sessoes_estendidas

Name: sessoes_estendidas
Creator: Strasmore
Published: 2026-10-04
License: https://www.strasmore.com/terms/

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 us-market-volume-by-hour-brasilia-time.

as of 2026-10-04 ranking 3×4read in context →

sessoes_estendidas — 3 rows by 4 columns, computed 2026-10-04 from US exchange, SIP and OPRA data.
segmento	janela_brasilia	pct_do_volume_diario	volume_medio_milhoes
Pre-market	05h00 as 10h29	2.97	6.5
Sessao regular	10h30 as 17h00	92.18	201
After-hours	17h01 as 21h00	4.85	10.6

Rows × columns: 3 × 4
Computed: 2026-10-04
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 sessoes_estendidas, derived from the stored result.
Column	Type	Range	Notes
`segmento`	text	3 distinct values (After-hours, Pre-market, Sessao regular)
`janela_brasilia`	text	3 distinct values
`pct_do_volume_diario`	number	2.97 to 92.18	percent
`volume_medio_milhoes`	number	6.5 to 201	count

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 2026-10-04, 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 brutas AS
(
    SELECT
        toHour(toTimeZone(window_start, 'America/New_York')) * 60
            + toMinute(toTimeZone(window_start, 'America/New_York')) AS minuto_et,
        toDate(toTimeZone(window_start, 'America/New_York'))         AS sessao,
        volume
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('SPY', 'AAPL', 'MSFT', 'NVDA', 'KO')
      AND window_start >= '2026-07-01 08:00:00'
      AND window_start <  '2026-10-01 08:00:00'
),
dia AS
(
    SELECT *
    FROM brutas
    WHERE minuto_et >= 240 AND minuto_et <= 1200
)
SELECT
    multiIf(minuto_et < 570, 'Pre-market',
            minuto_et <= 960, 'Sessao regular',
                              'After-hours')                        AS segmento,
    multiIf(minuto_et < 570, '05h00 as 10h29',
            minuto_et <= 960, '10h30 as 17h00',
                              '17h01 as 21h00')                     AS janela_brasilia,
    round(toFloat64(sum(volume)) * 100
          / toFloat64((SELECT sum(volume) FROM dia)), 2)             AS pct_do_volume_diario,
    round(toFloat64(sum(volume)) / countDistinct(sessao) / 1e6, 1)   AS volume_medio_milhoes
FROM dia
GROUP BY segmento, janela_brasilia
ORDER BY min(minuto_et)

SQL to run

WITH brutas AS
(
    SELECT
        toHour(toTimeZone(window_start, 'America/New_York')) * 60
            + toMinute(toTimeZone(window_start, 'America/New_York')) AS minuto_et,
        toDate(toTimeZone(window_start, 'America/New_York'))         AS sessao,
        volume
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('SPY', 'AAPL', 'MSFT', 'NVDA', 'KO')
      AND window_start >= '2026-07-01 08:00:00'
      AND window_start <  '2026-10-01 08:00:00'
),
dia AS
(
    SELECT *
    FROM brutas
    WHERE minuto_et >= 240 AND minuto_et <= 1200
)
SELECT
    multiIf(minuto_et < 570, 'Pre-market',
            minuto_et <= 960, 'Sessao regular',
                              'After-hours')                        AS segmento,
    multiIf(minuto_et < 570, '05h00 as 10h29',
            minuto_et <= 960, '10h30 as 17h00',
                              '17h01 as 21h00')                     AS janela_brasilia,
    round(toFloat64(sum(volume)) * 100
          / toFloat64((SELECT sum(volume) FROM dia)), 2)             AS pct_do_volume_diario,
    round(toFloat64(sum(volume)) / countDistinct(sessao) / 1e6, 1)   AS volume_medio_milhoes
FROM dia
GROUP BY segmento, janela_brasilia
ORDER BY min(minuto_et)

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