STRASMORE/EXPLORE 2,170 QUERIES

The information flow in one row: tagging switches on, feed composition, co-tags

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 2026-07-27, from SPCX: SpaceX's First Month on the Public Market.

as of scalar 1×17read in context →
prior 12 months articles
0
first tagged day
2026-06-11
first day articles
14
peak day date
2026-06-12
peak day articles
42
june articles
347
publishers
4
top publisher
The Motley Fool
top publisher articles
224
top publisher pct
65
tsla co articles
83
nvda co articles
59
alphabet co articles
57
rklb co articles
21
asts co articles
15
tsla minus rklb
62
notes offering headline
SpaceX's Fundraising Is Not Over With a $20 Billion New Bond Offering
Rows × columns
1 × 17
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 The information flow in one row: tagging switches on, feed composition, co-tags, derived from the stored result.
ColumnTypeRangeNotes
prior_12_months_articles number every row is 0
first_tagged_day date 2026-06-11
first_day_articles number every row is 14
peak_day_date date 2026-06-12
peak_day_articles number every row is 42
june_articles number every row is 347
publishers number every row is 4
top_publisher text 1 distinct value (The Motley Fool)
top_publisher_articles number every row is 224
top_publisher_pct number every row is 65 percent
tsla_co_articles number every row is 83
nvda_co_articles number every row is 59
alphabet_co_articles number every row is 57
rklb_co_articles number every row is 21
asts_co_articles number every row is 15
tsla_minus_rklb number every row is 62
notes_offering_headline text 1 distinct value

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 count()
        FROM global_markets.stocks_news
        WHERE has(tickers, 'SPCX')
          AND published_utc >= toDateTime('2025-06-01 00:00:00')
          AND published_utc < toDateTime('2026-06-01 00:00:00')
    ) AS prior_12mo,
    (
        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, 'SPCX')
              AND published_utc >= toDateTime('2026-06-01 00:00:00')
              AND published_utc < toDateTime('2026-07-01 04:00:00')
            GROUP BY d ORDER BY n DESC, d ASC LIMIT 1
        )
    ) AS peak_day,
    (
        SELECT (JSONExtractString(any(publisher), 'name'), count())
        FROM global_markets.stocks_news
        WHERE has(tickers, 'SPCX')
          AND published_utc >= toDateTime('2026-06-01 00:00:00')
          AND published_utc < toDateTime('2026-07-01 04:00:00')
        GROUP BY JSONExtractString(publisher, 'name') ORDER BY count() DESC LIMIT 1
    ) AS top_pub,
    (
        SELECT n
        FROM (
            SELECT toDate(toTimeZone(published_utc, 'America/New_York')) AS d, count() AS n
            FROM global_markets.stocks_news
            WHERE has(tickers, 'SPCX')
              AND published_utc >= toDateTime('2026-06-01 00:00:00')
              AND published_utc < toDateTime('2026-07-01 04:00:00')
            GROUP BY d ORDER BY d ASC LIMIT 1
        )
    ) AS first_day_n,
    (
        SELECT substring(title, 1, 90)
        FROM global_markets.stocks_news
        WHERE has(tickers, 'SPCX')
          AND published_utc >= toDateTime('2026-06-22 04:00:00')
          AND published_utc < toDateTime('2026-06-24 04:00:00')
          AND title ILIKE '%bond%'
        ORDER BY published_utc ASC LIMIT 1
    ) AS notes_headline
SELECT
    prior_12mo AS prior_12_months_articles,
    toString(min(toDate(toTimeZone(published_utc, 'America/New_York')))) AS first_tagged_day,
    first_day_n AS first_day_articles,
    peak_day.1 AS peak_day_date,
    peak_day.2 AS peak_day_articles,
    count() AS june_articles,
    uniqExact(JSONExtractString(publisher, 'name')) AS publishers,
    top_pub.1 AS top_publisher,
    top_pub.2 AS top_publisher_articles,
    round(100.0 * top_pub.2 / count(), 0) AS top_publisher_pct,
    countIf(has(tickers, 'TSLA')) AS tsla_co_articles,
    countIf(has(tickers, 'NVDA')) AS nvda_co_articles,
    countIf(hasAny(tickers, ['GOOG', 'GOOGL', 'GOOGN', 'GOOGM'])) AS alphabet_co_articles,
    countIf(has(tickers, 'RKLB')) AS rklb_co_articles,
    countIf(has(tickers, 'ASTS')) AS asts_co_articles,
    countIf(has(tickers, 'TSLA')) - countIf(has(tickers, 'RKLB')) AS tsla_minus_rklb,
    notes_headline AS notes_offering_headline
FROM global_markets.stocks_news
WHERE has(tickers, 'SPCX')
  AND published_utc >= toDateTime('2026-06-01 00:00:00')
  AND published_utc < toDateTime('2026-07-01 04:00:00')

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