Friday close to Monday's first minute: absolute overnight move, 2023 to July 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 2026-08-04, from What Happens If an Option Expires In the Money.
| ticker | weekends_count | median_weekend_gap_pct | p90_weekend_gap_pct |
|---|---|---|---|
| NVDA | 157 | 1.05 | 3.04 |
| CVX | 157 | 0.49 | 1.59 |
| AAPL | 157 | 0.49 | 1.71 |
| MSFT | 157 | 0.41 | 1.36 |
| T | 157 | 0.35 | 1.15 |
| KO | 157 | 0.31 | 0.68 |
| JNJ | 157 | 0.28 | 0.88 |
| SPY | 157 | 0.28 | 0.99 |
- Rows × columns
- 8 × 4
- 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 |
|---|---|---|---|
ticker |
text | 8 distinct values (AAPL, CVX, JNJ…) | |
weekends_count |
number | every row is 157 | count |
median_weekend_gap_pct |
number | 0.28 to 1.05 | percent |
p90_weekend_gap_pct |
number | 0.68 to 3.04 | 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 session_marks AS (
SELECT ticker,
toDate(toTimeZone(window_start, 'America/New_York')) AS session,
argMax(toFloat64(close), window_start) AS close_px,
argMin(toFloat64(close), window_start) AS first_minute_px,
count() AS session_bars
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('SPY', 'AAPL', 'MSFT', 'NVDA', 'JNJ', 'CVX', 'KO', 'T')
AND toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2023-01-02')
AND toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-07-31')
AND toDayOfWeek(toDate(toTimeZone(window_start, 'America/New_York'))) IN (1, 5)
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
+ toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
GROUP BY ticker, session
HAVING session_bars > 300
),
weekends AS (
SELECT ticker,
subtractDays(toMonday(session), if(toDayOfWeek(session) = 1, 7, 0)) AS weekend_id,
argMaxIf(close_px, session, toDayOfWeek(session) = 5) AS friday_close,
argMaxIf(first_minute_px, session, toDayOfWeek(session) = 1) AS monday_first_px
FROM session_marks
GROUP BY ticker, weekend_id
HAVING countIf(toDayOfWeek(session) = 5) = 1
AND countIf(toDayOfWeek(session) = 1) = 1
AND friday_close > 0
)
SELECT ticker,
count() AS weekends_count,
round(quantileDeterministic(0.5)(abs(monday_first_px / friday_close - 1) * 100,
cityHash64(toString(weekend_id))), 2) AS median_weekend_gap_pct,
round(quantileDeterministic(0.9)(abs(monday_first_px / friday_close - 1) * 100,
cityHash64(toString(weekend_id))), 2) AS p90_weekend_gap_pct
FROM weekends
GROUP BY ticker
ORDER BY median_weekend_gap_pct DESC