STRASMORE/EXPLORE 3,293 QUERIES

abertura_empirica

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 2026-11-01, from us-stock-market-hours-brasilia-time.

as of series 10×6read in context →
abertura_empirica — 10 rows by 6 columns, computed from US exchange, SIP and OPRA data.
datedia_mesdia_semanaabertura_brtabertura_brt_em_horassalto_de_volume_vs_bloco_anterior
2026-03-0202/03segunda11:3011.528.5
2026-03-0303/03terça11:3011.523.7
2026-03-0404/03quarta11:3011.514.4
2026-03-0505/03quinta11:3011.517.8
2026-03-0606/03sexta11:3011.518.5
2026-03-0909/03segunda10:3010.519.8
2026-03-1010/03terça10:3010.523.4
2026-03-1111/03quarta10:3010.517.5
2026-03-1212/03quinta10:3010.513.7
2026-03-1313/03sexta10:3010.519.1
Rows × columns
10 × 6
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 abertura_empirica, derived from the stored result.
ColumnTypeRangeNotes
date date 2026-03-02 to 2026-03-13
dia_mes text 10 distinct values (02/03, 03/03, 04/03…)
dia_semana text 5 distinct values (quarta, quinta, segunda…)
abertura_brt text 2 distinct values (10:30, 11:30)
abertura_brt_em_horas number 10.5 to 11.5
salto_de_volume_vs_bloco_anterior number 13.7 to 28.5 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 , 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 blocos AS
(
    SELECT
        toDate(window_start, 'America/New_York')                        AS dia,
        toStartOfInterval(window_start, INTERVAL 30 MINUTE)             AS bloco,
        bloco - INTERVAL 30 MINUTE                                      AS bloco_anterior,
        sum(toFloat64(volume))                                          AS acoes
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= toDateTime('2026-03-02 00:00:00', 'America/New_York')
      AND window_start <  toDateTime('2026-03-14 00:00:00', 'America/New_York')
    GROUP BY dia, bloco, bloco_anterior
)
SELECT
    toString(atual.dia)                                                                 AS date,
    formatDateTime(atual.dia, '%d/%m')                                                  AS dia_mes,
    multiIf(toDayOfWeek(atual.dia) = 1, 'segunda', toDayOfWeek(atual.dia) = 2, 'terça',
            toDayOfWeek(atual.dia) = 3, 'quarta',  toDayOfWeek(atual.dia) = 4, 'quinta',
            toDayOfWeek(atual.dia) = 5, 'sexta',   toDayOfWeek(atual.dia) = 6, 'sábado',
            'domingo')                                                                  AS dia_semana,
    formatDateTime(argMax(atual.bloco, atual.acoes / anterior.acoes), '%H:%i', 'America/Sao_Paulo') AS abertura_brt,
    toHour(toTimeZone(argMax(atual.bloco, atual.acoes / anterior.acoes), 'America/Sao_Paulo'))
      + toMinute(toTimeZone(argMax(atual.bloco, atual.acoes / anterior.acoes), 'America/Sao_Paulo')) / 60 AS abertura_brt_em_horas,
    round(max(atual.acoes / anterior.acoes), 1)                                         AS salto_de_volume_vs_bloco_anterior
FROM blocos AS atual
INNER JOIN blocos AS anterior
    ON anterior.dia = atual.dia
   AND anterior.bloco = atual.bloco_anterior
WHERE anterior.acoes > 0
GROUP BY atual.dia
ORDER BY atual.dia
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