`	number	0 to 1.6	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 2026-10-08, 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
    regular AS
    (
        SELECT
            ticker,
            toDate(toTimeZone(window_start, 'America/New_York')) AS session_date,
            max(high) AS regular_high,
            min(low)  AS regular_low
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker IN ('AAPL', 'MSFT', 'NVDA', 'SPY', 'KO', 'JNJ')
          AND window_start >= '2026-07-01 00:00:00'
          AND window_start <  '2026-10-01 00:00:00'
          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
               + toMinute(toTimeZone(window_start, 'America/New_York'))) >= 570
          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
               + toMinute(toTimeZone(window_start, 'America/New_York'))) < 960
        GROUP BY ticker, session_date
    ),
    daily_bars AS
    (
        SELECT
            ticker,
            date      AS session_date,
            any(high) AS daily_high,
            any(low)  AS daily_low
        FROM global_markets.stocks_daily_aggs
        WHERE ticker IN ('AAPL', 'MSFT', 'NVDA', 'SPY', 'KO', 'JNJ')
          AND date >= '2026-07-01'
          AND date <  '2026-10-01'
        GROUP BY ticker, session_date
    )
SELECT
    r.ticker AS symbol,
    round(100 * countIf(toFloat64(d.daily_high) > toFloat64(r.regular_high)) / count(), 1) AS high_above_regular_pct,
    round(100 * countIf(toFloat64(d.daily_low)  < toFloat64(r.regular_low))  / count(), 1) AS low_below_regular_pct
FROM regular AS r
INNER JOIN daily_bars AS d
    ON r.ticker = d.ticker AND r.session_date = d.session_date
GROUP BY symbol
ORDER BY high_above_regular_pct DESC

SQL to run

WITH
    regular AS
    (
        SELECT
            ticker,
            toDate(toTimeZone(window_start, 'America/New_York')) AS session_date,
            max(high) AS regular_high,
            min(low)  AS regular_low
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker IN ('AAPL', 'MSFT', 'NVDA', 'SPY', 'KO', 'JNJ')
          AND window_start >= '2026-07-01 00:00:00'
          AND window_start <  '2026-10-01 00:00:00'
          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
               + toMinute(toTimeZone(window_start, 'America/New_York'))) >= 570
          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
               + toMinute(toTimeZone(window_start, 'America/New_York'))) < 960
        GROUP BY ticker, session_date
    ),
    daily_bars AS
    (
        SELECT
            ticker,
            date      AS session_date,
            any(high) AS daily_high,
            any(low)  AS daily_low
        FROM global_markets.stocks_daily_aggs
        WHERE ticker IN ('AAPL', 'MSFT', 'NVDA', 'SPY', 'KO', 'JNJ')
          AND date >= '2026-07-01'
          AND date <  '2026-10-01'
        GROUP BY ticker, session_date
    )
SELECT
    r.ticker AS symbol,
    round(100 * countIf(toFloat64(d.daily_high) > toFloat64(r.regular_high)) / count(), 1) AS high_above_regular_pct,
    round(100 * countIf(toFloat64(d.daily_low)  < toFloat64(r.regular_low))  / count(), 1) AS low_below_regular_pct
FROM regular AS r
INNER JOIN daily_bars AS d
    ON r.ticker = d.ticker AND r.session_date = d.session_date
GROUP BY symbol
ORDER BY high_above_regular_pct DESC

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