How often a resting limit was reached, by distance from the prior close (SPY, 2021 to Sep 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 2026-10-05, from Buy Limit vs Sell Limit Orders Explained.
| limit_distance | buy_limit_touched_pct | sell_limit_touched_pct |
|---|---|---|
| 0.25 | 60.7 | 68.8 |
| 0.5 | 44.1 | 48.1 |
| 1 | 23.2 | 22.2 |
| 1.5 | 12.4 | 10.7 |
| 2 | 5.8 | 4.7 |
| 3 | 1.5 | 1.1 |
- Rows × columns
- 6 × 3
- Computed
- Completeness
- No missing values
- Source
- US exchange, SIP and OPRA market data
- Licence
- Strasmore terms · free, no signup
What each column holds
| Column | Type | Range | Notes |
|---|---|---|---|
limit_distance |
number | 0.25 to 3 | |
buy_limit_touched_pct |
number | 1.5 to 60.7 | percent |
sell_limit_touched_pct |
number | 1.1 to 68.8 | 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 daily AS
(
SELECT
date,
toFloat64(any(close)) AS close,
toFloat64(min(low)) AS low,
toFloat64(max(high)) AS high
FROM global_markets.stocks_daily_aggs
WHERE ticker = 'SPY'
AND date >= '2021-01-01'
AND date < '2026-10-01'
GROUP BY date
),
framed AS
(
SELECT
date,
low,
high,
lagInFrame(close, 1) OVER (ORDER BY date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prior_close
FROM daily
)
SELECT
limit_distance,
round(100 * countIf(low <= prior_close * (1 - limit_distance / 100)) / count(), 1) AS buy_limit_touched_pct,
round(100 * countIf(high >= prior_close * (1 + limit_distance / 100)) / count(), 1) AS sell_limit_touched_pct
FROM
(
SELECT
low,
high,
prior_close,
arrayJoin([0.25, 0.5, 1.0, 1.5, 2.0, 3.0]) AS limit_distance
FROM framed
WHERE prior_close > 0
)
GROUP BY limit_distance
ORDER BY limit_distance
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