STRASMORE/EXPLORE 2,170 QUERIES

The arc on one row: issue price, first print, June peak, and the latest close

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 2026-08-20, from SPCX: SpaceX Stock Price Decline From Peak.

as of scalar 1×15read in context →
issue price
135
ipo open
150
peak price
225.64
peak label
Jun 16, 2026
peak month
6
peak day
16
latest label
Aug 19, 2026
latest close
139.31
drop from peak usd
86.33
decline from peak pct
38.3
peak above ipo pct
50.4
vs first print pct
-7.1
vs issue pct
3.2
spy period pct
3.96
spy minus spcx pp
11.1
Rows × columns
1 × 15
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 arc on one row: issue price, first print, June peak, and the latest close, derived from the stored result.
ColumnTypeRangeNotes
issue_price text 1 distinct value (135)
ipo_open number every row is 150 US dollars
peak_price number every row is 225.64 US dollars
peak_label text 1 distinct value (Jun 16, 2026)
peak_month number every row is 6
peak_day number every row is 16
latest_label text 1 distinct value (Aug 19, 2026)
latest_close number every row is 139.31 US dollars
drop_from_peak_usd number every row is 86.33 US dollars
decline_from_peak_pct number every row is 38.3 percent
peak_above_ipo_pct number every row is 50.4 percent
vs_first_print_pct number every row is -7.1 percent
vs_issue_pct number every row is 3.2 percent
spy_period_pct number every row is 3.96 percent
spy_minus_spcx_pp number every row is 11.1

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
    spcx_sessions AS (
        SELECT
            toDate(toTimeZone(window_start, 'America/New_York')) AS d,
            argMax(toFloat64(close), window_start) AS c,
            max(toFloat64(high)) AS hi
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'SPCX'
          AND window_start >= '2026-06-12 00:00:00' AND window_start < now()
          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
        GROUP BY d
        HAVING count() >= 150
    ),
    latest_row AS (
        SELECT max(d) AS latest_d, argMax(c, d) AS latest_c
        FROM spcx_sessions
    ),
    peak_row AS (
        SELECT max(hi) AS peak_hi, argMax(d, (hi, -toInt32(d))) AS peak_d
        FROM spcx_sessions
    ),
    first_print AS (
        SELECT round(toFloat64(argMin(open, window_start)), 2) AS ipo_open_px
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'SPCX'
          AND window_start >= '2026-06-12 00:00:00' AND window_start < '2026-06-13 00:00:00'
          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
    ),
    issue_row AS (
        SELECT toFloat64(final_issue_price) AS issue_px
        FROM global_markets.stocks_ipos
        WHERE ticker = 'SPCX'
        ORDER BY listing_date DESC LIMIT 1
    ),
    spy_ret AS (
        SELECT round((argMax(toFloat64(close), window_start) / argMin(toFloat64(open), window_start) - 1) * 100, 2) AS spy_pct
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'SPY'
          AND window_start >= '2026-06-12 00:00:00' AND window_start < now()
          AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
    )
SELECT
    toString(round(ip.issue_px, 2)) AS issue_price,
    fp.ipo_open_px AS ipo_open,
    round(pk.peak_hi, 2) AS peak_price,
    formatDateTime(pk.peak_d, '%b %e, %Y') AS peak_label,
    toMonth(pk.peak_d) AS peak_month,
    toDayOfMonth(pk.peak_d) AS peak_day,
    formatDateTime(lt.latest_d, '%b %e, %Y') AS latest_label,
    round(lt.latest_c, 2) AS latest_close,
    round(pk.peak_hi - lt.latest_c, 2) AS drop_from_peak_usd,
    round((pk.peak_hi - lt.latest_c) / pk.peak_hi * 100, 1) AS decline_from_peak_pct,
    round((pk.peak_hi - fp.ipo_open_px) / fp.ipo_open_px * 100, 1) AS peak_above_ipo_pct,
    round((lt.latest_c / fp.ipo_open_px - 1) * 100, 1) AS vs_first_print_pct,
    round((lt.latest_c / ip.issue_px - 1) * 100, 1) AS vs_issue_pct,
    sr.spy_pct AS spy_period_pct,
    round(sr.spy_pct - (lt.latest_c / fp.ipo_open_px - 1) * 100, 1) AS spy_minus_spcx_pp
FROM peak_row pk, first_print fp, issue_row ip, latest_row lt, spy_ret sr

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