volume_por_hora

Name: volume_por_hora
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 8×3read in context →

volume_por_hora — 8 rows by 3 columns, computed 2026-10-04 from US exchange, SIP and OPRA data.
hora_brasilia	pct_do_volume	volume_medio_milhoes
10h	16.3	32.7
11h	17.7	35.6
12h	13.2	26.5
13h	10.7	21.6
14h	9.2	18.4
15h	9.8	19.7
16h	21.1	42.3
17h	2.1	4.1

Rows × columns: 8 × 3
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 volume_por_hora, derived from the stored result.
Column	Type	Range	Notes
`hora_brasilia`	text	8 distinct values (10h, 11h, 12h…)
`pct_do_volume`	number	2.1 to 21.1	percent
`volume_medio_milhoes`	number	4.1 to 42.3	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 barras AS
(
    SELECT
        formatDateTime(toTimeZone(window_start, 'America/Sao_Paulo'), '%Hh') AS hora_br,
        toDate(toTimeZone(window_start, 'America/New_York'))                 AS sessao,
        toHour(toTimeZone(window_start, 'America/New_York')) * 60
            + toMinute(toTimeZone(window_start, 'America/New_York'))         AS minuto_et,
        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'
),
regular AS
(
    SELECT *
    FROM barras
    WHERE minuto_et >= 570 AND minuto_et <= 960
)
SELECT
    hora_br                                                        AS hora_brasilia,
    round(toFloat64(sum(volume)) * 100
          / toFloat64((SELECT sum(volume) FROM regular)), 1)       AS pct_do_volume,
    round(toFloat64(sum(volume)) / countDistinct(sessao) / 1e6, 1) AS volume_medio_milhoes
FROM regular
GROUP BY hora_br
ORDER BY hora_br

SQL to run

WITH barras AS
(
    SELECT
        formatDateTime(toTimeZone(window_start, 'America/Sao_Paulo'), '%Hh') AS hora_br,
        toDate(toTimeZone(window_start, 'America/New_York'))                 AS sessao,
        toHour(toTimeZone(window_start, 'America/New_York')) * 60
            + toMinute(toTimeZone(window_start, 'America/New_York'))         AS minuto_et,
        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'
),
regular AS
(
    SELECT *
    FROM barras
    WHERE minuto_et >= 570 AND minuto_et <= 960
)
SELECT
    hora_br                                                        AS hora_brasilia,
    round(toFloat64(sum(volume)) * 100
          / toFloat64((SELECT sum(volume) FROM regular)), 1)       AS pct_do_volume,
    round(toFloat64(sum(volume)) / countDistinct(sessao) / 1e6, 1) AS volume_medio_milhoes
FROM regular
GROUP BY hora_br
ORDER BY hora_br

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