STRASMORE/EXPLORE 3,293 QUERIES

upcoming

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 does-the-us-market-close-for-brazilian-holidays.

as of series 12×8read in context →
upcoming — 12 rows by 8 columns, computed from US exchange, SIP and OPRA data.
holiday_datedate_brweekdayholidayday_statusearly_close_nyearly_close_brasiliadays_away
2026-11-2626/11/2026quiThanksgivingfechada25
2026-11-2727/11/2026sexThanksgivingpregão reduzido13:0015:0026
2026-12-2424/12/2026quiChristmaspregão reduzido13:0015:0053
2026-12-2525/12/2026sexChristmasfechada54
2027-01-0101/01/2027sexNew Years Dayfechada61
2027-01-1818/01/2027segMartin Luther King, Jr. Dayfechada78
2027-02-1515/02/2027segWashington's Birthdayfechada106
2027-03-2626/03/2027sexGood Fridayfechada145
2027-05-3131/05/2027segMemorial Dayfechada211
2027-06-1818/06/2027sexJuneteenthfechada229
2027-07-0505/07/2027segIndependence Dayfechada246
2027-09-0606/09/2027segLabor Dayfechada309
Rows × columns
12 × 8
Period covered
to
Computed
Completeness
Some fields are partly empty — see the columns below
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 upcoming, derived from the stored result.
ColumnTypeRangeNotes
holiday_date date 2026-11-26 to 2027-09-06
date_br text 12 distinct values (01/01/2027, 05/07/2027, 06/09/2027…)
weekday text 3 distinct values (qui, seg, sex)
holiday text 10 distinct values (Christmas, Good Friday, Independence Day…)
day_status text 2 distinct values (fechada, pregão reduzido)
early_close_ny text 1 distinct value (13:00) 2 of 12 rows populated
early_close_brasilia text 1 distinct value (15:00) 2 of 12 rows populated
days_away number 25 to 309

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
    toString(date)                                              AS holiday_date,
    formatDateTime(date, '%d/%m/%Y')                            AS date_br,
    arrayElement(['seg', 'ter', 'qua', 'qui', 'sex', 'sáb', 'dom'],
                 toDayOfWeek(date))                             AS weekday,
    any(name)                                                   AS holiday,
    any(multiIf(status = 'closed',      'fechada',
                status = 'early-close', 'pregão reduzido',
                toString(status)))                              AS day_status,
    any(if(status = 'early-close',
           formatDateTime(toTimeZone(close, 'America/New_York'), '%H:%i'),
           ''))                                                 AS early_close_ny,
    any(if(status = 'early-close',
           formatDateTime(toTimeZone(close, 'America/Sao_Paulo'), '%H:%i'),
           ''))                                                 AS early_close_brasilia,
    dateDiff('day', today(), date)                              AS days_away
FROM global_markets.stocks_market_holidays
WHERE date >= today()
GROUP BY date
ORDER BY date
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