STRASMORE/EXPLORE 3,094 QUERIES

Calendar days spanned by each rolling five-session window

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 2026-10-05, from Does the PDT Rule Apply to Crypto and Futures?.

as of series 78×3read in context →
Calendar days spanned by each rolling five-session window — 78 rows by 3 columns, computed from US exchange, SIP and OPRA data.
session_datecalendar_days_spannedlongest_span_days
2026-06-1258
2026-06-1578
2026-06-1678
2026-06-1778
2026-06-1878
2026-06-2288
2026-06-2388
2026-06-2488
2026-06-2588
2026-06-2658
2026-06-2978
2026-06-3078
2026-07-0178
2026-07-0278
2026-07-0688
2026-07-0788
2026-07-0888
2026-07-0988
2026-07-1058
2026-07-1378
2026-07-1478
2026-07-1578
2026-07-1678
2026-07-1758
2026-07-2078
2026-07-2178
2026-07-2278
2026-07-2378
2026-07-2458
2026-07-2778
2026-07-2878
2026-07-2978
2026-07-3078
2026-07-3158
2026-08-0378
2026-08-0478
2026-08-0578
2026-08-0678
2026-08-0758
2026-08-1078
2026-08-1178
2026-08-1278
2026-08-1378
2026-08-1458
2026-08-1778
2026-08-1878
2026-08-1978
2026-08-2078
2026-08-2158
2026-08-2478
2026-08-2578
2026-08-2678
2026-08-2778
2026-08-2858
2026-08-3178
2026-09-0178
2026-09-0278
2026-09-0378
2026-09-0458
2026-09-0888
2026-09-0988
2026-09-1088
2026-09-1188
2026-09-1478
2026-09-1578
2026-09-1678
2026-09-1778
2026-09-1858
2026-09-2178
2026-09-2278
2026-09-2378
2026-09-2478
2026-09-2558
2026-09-2878
2026-09-2978
2026-09-3078
2026-10-0178
2026-10-0258
Rows × columns
78 × 3
Period covered
to
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 Calendar days spanned by each rolling five-session window, derived from the stored result.
ColumnTypeRangeNotes
session_date date 2026-06-12 to 2026-10-02
calendar_days_spanned number 5 to 8
longest_span_days number every row is 8

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
    sessions AS
    (
        SELECT DISTINCT toDate(toTimeZone(window_start, 'America/New_York')) AS d
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'SPY'
          AND window_start >= today() - 120
          AND window_start <  today() - 2
          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
    ),
    spans AS
    (
        SELECT
            d,
            dateDiff('day', min(d) OVER (ORDER BY d ASC ROWS BETWEEN 4 PRECEDING AND CURRENT ROW), d) + 1 AS span_days,
            count()   OVER (ORDER BY d ASC ROWS BETWEEN 4 PRECEDING AND CURRENT ROW)                    AS sessions_in_window
        FROM sessions
    )
SELECT
    toString(d)                              AS session_date,
    toUInt16(span_days)                      AS calendar_days_spanned,
    toUInt16(max(span_days) OVER ())         AS longest_span_days
FROM spans
WHERE sessions_in_window = 5
ORDER BY d ASC
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