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DXYZ close versus its June 30, 2026 published NAV of $34.30

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 2026-11-01, from How Pre-IPO Shares Trade Before the Ticker.

as of series 45×6read in context →
DXYZ close versus its June 30, 2026 published NAV of $34.30 — 45 rows by 6 columns, computed from US exchange, SIP and OPRA data.
session_datesession_labelclosenav_june_30_2026vs_nav_pctvolume_millions
2026-08-28Aug 28, 202634.7434.31.31.47
2026-08-31Aug 31, 202632.1334.3-6.31.68
2026-09-01Sep 1, 202631.634.3-7.91.12
2026-09-02Sep 2, 202632.734.3-4.70.68
2026-09-03Sep 3, 202632.2534.3-60.72
2026-09-04Sep 4, 202632.734.3-4.70.73
2026-09-08Sep 8, 202634.2434.3-0.21.38
2026-09-09Sep 9, 202632.634.3-50.92
2026-09-10Sep 10, 202632.0534.3-6.60.65
2026-09-11Sep 11, 202632.1134.3-6.40.53
2026-09-14Sep 14, 202631.5734.3-80.85
2026-09-15Sep 15, 202630.2634.3-11.80.65
2026-09-16Sep 16, 202630.7534.3-10.30.69
2026-09-17Sep 17, 202631.1534.3-9.20.59
2026-09-18Sep 18, 202631.3134.3-8.71.08
2026-09-21Sep 21, 202630.9934.3-9.70.94
2026-09-22Sep 22, 202630.3534.3-11.50.82
2026-09-23Sep 23, 202629.7334.3-13.30.9
2026-09-24Sep 24, 202629.1434.3-150.94
2026-09-25Sep 25, 202630.6234.3-10.70.8
2026-09-28Sep 28, 202629.8634.3-12.90.45
2026-09-29Sep 29, 202630.6434.3-10.70.52
2026-09-30Sep 30, 202630.8534.3-10.10.53
2026-10-01Oct 1, 202631.2434.3-8.90.82
2026-10-02Oct 2, 202632.834.3-4.41.1
2026-10-05Oct 5, 202632.5534.3-5.11.07
2026-10-06Oct 6, 202631.5734.3-80.93
2026-10-07Oct 7, 202631.1634.3-9.20.61
2026-10-08Oct 8, 202630.534.3-11.10.86
2026-10-09Oct 9, 202630.7434.3-10.40.57
2026-10-12Oct 12, 202630.2934.3-11.70.63
2026-10-13Oct 13, 202630.134.3-12.20.88
2026-10-14Oct 14, 202630.0434.3-12.41.51
2026-10-15Oct 15, 20262934.3-15.51.74
2026-10-16Oct 16, 202627.9134.3-18.60.91
2026-10-19Oct 19, 202627.9134.3-18.60.5
2026-10-20Oct 20, 202628.5534.3-16.80.65
2026-10-21Oct 21, 20262934.3-15.50.42
2026-10-22Oct 22, 202626.8834.3-21.61.02
2026-10-23Oct 23, 202627.534.3-19.80.67
2026-10-26Oct 26, 202628.1134.3-181.06
2026-10-27Oct 27, 202628.134.3-18.10.72
2026-10-28Oct 28, 202627.6534.3-19.40.65
2026-10-29Oct 29, 202626.7934.3-21.90.54
2026-10-30Oct 30, 202625.5334.3-25.60.95
Rows × columns
45 × 6
Period covered
to
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 DXYZ close versus its June 30, 2026 published NAV of $34.30, derived from the stored result.
ColumnTypeRangeNotes
session_date date 2026-08-28 to 2026-10-30
session_label text 45 distinct values (Aug 28, 2026, Aug 31, 2026, Oct 1, 2026…)
close number 25.53 to 34.74 US dollars
nav_june_30_2026 number every row is 34.3 US dollars
vs_nav_pct number -25.6 to 1.3 percent
volume_millions number 0.42 to 1.74 count

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.

Run it yourself

This is the exact query behind the result above. Change a ticker, a date or a column and run it against the warehouse — no account, no key. The no-signup tier is smaller than the one this page was computed on; a query that reaches past it comes back saying which plan runs it.

SELECT
    toString(toDate(date))                                   AS session_date,
    concat(formatDateTime(toDate(date), '%b'), ' ',
           toString(toDayOfMonth(toDate(date))), ', ',
           toString(toYear(toDate(date))))                   AS session_label,
    round(toFloat64(close), 2)                               AS close,
    34.30                                                    AS nav_june_30_2026,
    round((toFloat64(close) / 34.30 - 1) * 100, 1)           AS vs_nav_pct,
    round(toFloat64(volume) / 1e6, 2)                        AS volume_millions
FROM global_markets.stocks_daily_aggs
WHERE ticker = 'DXYZ'
  AND date >= '2026-08-28'
ORDER BY session_date
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