STRASMORE/EXPLORE 2,272 QUERIES

Same session, same 10-session lookback: same-time basis vs full-day basis through the day

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 2026-09-16, from Why Relative Volume Differs Between Platforms.

as of series 14×3read in context →
Same session, same 10-session lookback: same-time basis vs full-day basis through the day — 14 rows by 3 columns, computed from US exchange, SIP and OPRA data.
et_timesame_time_basis_ratiofull_day_basis_ratio
09:453.10.26
10:002.480.35
10:301.920.46
11:001.880.6
11:301.880.74
12:002.020.92
12:302.011.04
13:002.161.21
13:302.121.3
14:002.161.43
14:302.091.51
15:0021.59
15:301.981.69
16:001.871.87
Rows × columns
14 × 3
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 Same session, same 10-session lookback: same-time basis vs full-day basis through the day, derived from the stored result.
ColumnTypeRangeNotes
et_time text 14 distinct values (09:45, 10:00, 10:30…)
same_time_basis_ratio number 1.87 to 3.1 ratio or rate
full_day_basis_ratio number 0.26 to 1.87 ratio or rate

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
    toDate('2026-09-10') AS session_day,
    [585, 600, 630, 660, 690, 720, 750, 780, 810, 840, 870, 900, 930, 960] AS checkpoints
SELECT
    formatDateTime(toDateTime(session_day, 'UTC') + checkpoints[i] * 60, '%H:%i', 'UTC') AS et_time,
    round(session_cums[i] / typical_cums[i], 2)                                            AS same_time_basis_ratio,
    round(session_cums[i] / typical_cums[14], 2)                                           AS full_day_basis_ratio
FROM
(
    SELECT
        arrayJoin(arrayEnumerate(checkpoints)) AS i,
        session_cums,
        arrayMap(k -> arrayAvg(x -> arrayElement(tupleElement(x, 2), k), arraySlice(prior, 1, 10)),
                 arrayEnumerate(checkpoints)) AS typical_cums
    FROM
    (
        SELECT
            anyIf(cums, d = session_day)                                                        AS session_cums,
            arrayReverseSort(x -> tupleElement(x, 1), groupArrayIf((d, cums), d < session_day)) AS prior
        FROM
        (
            SELECT
                d,
                arrayMap(cp -> arraySum(x -> if(tupleElement(x, 1) <= cp, tupleElement(x, 2), 0), mv),
                         checkpoints) AS cums
            FROM
            (
                SELECT d, groupArray((minute_of_day, vol)) AS mv
                FROM
                (
                    SELECT
                        toDate(toTimeZone(window_start, 'America/New_York'))      AS d,
                        toHour(toTimeZone(window_start, 'America/New_York')) * 60
                          + toMinute(toTimeZone(window_start, 'America/New_York')) AS minute_of_day,
                        max(toFloat64(volume))                                     AS vol
                    FROM global_markets.delayed_stocks_minute_aggs
                    WHERE ticker = 'AAPL'
                      AND window_start >= toDateTime(session_day - 20, 'America/New_York')
                      AND window_start <  toDateTime(session_day + 1, 'America/New_York')
                    GROUP BY d, minute_of_day
                    HAVING minute_of_day >= 570 AND minute_of_day <= 960
                )
                GROUP BY d
            )
        )
        HAVING length(session_cums) = 14 AND length(prior) >= 10
    )
)
ORDER BY i

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More from this analysisWhy Relative Volume Differs Between Platforms
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