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Fourteen chip names: prior close, day close, day range, dollar volume, low/high minute ET

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 2026-07-26, from Market Recap: July 8, 2026, The Day in Numbers.

as of table 14×10read in context →
Fourteen chip names: prior close, day close, day range, dollar volume, low/high minute ET — 14 rows by 10 columns, computed from US exchange, SIP and OPRA data.
tickerprior_closeday_closepct_chgrange_pctday_lowday_highlow_minute_ethigh_minute_etday_dollar_bn
AMD516.57517.260.134.81498.15522.986835878.93
AVGO370.79388.674.824.91376.89395.095707789.39
INTC110.5110.27-0.215.5104.41110.497139579.48
KLAC216.52221.032.084.2214.3223.46859291.79
LRCX326.12332.932.094.53322.72337.55705872.1
MRVL230.81231.660.375.12224.98236.795705934.57
MU938.95949.371.116.24900.4195957060032.02
NVDA196.93204.143.665.13195.06205.1657093724.17
SNDK1619.261729.46.88.9415901734.6957095916.82
SOXL165.27174.845.7910.82158.87176.755708168.12
SOXS4.824.52-6.22114.464.999295702.97
STX827.4859.683.96.18811.27862.415709593.46
TER343.1351.562.475.6335.06354.276865870.77
WDC532.34550.713.456.91526562.765706003.03
Rows × columns
14 × 10
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 Fourteen chip names: prior close, day close, day range, dollar volume, low/high minute ET, derived from the stored result.
ColumnTypeRangeNotes
ticker text 14 distinct values (AMD, AVGO, INTC…)
prior_close number 4.82 to 1,619.26 US dollars
day_close number 4.52 to 1,729.4 US dollars
pct_chg number -6.22 to 6.8 percent
range_pct number 4.2 to 11 percent
day_low number 4.46 to 1,590 US dollars
day_high number 4.99 to 1,734.69 US dollars
low_minute_et number 570 to 929 US dollars
high_minute_et number 570 to 959 US dollars
day_dollar_bn number 0.77 to 32.02

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 per_name AS (
    SELECT
        ticker,
        toFloat64(argMaxIf(close, window_start, window_start < '2026-07-08 00:00:00')) AS prior_close,
        toFloat64(argMaxIf(close, window_start, window_start >= '2026-07-08 00:00:00')) AS day_close,
        maxIf(toFloat64(high), window_start >= '2026-07-08 00:00:00') AS day_high,
        minIf(toFloat64(low), window_start >= '2026-07-08 00:00:00') AS day_low,
        argMinIf(window_start, (toFloat64(low), toInt64(toUnixTimestamp(window_start))), window_start >= '2026-07-08 00:00:00') AS low_bar,
        argMaxIf(window_start, (toFloat64(high), -toInt64(toUnixTimestamp(window_start))), window_start >= '2026-07-08 00:00:00') AS high_bar,
        round(sumIf(toFloat64(close) * toFloat64(volume), window_start >= '2026-07-08 00:00:00') / 1e9, 2) AS day_dollar_bn
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('AMD', 'AVGO', 'INTC', 'KLAC', 'LRCX', 'MRVL', 'MU', 'NVDA', 'SNDK', 'SOXL', 'SOXS', 'STX', 'TER', 'WDC')
      AND ((window_start >= '2026-07-07 13:30:00' AND window_start < '2026-07-07 20:00:00')
        OR (window_start >= '2026-07-08 13:30:00' AND window_start < '2026-07-08 20:00:00'))
    GROUP BY ticker
)
SELECT
    ticker,
    round(prior_close, 2) AS prior_close,
    round(day_close, 2) AS day_close,
    round((day_close / prior_close - 1) * 100, 2) AS pct_chg,
    round(((day_high - day_low) / prior_close) * 100, 2) AS range_pct,
    round(toFloat64(day_low), 2) AS day_low,
    round(toFloat64(day_high), 2) AS day_high,
    toUInt32(toHour(toTimeZone(low_bar, 'America/New_York')) * 60 + toMinute(toTimeZone(low_bar, 'America/New_York'))) AS low_minute_et,
    toUInt32(toHour(toTimeZone(high_bar, 'America/New_York')) * 60 + toMinute(toTimeZone(high_bar, 'America/New_York'))) AS high_minute_et,
    day_dollar_bn
FROM per_name
ORDER BY ticker

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