STRASMORE/EXPLORE 2,170 QUERIES

News-feed attention: articles tagged NVDA during the week, decoded

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 1×11read in context →
week articles
86
publishers
3
peak day date
2026-07-06
peak day articles
25
thursday articles
20
peak minus thursday
5
top publisher
The Motley Fool
top publisher share pct
77.9
mu co articles
24
amd co articles
17
ai titled articles
29
Rows × columns
1 × 11
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 News-feed attention: articles tagged NVDA during the week, decoded, derived from the stored result.
ColumnTypeRangeNotes
week_articles number every row is 86
publishers number every row is 3
peak_day_date date 2026-07-06
peak_day_articles number every row is 25
thursday_articles number every row is 20
peak_minus_thursday number every row is 5
top_publisher text 1 distinct value (The Motley Fool)
top_publisher_share_pct number every row is 77.9 percent
mu_co_articles number every row is 24
amd_co_articles number every row is 17
ai_titled_articles number every row is 29

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
    (
        SELECT (toString(d), n)
        FROM (
            SELECT toDate(toTimeZone(published_utc, 'America/New_York')) AS d, count() AS n
            FROM global_markets.stocks_news
            WHERE has(tickers, 'NVDA')
              AND published_utc >= toDateTime('2026-07-06 00:00:00')
              AND published_utc < toDateTime('2026-07-11 04:00:00')
            GROUP BY d ORDER BY n DESC, d ASC LIMIT 1
        )
    ) AS peak_day,
    (
        SELECT (JSONExtractString(publisher, 'name') AS p, count() AS n)
        FROM global_markets.stocks_news
        WHERE has(tickers, 'NVDA')
          AND published_utc >= toDateTime('2026-07-06 00:00:00')
          AND published_utc < toDateTime('2026-07-11 04:00:00')
        GROUP BY p ORDER BY n DESC, p ASC LIMIT 1
    ) AS top_pub
SELECT
    count() AS week_articles,
    uniqExact(JSONExtractString(publisher, 'name')) AS publishers,
    peak_day.1 AS peak_day_date,
    peak_day.2 AS peak_day_articles,
    countIf(toDate(toTimeZone(published_utc, 'America/New_York')) = toDate('2026-07-09')) AS thursday_articles,
    peak_day.2 - countIf(toDate(toTimeZone(published_utc, 'America/New_York')) = toDate('2026-07-09')) AS peak_minus_thursday,
    top_pub.1 AS top_publisher,
    round(100.0 * top_pub.2 / count(), 1) AS top_publisher_share_pct,
    countIf(has(tickers, 'MU')) AS mu_co_articles,
    countIf(has(tickers, 'AMD')) AS amd_co_articles,
    countIf(positionCaseInsensitive(title, 'artificial intelligence') > 0 OR position(title, 'AI') > 0) AS ai_titled_articles
FROM global_markets.stocks_news
WHERE has(tickers, 'NVDA')
  AND published_utc >= toDateTime('2026-07-06 00:00:00')
  AND published_utc < toDateTime('2026-07-11 04:00:00')

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