The S&P 500's underwater record since 2016 (SPY, one scorecard)
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.
- Rows × columns
- 1 × 6
- 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 |
|---|---|---|---|
deepest_fall_pct |
number | every row is 34.2 | percent |
current_fall_pct |
number | every row is 0.6 | percent |
pct_days_below_high |
number | every row is 70 | percent |
pct_days_below_5 |
number | every row is 32 | percent |
pct_days_below_10 |
number | every row is 16 | percent |
trading_days |
number | every row is 2,647 |
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 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) - 1) * 100 AS ddpct
FROM d
)
SELECT round(-min(ddpct), 1) AS deepest_fall_pct,
round(-argMax(ddpct, dt), 1) AS current_fall_pct,
round(100.0 * countIf(ddpct < -0.5) / count(), 0) AS pct_days_below_high,
round(100.0 * countIf(ddpct < -5) / count(), 0) AS pct_days_below_5,
round(100.0 * countIf(ddpct < -10) / count(), 0) AS pct_days_below_10,
count() AS trading_days
FROM dd
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