vxx_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 2026-09-22, from what-is-vxx-etn.
| month | month_label | vxx_close_adj | change_pct |
|---|---|---|---|
| 2019-01-01 | Jan 2019 | 158474.24 | 0 |
| 2019-05-01 | May 2019 | 124600.32 | -21.4 |
| 2019-06-01 | Jun 2019 | 106496 | -32.8 |
| 2019-07-01 | Jul 2019 | 96624.64 | -39 |
| 2019-08-01 | Aug 2019 | 110592 | -30.2 |
| 2019-09-01 | Sep 2019 | 97239.04 | -38.6 |
| 2019-10-01 | Oct 2019 | 80896 | -49 |
| 2019-11-01 | Nov 2019 | 67747.84 | -57.2 |
| 2019-12-01 | Dec 2019 | 61931.52 | -60.9 |
| 2020-01-01 | Jan 2020 | 66355.2 | -58.1 |
| 2020-02-01 | Feb 2020 | 93429.76 | -41 |
| 2020-03-01 | Mar 2020 | 189440 | 19.5 |
| 2020-04-01 | Apr 2020 | 155115.52 | -2.1 |
| 2020-05-01 | May 2020 | 135700.48 | -14.4 |
| 2020-06-01 | Jun 2020 | 139059.2 | -12.3 |
| 2020-07-01 | Jul 2020 | 116817.92 | -26.3 |
| 2020-08-01 | Aug 2020 | 109977.6 | -30.6 |
| 2020-09-01 | Sep 2020 | 101990.4 | -35.6 |
| 2020-10-01 | Oct 2020 | 108666.88 | -31.4 |
| 2020-11-01 | Nov 2020 | 70369.28 | -55.6 |
| 2020-12-01 | Dec 2020 | 68771.84 | -56.6 |
| 2021-01-01 | Jan 2021 | 86343.68 | -45.5 |
| 2021-02-01 | Feb 2021 | 65658.88 | -58.6 |
| 2021-03-01 | Mar 2021 | 46694.4 | -70.5 |
| 2021-04-01 | Apr 2021 | 10280.96 | -93.5 |
| 2021-05-01 | May 2021 | 8883.2 | -94.4 |
| 2021-06-01 | Jun 2021 | 7541.76 | -95.2 |
| 2021-07-01 | Jul 2021 | 7733.76 | -95.1 |
| 2021-08-01 | Aug 2021 | 6525.44 | -95.9 |
| 2021-09-01 | Sep 2021 | 7124.48 | -95.5 |
| 2021-10-01 | Oct 2021 | 5488.64 | -96.5 |
| 2021-11-01 | Nov 2021 | 6517.76 | -95.9 |
| 2021-12-01 | Dec 2021 | 4743.68 | -97 |
| 2022-01-01 | Jan 2022 | 5480.96 | -96.5 |
| 2022-02-01 | Feb 2022 | 6144 | -96.1 |
| 2022-03-01 | Mar 2022 | 6579.2 | -95.8 |
| 2022-04-01 | Apr 2022 | 7093.76 | -95.5 |
| 2022-05-01 | May 2022 | 5775.36 | -96.4 |
| 2022-06-01 | Jun 2022 | 5908.48 | -96.3 |
| 2022-07-01 | Jul 2022 | 5360.64 | -96.6 |
| 2022-08-01 | Aug 2022 | 4925.44 | -96.9 |
| 2022-09-01 | Sep 2022 | 5429.76 | -96.6 |
| 2022-10-01 | Oct 2022 | 4520.96 | -97.1 |
| 2022-11-01 | Nov 2022 | 3819.52 | -97.6 |
| 2022-12-01 | Dec 2022 | 3614.72 | -97.7 |
| 2023-01-01 | Jan 2023 | 2897.92 | -98.2 |
| 2023-02-01 | Feb 2023 | 2954.24 | -98.1 |
| 2023-03-01 | Mar 2023 | 718.56 | -99.5 |
| 2023-04-01 | Apr 2023 | 605.76 | -99.6 |
| 2023-05-01 | May 2023 | 551.36 | -99.7 |
| 2023-06-01 | Jun 2023 | 400 | -99.7 |
| 2023-07-01 | Jul 2023 | 361.6 | -99.8 |
| 2023-08-01 | Aug 2023 | 344 | -99.8 |
| 2023-09-01 | Sep 2023 | 373.12 | -99.8 |
| 2023-10-01 | Oct 2023 | 375.2 | -99.8 |
| 2023-11-01 | Nov 2023 | 276.64 | -99.8 |
| 2023-12-01 | Dec 2023 | 248.32 | -99.8 |
| 2024-01-01 | Jan 2024 | 242.08 | -99.8 |
| 2024-02-01 | Feb 2024 | 216.96 | -99.9 |
