STRASMORE/EXPLORE 3,127 QUERIES

How often a 2 percent stop distance gets touched, by name

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 2026-10-06, from Buy Stop vs Sell Stop Orders: How Each Fires.

as of ranking 6×3read in context →
How often a 2 percent stop distance gets touched, by name — 6 rows by 3 columns, computed from US exchange, SIP and OPRA data.
tickerdown_touch_pctup_touch_pct
NVDA32.838
MSFT20.825.2
T18.419.2
AAPL12.819.2
KO6.410.8
SPY2.82.8
Rows × columns
6 × 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 How often a 2 percent stop distance gets touched, by name, derived from the stored result.
ColumnTypeRangeNotes
ticker text 6 distinct values (AAPL, KO, MSFT…)
down_touch_pct number 2.8 to 32.8 percent
up_touch_pct number 2.8 to 38 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 px AS
(
    SELECT
        ticker,
        date,
        toFloat64(low)  AS low_px,
        toFloat64(high) AS high_px,
        toFloat64(lagInFrame(close, 1) OVER (PARTITION BY ticker ORDER BY date)) AS prev_close
    FROM global_markets.stocks_daily_aggs
    WHERE ticker IN ('AAPL', 'KO', 'MSFT', 'NVDA', 'SPY', 'T')
      AND date >= '2025-10-01'
      AND date <  '2026-10-01'
      AND (ticker, date) NOT IN (SELECT ticker, execution_date FROM global_markets.stocks_splits)
)
SELECT
    ticker,
    round(100 * countIf(low_px  <= prev_close * 0.98) / count(), 1) AS down_touch_pct,
    round(100 * countIf(high_px >= prev_close * 1.02) / count(), 1) AS up_touch_pct
FROM px
WHERE prev_close > 0
GROUP BY ticker
ORDER BY down_touch_pct DESC
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