STRASMORE/EXPLORE 2,170 QUERIES

The COVID crash, peak to trough to recovery: SPY daily closes, one row

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 2026-07-26, from COVID Crash 2020: Four Halts, Peak to Trough.

as of scalar 1×11read in context →
peak date
2020-02-19
peak close
338.31
trough date
2020-03-23
trough close
222.51
decline pct
-34.2
sessions peak to trough
23
calendar days
33
sessions to minus 30
22
gfc 2008 sessions to minus 30
250
recovery date
2020-08-18
sessions trough to recovery
103
Rows × columns
1 × 11
Period covered
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 COVID crash, peak to trough to recovery: SPY daily closes, one row, derived from the stored result.
ColumnTypeRangeNotes
peak_date date 2020-02-19
peak_close number every row is 338.31 US dollars
trough_date date 2020-03-23
trough_close number every row is 222.51 US dollars
decline_pct number every row is -34.2 percent
sessions_peak_to_trough number every row is 23
calendar_days number every row is 33
sessions_to_minus_30 number every row is 22
gfc_2008_sessions_to_minus_30 number every row is 250
recovery_date date 2020-08-18
sessions_trough_to_recovery number every row is 103

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 dailies AS (
    SELECT
        toDate(toTimeZone(window_start, 'America/New_York')) AS d,
        argMaxIf(toFloat64(close), window_start, (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959) AS c
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= toDateTime('2020-02-01 00:00:00') AND window_start < toDateTime('2020-09-01 00:00:00')
    GROUP BY d
),
peak AS (SELECT argMax(d, (c, -toInt32(d))) AS pd, max(c) AS pc FROM dailies WHERE d < toDate('2020-03-01')),
trough AS (SELECT argMin(d, (c, toInt32(d))) AS td, min(c) AS tc FROM dailies WHERE d < toDate('2020-04-01')),
gfc AS (
    SELECT
        toDate(toTimeZone(window_start, 'America/New_York')) AS d,
        argMaxIf(toFloat64(close), window_start, (toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959) AS c
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= toDateTime('2007-06-01 00:00:00') AND window_start < toDateTime('2009-01-01 00:00:00')
    GROUP BY d
),
gpeak AS (SELECT argMax(d, (c, -toInt32(d))) AS pd, max(c) AS pc FROM gfc WHERE d < toDate('2008-01-01'))
SELECT
    toString((SELECT pd FROM peak)) AS peak_date,
    round((SELECT pc FROM peak), 2) AS peak_close,
    toString((SELECT td FROM trough)) AS trough_date,
    round((SELECT tc FROM trough), 2) AS trough_close,
    round(((SELECT tc FROM trough) / (SELECT pc FROM peak) - 1) * 100, 1) AS decline_pct,
    countIf(d > (SELECT pd FROM peak) AND d <= (SELECT td FROM trough)) AS sessions_peak_to_trough,
    dateDiff('day', (SELECT pd FROM peak), (SELECT td FROM trough)) AS calendar_days,
    countIf(d > (SELECT pd FROM peak) AND d <= (SELECT min(d) FROM dailies WHERE c <= 0.7 * (SELECT pc FROM peak))) AS sessions_to_minus_30,
    (SELECT countIf(d > (SELECT pd FROM gpeak) AND d <= (SELECT min(d) FROM gfc WHERE c <= 0.7 * (SELECT pc FROM gpeak))) FROM gfc) AS gfc_2008_sessions_to_minus_30,
    toString((SELECT min(d) FROM dailies WHERE d > (SELECT td FROM trough) AND c >= (SELECT pc FROM peak))) AS recovery_date,
    countIf(d > (SELECT td FROM trough) AND d <= (SELECT min(d) FROM dailies WHERE d > (SELECT td FROM trough) AND c >= (SELECT pc FROM peak))) AS sessions_trough_to_recovery
FROM dailies

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More from this analysisCOVID Crash 2020: Four Halts, Peak to Trough
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