| 2024-03-01 | Mar 2024 | 207.52 | -99.9 |
| 2024-04-01 | Apr 2024 | 217.76 | -99.9 |
| 2024-05-01 | May 2024 | 184.48 | -99.9 |
| 2024-06-01 | Jun 2024 | 174.72 | -99.9 |
| 2024-07-01 | Jul 2024 | 46.25 | -100 |
| 2024-08-01 | Aug 2024 | 44.5 | -100 |
| 2024-09-01 | Sep 2024 | 49.6 | -100 |
| 2024-10-01 | Oct 2024 | 57.87 | -100 |
| 2024-11-01 | Nov 2024 | 42.58 | -100 |
| 2024-12-01 | Dec 2024 | 45.8 | -100 |
| 2025-01-01 | Jan 2025 | 44.12 | -100 |
| 2025-02-01 | Feb 2025 | 45.83 | -100 |
| 2025-03-01 | Mar 2025 | 51.47 | -100 |
| 2025-04-01 | Apr 2025 | 64.64 | -100 |
| 2025-05-01 | May 2025 | 53.83 | -100 |
| 2025-06-01 | Jun 2025 | 48.05 | -100 |
| 2025-07-01 | Jul 2025 | 42.46 | -100 |
| 2025-08-01 | Aug 2025 | 36.27 | -100 |
| 2025-09-01 | Sep 2025 | 33.16 | -100 |
| 2025-10-01 | Oct 2025 | 34 | -100 |
| 2025-11-01 | Nov 2025 | 32.1 | -100 |
| 2025-12-01 | Dec 2025 | 26.47 | -100 |
| 2026-01-01 | Jan 2026 | 27.5 | -100 |
| 2026-02-01 | Feb 2026 | 28.9 | -100 |
| 2026-03-01 | Mar 2026 | 35.7 | -100 |
| 2026-04-01 | Apr 2026 | 28.19 | -100 |
| 2026-05-01 | May 2026 | 24.14 | -100 |
| 2026-06-01 | Jun 2026 | 22.09 | -100 |
| 2026-07-01 | Jul 2026 | 21.25 | -100 |
| 2026-08-01 | Aug 2026 | 18 | -100 |
| 2026-09-01 | Sep 2026 | 17.51 | -100 |
- Rows × columns
- 90 × 4
- Period covered
- to
- Computed
- Completeness
- No missing values
- Source
- US exchange, SIP and OPRA market data
- Licence
- Strasmore terms · free, no signup
What each column holds
| Column | Type | Range | Notes |
|---|---|---|---|
month |
date | 2019-01-01 to 2026-09-01 | |
month_label |
text | 90 distinct values (Apr 2020, Apr 2021, Apr 2022…) | |
vxx_close_adj |
number | 17.51 to 189,440 | US dollars |
change_pct |
number | -100 to 19.5 | percent |
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 splits AS
(
SELECT
groupArray(execution_date) AS split_dates,
groupArray(price_factor) AS price_factors
FROM
(
SELECT
execution_date,
toFloat64(any(split_from)) / toFloat64(any(split_to)) AS price_factor
FROM global_markets.stocks_splits
WHERE ticker = 'VXX'
GROUP BY execution_date
)
),
daily AS
(
SELECT
a.date AS date,
toFloat64(a.close) * arrayProduct(arrayMap((d, f) -> if(d > a.date, f, 1.0), s.split_dates, s.price_factors)) AS adj_close
FROM global_markets.stocks_daily_aggs AS a
CROSS JOIN splits AS s
WHERE a.ticker = 'VXX'
AND a.date >= toDate('2019-01-01')
),
month_end AS
(
SELECT
toStartOfMonth(date) AS month_start,
argMax(adj_close, date) AS adj_close
FROM daily
GROUP BY month_start
)
SELECT
toString(month_start) AS month,
formatDateTime(month_start, '%b %Y') AS month_label,
round(adj_close, 2) AS vxx_close_adj,
round(100 * (adj_close / first_value(adj_close) OVER (ORDER BY month_start) - 1), 1) AS change_pct
FROM month_end
ORDER BY month_start