The S&P 500's underwater curve: worst drawdown from a prior high, by month
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 2026-07-16, from How Markets Recover From Crashes.
| month | worst_drawdown_pct |
|---|---|
| 2016-01-01 | -7.8 |
| 2016-02-01 | -9.1 |
| 2016-03-01 | -1.6 |
| 2016-04-01 | -1.8 |
| 2016-05-01 | -2.8 |
| 2016-06-01 | -6 |
| 2016-07-01 | -1.8 |
| 2016-08-01 | -0.9 |
| 2016-09-01 | -2.7 |
| 2016-10-01 | -3.1 |
| 2016-11-01 | -4.8 |
| 2016-12-01 | -1.8 |
| 2017-01-01 | -1.1 |
| 2017-02-01 | -0.8 |
| 2017-03-01 | -2.6 |
| 2017-04-01 | -3 |
| 2017-05-01 | -1.8 |
| 2017-06-01 | -1.3 |
| 2017-07-01 | -1.7 |
| 2017-08-01 | -2.1 |
| 2017-09-01 | -0.7 |
| 2017-10-01 | -0.7 |
| 2017-11-01 | -1 |
| 2017-12-01 | -0.6 |
| 2018-01-01 | -1.7 |
| 2018-02-01 | -10.1 |
| 2018-03-01 | -10 |
| 2018-04-01 | -10.1 |
| 2018-05-01 | -8.4 |
| 2018-06-01 | -6 |
| 2018-07-01 | -5.5 |
| 2018-08-01 | -2 |
| 2018-09-01 | -1.3 |
| 2018-10-01 | -10.1 |
| 2018-11-01 | -10.3 |
| 2018-12-01 | -20.2 |
| 2019-01-01 | -16.8 |
| 2019-02-01 | -8 |
| 2019-03-01 | -6.5 |
| 2019-04-01 | -2.6 |
| 2019-05-01 | -6.3 |
| 2019-06-01 | -6.6 |
| 2019-07-01 | -1.5 |
| 2019-08-01 | -6 |
| 2019-09-01 | -3.7 |
| 2019-10-01 | -4.6 |
| 2019-11-01 | -0.5 |
| 2019-12-01 | -1.9 |
| 2020-01-01 | -3.1 |
| 2020-02-01 | -12.5 |
| 2020-03-01 | -34.2 |
| 2020-04-01 | -27.3 |
| 2020-05-01 | -16.7 |
| 2020-06-01 | -11.3 |
| 2020-07-01 | -8.2 |
| 2020-08-01 | -2.8 |
| 2020-09-01 | -9.8 |
| 2020-10-01 | -8.7 |
| 2020-11-01 | -7.7 |
| 2020-12-01 | -1.5 |
| 2021-01-01 | -3.7 |
| 2021-02-01 | -3.2 |
| 2021-03-01 | -4.1 |
| 2021-04-01 | -1.2 |
| 2021-05-01 | -3.9 |
| 2021-06-01 | -2.4 |
| 2021-07-01 | -2.8 |
| 2021-08-01 | -1.7 |
| 2021-09-01 | -5.3 |
| 2021-10-01 | -5.4 |
| 2021-11-01 | -3 |
| 2021-12-01 | -4.1 |
| 2022-01-01 | -9.7 |
| 2022-02-01 | -11.7 |
| 2022-03-01 | -12.9 |
| 2022-04-01 | -13.8 |
| 2022-05-01 | -18.5 |
| 2022-06-01 | -23.4 |
| 2022-07-01 | -20.9 |
| 2022-08-01 | -17.3 |
| 2022-09-01 | -25.2 |
| 2022-10-01 | -25.4 |
| 2022-11-01 | -22.3 |
| 2022-12-01 | -21.2 |
| 2023-01-01 | -20.6 |
| 2023-02-01 | -17.1 |
| 2023-03-01 | -19.4 |
| 2023-04-01 | -15.4 |
| 2023-05-01 | -15.2 |
| 2023-06-01 | -11.7 |
| 2023-07-01 | -8.2 |
| 2023-08-01 | -8.7 |
| 2023-09-01 | -10.9 |
| 2023-10-01 | -14 |
| 2023-11-01 | -11.5 |
| 2023-12-01 | -4.8 |
| 2024-01-01 | -2.2 |
| 2024-02-01 | -1.4 |
| 2024-03-01 | -1.4 |
| 2024-04-01 | -5.4 |
| 2024-05-01 | -4.4 |
| 2024-06-01 | -1.1 |
| 2024-07-01 | -4.7 |
| 2024-08-01 | -8.4 |
| 2024-09-01 | -4.3 |
| 2024-10-01 | -2.7 |
| 2024-11-01 | -2.5 |
| 2024-12-01 | -3.6 |
| 2025-01-01 | -4.5 |
| 2025-02-01 | -4.5 |
| 2025-03-01 | -10 |
| 2025-04-01 | -19 |
| 2025-05-01 | -8.9 |
| 2025-06-01 | -3.3 |
| 2025-07-01 | -0.8 |
| 2025-08-01 | -2.4 |
| 2025-09-01 | -1.3 |
| 2025-10-01 | -3 |
| 2025-11-01 | -5.1 |
| 2025-12-01 | -2.6 |
| 2026-01-01 | -2.5 |
| 2026-02-01 | -2.6 |
| 2026-03-01 | -9.1 |
| 2026-04-01 | -5.8 |
| 2026-05-01 | -1.9 |
| 2026-06-01 | -4.5 |
| 2026-07-01 | -1.9 |
- Rows × columns
- 127 × 2
- 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 | 2016-01-01 to 2026-07-01 | |
worst_drawdown_pct |
number | -34.2 to -0.5 | 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.
the exact SQL behind every number
WITH d AS (
SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS dt,
argMax(toFloat64(close), toTimeZone(window_start, 'America/New_York')) AS c
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY' AND window_start >= '2016-01-01'
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
+ toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
GROUP BY dt
),
dd AS (
SELECT dt, c,
max(c) OVER (ORDER BY dt ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS peak
FROM d
)
SELECT toStartOfMonth(dt) AS month, round(min((c / peak - 1) * 100), 1) AS worst_drawdown_pct
FROM dd GROUP BY month ORDER BY month
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