STRASMORE/EXPLORE 3,256 QUERIES

qqq_monthly

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 2026-10-09, from what-is-qqq-etf-for-korean-investors.

as of series 36×2read in context →
qqq_monthly — 36 rows by 2 columns, computed from US exchange, SIP and OPRA data.
monthmonth_close
2023-10350.87
2023-11388.83
2023-12409.52
2024-01416.97
2024-02439
2024-03444.01
2024-04424.59
2024-05450.71
2024-06479.11
2024-07471.07
2024-08476.27
2024-09488.07
2024-10483.85
2024-11509.74
2024-12511.23
2025-01522.29
2025-02508.17
2025-03468.92
2025-04475.47
2025-05519.11
2025-06551.64
2025-07565.01
2025-08570.4
2025-09600.37
2025-10629.07
2025-11619.25
2025-12614.31
2026-01621.87
2026-02607.29
2026-03577.18
2026-04667.74
2026-05738.31
2026-06736.4
2026-07687.99
2026-08716.76
2026-09739.77
Rows × columns
36 × 2
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 qqq_monthly, derived from the stored result.
ColumnTypeRangeNotes
month text 36 distinct values (2023-10, 2023-11, 2023-12…)
month_close number 350.87 to 739.77 US dollars

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.

WITH monthly AS
(
    SELECT
        toStartOfMonth(date)                     AS month_start,
        round(toFloat64(argMax(close, date)), 2) AS month_close
    FROM global_markets.stocks_daily_aggs
    WHERE ticker = 'QQQ'
      AND date >= '2023-10-01'
      AND date <  toStartOfMonth(today())
    GROUP BY month_start
)
SELECT
    formatDateTime(month_start, '%Y-%m') AS month,
    month_close
FROM monthly
ORDER BY month_start
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