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Weekly average daily volume: Reddit's first year of trading, March 2024 to March 2025

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 2026-08-03, from How to Find a Lockup Expiration Date.

as of series 53×2read in context →
Weekly average daily volume: Reddit's first year of trading, March 2024 to March 2025 — 53 rows by 2 columns, computed from US exchange, SIP and OPRA data.
weekavg_daily_volume_m
2024-03-1832.21
2024-03-2522.16
2024-04-016.69
2024-04-083.03
2024-04-152.38
2024-04-221.78
2024-04-291.86
2024-05-065.98
2024-05-137.75
2024-05-203.41
2024-05-272.14
2024-06-032.68
2024-06-102.98
2024-06-172.4
2024-06-241.98
2024-07-013.47
2024-07-082.48
2024-07-152.82
2024-07-222.63
2024-07-292.29
2024-08-057.33
2024-08-123.69
2024-08-194.28
2024-08-263.66
2024-09-022.77
2024-09-093.67
2024-09-163.96
2024-09-233.86
2024-09-304.18
2024-10-073.57
2024-10-144.62
2024-10-213.16
2024-10-2816.83
2024-11-047.18
2024-11-114.34
2024-11-188.36
2024-11-255.49
2024-12-025.35
2024-12-098.25
2024-12-165.48
2024-12-232.41
2024-12-305.16
2025-01-064.1
2025-01-134
2025-01-204.75
2025-01-274.29
2025-02-034.59
2025-02-1010.01
2025-02-178.21
2025-02-246.1
2025-03-037.42
2025-03-1011.87
2025-03-1712.16
Rows × columns
53 × 2
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 Weekly average daily volume: Reddit's first year of trading, March 2024 to March 2025, derived from the stored result.
ColumnTypeRangeNotes
week date 2024-03-18 to 2025-03-17
avg_daily_volume_m number 1.78 to 32.21 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.

the exact SQL behind every number
WITH daily AS (
    SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS session_date,
           toFloat64(sum(volume)) AS shares
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'RDDT'
      AND window_start >= toDateTime('2024-03-21 00:00:00')
      AND window_start < toDateTime('2025-03-21 00:00:00')
    GROUP BY session_date
)
SELECT toMonday(session_date) AS week,
       round(avg(shares) / 1e6, 2) AS avg_daily_volume_m
FROM daily
GROUP BY week
ORDER BY week

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