Median and 95th-percentile opening step by weekday (SPY, 2016 to 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 2026-10-07, from Forex Pending Order Types: Limits & Stops.
| weekday | median_gap_pct | p95_gap_pct |
|---|---|---|
| Friday | 0.327 | 1.213 |
| Monday | 0.307 | 1.442 |
| Thursday | 0.305 | 1.261 |
| Tuesday | 0.263 | 1.364 |
| Wednesday | 0.257 | 1.235 |
- Rows × columns
- 5 × 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 |
|---|---|---|---|
weekday |
text | 5 distinct values (Friday, Monday, Thursday…) | |
median_gap_pct |
number | 0.257 to 0.327 | percent |
p95_gap_pct |
number | 1.213 to 1.442 | 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,
any(toFloat64(open)) AS session_open,
any(toFloat64(close)) AS session_close
FROM global_markets.stocks_daily_aggs
WHERE ticker = 'SPY'
AND date >= '2016-01-01'
AND date < '2026-10-01'
GROUP BY date
),
gapped AS
(
SELECT
date,
session_open,
lagInFrame(session_close) OVER (ORDER BY date ASC ROWS BETWEEN 1 PRECEDING AND 1 PRECEDING) AS prior_close
FROM daily
)
SELECT
formatDateTime(date, '%W') AS weekday,
round(quantileDeterministic(0.5)(gap_pct, det), 3) AS median_gap_pct,
round(quantileDeterministic(0.95)(gap_pct, det), 3) AS p95_gap_pct
FROM
(
SELECT
date,
toYYYYMMDD(date) AS det,
abs(session_open / prior_close - 1) * 100 AS gap_pct
FROM gapped
WHERE prior_close > 0
)
GROUP BY weekday
ORDER BY median_gap_pct DESC
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