Completed SPY drawdowns since 2016: depth, days falling, days climbing back
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 2026-08-05, from What Is Maximum Drawdown? Depth vs Recovery.
| episode_label | fall_from_peak_pct | days_to_trough | days_to_new_high | days_underwater |
|---|---|---|---|---|
| Feb 2020 | 34.2 | 33 | 148 | 181 |
| Jan 2022 | 25.4 | 282 | 464 | 746 |
| Sep 2018 | 20.2 | 95 | 126 | 221 |
| Feb 2025 | 19 | 48 | 80 | 128 |
| Jan 2018 | 10.1 | 66 | 144 | 210 |
| Sep 2020 | 9.8 | 21 | 51 | 72 |
| Jan 2026 | 9.1 | 62 | 16 | 78 |
| Jan 2016 | 9.1 | 37 | 29 | 66 |
- Rows × columns
- 8 × 5
- 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 |
|---|---|---|---|
episode_label |
text | 8 distinct values (Feb 2020, Feb 2025, Jan 2016…) | |
fall_from_peak_pct |
number | 9.1 to 34.2 | percent |
days_to_trough |
number | 21 to 282 | |
days_to_new_high |
number | 16 to 464 | US dollars |
days_underwater |
number | 66 to 746 |
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 daily AS (
SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS session_date,
argMax(toFloat64(close), window_start) AS close_px
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY'
AND toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2016-01-01')
AND toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-07-31')
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
+ toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
GROUP BY session_date
),
runs AS (
SELECT session_date,
close_px,
max(close_px) OVER (ORDER BY session_date
ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS running_peak
FROM daily
),
episodes AS (
SELECT running_peak AS peak_px,
min(session_date) AS peak_date,
argMin(session_date, close_px) AS trough_date,
min(close_px) AS trough_px
FROM runs
GROUP BY running_peak
),
sequenced AS (
SELECT peak_px,
peak_date,
trough_date,
trough_px,
leadInFrame(peak_date, 1) OVER (ORDER BY peak_date
ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING) AS recovery_date
FROM episodes
)
SELECT formatDateTime(peak_date, '%b %Y') AS episode_label,
round(100 * (1 - trough_px / peak_px), 1) AS fall_from_peak_pct,
dateDiff('day', peak_date, trough_date) AS days_to_trough,
dateDiff('day', trough_date, recovery_date) AS days_to_new_high,
dateDiff('day', peak_date, recovery_date) AS days_underwater
FROM sequenced
WHERE recovery_date > trough_date
AND round(100 * (1 - trough_px / peak_px), 1) >= 5
ORDER BY fall_from_peak_pct DESC
LIMIT 8
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