STRASMORE/EXPLORE 3,256 QUERIES

March 24, 2020 across index and sector ETFs: everything up, cyclicals first

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 2026-09-28, from March 24, 2020: The Day the Market Turned.

as of ranking 12×4read in context →
March 24, 2020 across index and sector ETFs: everything up, cyclicals first — 12 rows by 4 columns, computed from US exchange, SIP and OPRA data.
tickermar23_closemar24_closechange_pct
XLE23.5327.3916.4
XLI48.7554.9712.8
XLF17.6219.8512.7
DIA185.87206.9611.3
XLU44.9249.7610.8
XLK70.277.6410.6
XLY87.4295.779.6
SPY222.51243.599.5
IWM99.83109.179.4
QQQ170.61183.797.7
XLV74.880.317.4
XLP48.6651.125.1
Rows × columns
12 × 4
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 March 24, 2020 across index and sector ETFs: everything up, cyclicals first, derived from the stored result.
ColumnTypeRangeNotes
ticker text 12 distinct values (DIA, IWM, QQQ…)
mar23_close number 17.62 to 222.51 US dollars
mar24_close number 19.85 to 243.59 US dollars
change_pct number 5.1 to 16.4 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.

SELECT
    ticker,
    round(argMaxIf(toFloat64(close), window_start, (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959 AND toDate(toTimeZone(window_start, 'America/New_York')) = toDate('2020-03-23')), 2) AS mar23_close,
    round(argMaxIf(toFloat64(close), window_start, (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959 AND toDate(toTimeZone(window_start, 'America/New_York')) = toDate('2020-03-24')), 2) AS mar24_close,
    round((argMaxIf(toFloat64(close), window_start, (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959 AND toDate(toTimeZone(window_start, 'America/New_York')) = toDate('2020-03-24')) / argMaxIf(toFloat64(close), window_start, (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959 AND toDate(toTimeZone(window_start, 'America/New_York')) = toDate('2020-03-23')) - 1) * 100, 1) AS change_pct
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('SPY', 'DIA', 'QQQ', 'IWM', 'XLE', 'XLI', 'XLF', 'XLK', 'XLY', 'XLV', 'XLU', 'XLP')
  AND window_start >= toDateTime('2020-03-23 00:00:00') AND window_start < toDateTime('2020-03-25 00:00:00')
GROUP BY ticker
ORDER BY change_pct DESC
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More from this analysisMarch 24, 2020: The Day the Market Turned
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