STRASMORE/EXPLORE 3,094 QUERIES

mah_be_mah

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 us-stock-market-hours-tehran-time.

as of series 14×5read in context →
mah_be_mah — 14 rows by 5 columns, computed from US exchange, SIP and OPRA data.
monthmonth_labelopen_tehranclose_tehrantehran_lead
2025-09-012025/0917:0023:307.5
2025-10-012025/1017:0023:307.5
2025-11-012025/1118:0000:308.5
2025-12-012025/1218:0000:308.5
2026-01-012026/0118:0000:308.5
2026-02-012026/0218:0000:308.5
2026-03-012026/0317:0023:307.5
2026-04-012026/0417:0023:307.5
2026-05-012026/0517:0023:307.5
2026-06-012026/0617:0023:307.5
2026-07-012026/0717:0023:307.5
2026-08-012026/0817:0023:307.5
2026-09-012026/0917:0023:307.5
2026-10-012026/1017:0023:307.5
Rows × columns
14 × 5
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 mah_be_mah, derived from the stored result.
ColumnTypeRangeNotes
month date 2025-09-01 to 2026-10-01
month_label text 14 distinct values (2025/09, 2025/10, 2025/11…)
open_tehran text 2 distinct values (17:00, 18:00)
close_tehran text 2 distinct values (00:30, 23:30)
tehran_lead number 7.5 to 8.5

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
    month,
    month_label,
    argMax(tehran_open,  sessions) AS open_tehran,
    argMax(tehran_close, sessions) AS close_tehran,
    argMax(tehran_lead,  sessions) AS tehran_lead
FROM
(
    SELECT
        toString(toStartOfMonth(session_date))                      AS month,
        formatDateTime(toStartOfMonth(session_date), '%Y/%m')       AS month_label,
        tehran_open,
        tehran_close,
        tehran_lead,
        count()                                                     AS sessions
    FROM
    (
        SELECT
            toDate(toTimeZone(window_start, 'America/New_York'))                                     AS session_date,
            formatDateTime(toTimeZone(min(window_start), 'Asia/Tehran'), '%H:%i')                    AS tehran_open,
            formatDateTime(toTimeZone(max(window_start) + INTERVAL 1 MINUTE, 'Asia/Tehran'), '%H:%i') AS tehran_close,
            round((
                  (toHour(toTimeZone(min(window_start), 'Asia/Tehran')) * 60
                 + toMinute(toTimeZone(min(window_start), 'Asia/Tehran')))
                - (toHour(toTimeZone(min(window_start), 'America/New_York')) * 60
                 + toMinute(toTimeZone(min(window_start), 'America/New_York')))
            ) / 60, 1)                                                                               AS tehran_lead
        FROM global_markets.delayed_stocks_minute_aggs
        WHERE ticker = 'SPY'
          AND window_start >= today() - 400
          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
        GROUP BY session_date
        HAVING countDistinct(window_start) = 390
    )
    GROUP BY month, month_label, tehran_open, tehran_close, tehran_lead
)
GROUP BY month, month_label
ORDER BY month
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