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Largest month-over-month declines in SPY month-end closes

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 2026-08-22, from FINRA Margin Debt Statistics, Explained.

as of ranking 10×2read in context →
Largest month-over-month declines in SPY month-end closes — 10 rows by 2 columns, computed from US exchange, SIP and OPRA data.
calendar_labelspy_change_pct
Oct 2008-16.74
Mar 2020-12.99
Feb 2009-10.53
Sep 2022-9.6
Sep 2008-9.32
Dec 2018-9.3
Apr 2022-8.77
Jun 2008-8.77
Jun 2022-8.63
Jan 2009-8.4
Rows × columns
10 × 2
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 Largest month-over-month declines in SPY month-end closes, derived from the stored result.
ColumnTypeRangeNotes
calendar_label text 10 distinct values (Apr 2022, Dec 2018, Feb 2009…)
spy_change_pct number -16.74 to -8.4 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 daily AS
(
    SELECT
        toDate(toTimeZone(window_start, 'America/New_York')) AS d,
        argMax(close, window_start)                          AS px
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= toDateTime('2006-01-01 00:00:00')
      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
           + toMinute(toTimeZone(window_start, 'America/New_York'))) >= 570
      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
           + toMinute(toTimeZone(window_start, 'America/New_York'))) < 960
    GROUP BY d
),
month_close AS
(
    SELECT
        toStartOfMonth(d)        AS m,
        toFloat64(argMax(px, d)) AS close_px
    FROM daily
    GROUP BY m
),
chained AS
(
    SELECT
        m,
        close_px,
        lagInFrame(close_px, 1) OVER (ORDER BY m ASC
            ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) AS prior_close
    FROM month_close
)
SELECT
    formatDateTime(m, '%b %Y')                   AS calendar_label,
    round(100 * (close_px / prior_close - 1), 2) AS spy_change_pct
FROM chained
WHERE prior_close > 0
ORDER BY spy_change_pct ASC
LIMIT 10

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