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NVDA: the ten largest overnight moves, July 2024 to June 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 2026-08-03, from How to Find a Stock's Earnings Date.

as of ranking 10×3read in context →
NVDA: the ten largest overnight moves, July 2024 to June 2026 — 10 rows by 3 columns, computed from US exchange, SIP and OPRA data.
gap_labelgap_pctabs_gap_pct
Mon Aug 5, 2024-14.4914.49
Mon Jan 27, 2025-12.6512.65
Wed Jul 31, 20248.338.33
Tue Apr 8, 20256.566.56
Mon Apr 7, 2025-6.496.49
Wed Apr 16, 2025-6.116.11
Thu Apr 3, 2025-5.655.65
Wed Mar 12, 20255.595.59
Thu May 29, 20255.475.47
Fri Aug 2, 2024-5.465.46
Rows × columns
10 × 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 NVDA: the ten largest overnight moves, July 2024 to June 2026, derived from the stored result.
ColumnTypeRangeNotes
gap_label text 10 distinct values
gap_pct number -14.49 to 8.33 percent
abs_gap_pct number 5.46 to 14.49 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.

the exact SQL behind every number 
WITH daily AS (
    SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS session,
           argMin(close, window_start) AS first_price,
           argMax(close, window_start) AS last_price
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'NVDA'
      AND toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2024-07-01')
      AND toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-06-30')
      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
           + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
    GROUP BY session
),
overnight AS (
    SELECT session,
           first_price,
           lagInFrame(last_price) OVER (ORDER BY session
                                        ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prior_close
    FROM daily
)
SELECT formatDateTime(session, '%a %b %e, %Y') AS gap_label,
       round((toFloat64(first_price) / toFloat64(prior_close) - 1) * 100, 2) AS gap_pct,
       round(abs(toFloat64(first_price) / toFloat64(prior_close) - 1) * 100, 2) AS abs_gap_pct
FROM overnight
WHERE toFloat64(prior_close) > 0
  AND abs(toFloat64(first_price) / toFloat64(prior_close) - 1) < 0.3
ORDER BY abs(toFloat64(first_price) / toFloat64(prior_close) - 1) DESC
LIMIT 10

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