STRASMORE/EXPLORE 2,170 QUERIES

NVDA position check as of Friday's close: trailing-year extremes and moving averages

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 NVDA: Sit-Out, Then Surge, Week of July 6.

as of scalar 1×12read in context →
friday close
210.96
high 52w
236.54
high 52w date
2026-05-14
pct below 52w high
10.8
low 52w
162.02
low 52w date
2025-07-14
close vs 52w low pct
30.2
ma 50d
209.16
close vs ma50 pct
0.9
ma 200d
191.75
close vs ma200 pct
10
trading days observed
251
Rows × columns
1 × 12
Period covered
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 position check as of Friday's close: trailing-year extremes and moving averages, derived from the stored result.
ColumnTypeRangeNotes
friday_close number every row is 210.96 US dollars
high_52w number every row is 236.54 US dollars
high_52w_date date 2026-05-14
pct_below_52w_high number every row is 10.8 percent
low_52w number every row is 162.02 US dollars
low_52w_date date 2025-07-14
close_vs_52w_low_pct number every row is 30.2 percent
ma_50d number every row is 209.16
close_vs_ma50_pct number every row is 0.9 percent
ma_200d number every row is 191.75
close_vs_ma200_pct number every row is 10 percent
trading_days_observed number every row is 251

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 et_date,
        argMaxIf(toFloat64(close), window_start, (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) AS c,
        maxIf(toFloat64(high), (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) AS h,
        minIf(toFloat64(low), (toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) AS l
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'NVDA'
      AND window_start >= toDateTime('2025-07-11 00:00:00') AND window_start < toDateTime('2026-07-11 00:00:00')
    GROUP BY et_date
    HAVING countIf((toHour(window_start) * 60 + toMinute(window_start)) BETWEEN 810 AND 1199) > 0
)
SELECT
    round(argMax(c, et_date), 2) AS friday_close,
    round(max(h), 2) AS high_52w,
    argMax(toString(et_date), (h, et_date)) AS high_52w_date,
    round(100 * (1 - argMax(c, et_date) / max(h)), 1) AS pct_below_52w_high,
    round(min(l), 2) AS low_52w,
    argMax(toString(et_date), (-l, et_date)) AS low_52w_date,
    round(100 * (argMax(c, et_date) / min(l) - 1), 1) AS close_vs_52w_low_pct,
    round(arrayAvg(arrayMap(t -> t.2, arraySlice(arrayReverseSort(t -> t.1, groupArray((et_date, c))), 1, 50))), 2) AS ma_50d,
    round(100 * (argMax(c, et_date) / arrayAvg(arrayMap(t -> t.2, arraySlice(arrayReverseSort(t -> t.1, groupArray((et_date, c))), 1, 50))) - 1), 1) AS close_vs_ma50_pct,
    round(arrayAvg(arrayMap(t -> t.2, arraySlice(arrayReverseSort(t -> t.1, groupArray((et_date, c))), 1, 200))), 2) AS ma_200d,
    round(100 * (argMax(c, et_date) / arrayAvg(arrayMap(t -> t.2, arraySlice(arrayReverseSort(t -> t.1, groupArray((et_date, c))), 1, 200))) - 1), 1) AS close_vs_ma200_pct,
    count() AS trading_days_observed
FROM daily

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