STRASMORE/EXPLORE 3,256 QUERIES

Does a Monday move like three calendar days? SPY by weekday

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 2026-10-04, from The Rule of 16 in Options, and When It Breaks.

as of ranking 5×4read in context →
Does a Monday move like three calendar days? SPY by weekday — 5 rows by 4 columns, computed from US exchange, SIP and OPRA data.
labelsigma_pctvs_all_days_ratiosessions
Mon0.8220.87142
Tue0.7690.81157
Wed1.1771.24154
Thu0.981.03149
Fri0.9941.05151
Rows × columns
5 × 4
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 Does a Monday move like three calendar days? SPY by weekday, derived from the stored result.
ColumnTypeRangeNotes
label text 5 distinct values (Fri, Mon, Thu…)
sigma_pct number 0.769 to 1.177 percent
vs_all_days_ratio number 0.81 to 1.24 ratio or rate
sessions number 142 to 157

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.

SELECT
    label,
    round(sigma * 100, 3)                AS sigma_pct,
    round(sigma / avg(sigma) OVER (), 2) AS vs_all_days_ratio,
    sessions
FROM
(
    SELECT
        formatDateTime(session_date, '%a') AS label,
        min(toDayOfWeek(session_date))     AS dow,
        stddevPop(daily_return)            AS sigma,
        count()                            AS sessions
    FROM
    (
        SELECT
            session_date,
            close_px / lagInFrame(close_px) OVER (ORDER BY session_date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) - 1 AS daily_return
        FROM
        (
            SELECT
                date                  AS session_date,
                toFloat64(max(close)) AS close_px
            FROM global_markets.stocks_daily_aggs
            WHERE ticker = 'SPY'
              AND date >= today() - 1100
              AND date <  today() - 1
            GROUP BY session_date
        )
    )
    WHERE isFinite(daily_return)
    GROUP BY label
)
ORDER BY dow
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