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 2026-09-28, from COVID Crash 2020: Four Halts, Peak to Trough.
- 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
What each column holds
| Column | Type | Range | Notes |
|---|---|---|---|
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.
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 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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