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US Premarket and After-Hours in UK Time
SPY volume by New York hour, with the London clock beside itseries · 2026-10-01 · 16×4Preview: a 16-point series, roughly flat. AAPL median quoted spread by hour across one full extended dayseries · 2026-10-01 · 16×4Preview: a 16-point series, roughly flat. The London clock time of the 9:30am ET open, late October 2025series · 2026-10-01 · 16×4Preview: a 16-point series, roughly flat.
US Stock Market Hours in London Time (BST/GMT)
Upcoming US market closures, with London's status on each daytable · 2026-09-26 · 12×7 US trading sessions on a London clocktable · 2026-09-26 · 4×5 The four-hour weeks of 2026 and 2027, when 9:30 a.m. New York is 13:30 Londontable · 2026-09-26 · 4×5
SPY volume by New York hour, with the London clock beside it

SPY volume by New York hour, with the London clock beside it

most recentas of series 16×4read in context →
SPY volume by New York hour, with the London clock beside it — 16 rows by 4 columns, computed from US exchange, SIP and OPRA data.
et_timelondon_timeavg_session_volume_kshare_of_day_pct
04:0009:00239.50.56
05:0010:00168.40.4
06:0011:00181.90.43
07:0012:00356.20.84
08:0013:001497.93.52
09:0014:004831.611.36
10:0015:00501711.8
11:0016:004700.211.05
12:0017:003144.87.4
13:0018:002814.16.62
14:0019:004368.39.78
15:0020:0010170.322.78
16:0021:005502.312.32
17:0022:00375.50.84
18:0023:0095.60.21
19:0000:0039.40.09
the exact SQL behind every number
WITH bars AS
(
    SELECT
        toTimeZone(window_start, 'America/New_York') AS et,
        toTimeZone(window_start, 'Europe/London')    AS uk,
        volume
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= '2026-09-01 00:00:00'
      AND window_start <  '2026-10-01 00:00:00'
      AND toHour(toTimeZone(window_start, 'America/New_York')) BETWEEN 4 AND 19
)
SELECT
    formatDateTime(toStartOfHour(et), '%H:%i')                                     AS et_time,
    formatDateTime(toStartOfHour(uk), '%H:%i')                                     AS london_time,
    round(sum(volume) / countDistinct(toDate(et)) / 1000, 1)                       AS avg_session_volume_k,
    round(100 * sum(volume) / (SELECT sum(volume) FROM bars), 2)                   AS share_of_day_pct
FROM bars
GROUP BY et_time, london_time
ORDER BY et_time
$