Between-session gaps on four equity index ETFs, 2015 to date
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 2026-10-09, from Futures Price Limits and Price Banding.
| symbol | sample_size | median_gap_pct | p99_gap_pct | largest_gap_pct |
|---|---|---|---|---|
| IWM | 2934 | 0.381 | 3.52 | 9.08 |
| QQQ | 2940 | 0.376 | 3.12 | 9.46 |
| DIA | 2940 | 0.287 | 2.67 | 11.03 |
| SPY | 2945 | 0.291 | 2.6 | 10.45 |
- Rows × columns
- 4 × 5
- 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 |
|---|---|---|---|
symbol |
text | 4 distinct values (DIA, IWM, QQQ…) | |
sample_size |
number | 2,934 to 2,945 | |
median_gap_pct |
number | 0.287 to 0.381 | percent |
p99_gap_pct |
number | 2.6 to 3.52 | percent |
largest_gap_pct |
number | 9.08 to 11.03 | 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
ticker,
date,
any(open) AS session_open,
any(close) AS session_close
FROM global_markets.stocks_daily_aggs
WHERE ticker IN ('SPY', 'QQQ', 'DIA', 'IWM')
AND date >= '2015-01-01'
AND date < '2026-10-01'
GROUP BY ticker, date
),
gaps AS
(
SELECT
ticker,
date,
abs(toFloat64(session_open)
/ any(toFloat64(session_close)) OVER (PARTITION BY ticker ORDER BY date ASC
ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING)
- 1) AS gap
FROM daily
)
SELECT
ticker AS symbol,
count() AS sample_size,
round(100 * quantileDeterministic(0.5)(gap, toUInt64(toYYYYMMDD(date))), 3) AS median_gap_pct,
round(100 * quantileDeterministic(0.99)(gap, toUInt64(toYYYYMMDD(date))), 2) AS p99_gap_pct,
round(100 * max(gap), 2) AS largest_gap_pct
FROM gaps
WHERE isFinite(gap)
AND gap > 0
GROUP BY ticker
ORDER BY p99_gap_pct DESC
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