Volume in the four weeks around day 180 vs the weeks before it: nine US listings
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.
| ticker | baseline_volume_m | window_volume_m | volume_ratio |
|---|---|---|---|
| UBER | 8.47 | 38.41 | 4.53 |
| CAVA | 1.28 | 3.12 | 2.44 |
| RIVN | 16.54 | 28.53 | 1.72 |
| HOOD | 18.09 | 27.68 | 1.53 |
| ABNB | 7.55 | 8.46 | 1.12 |
| BIRK | 0.52 | 0.55 | 1.05 |
| RDDT | 3.73 | 3.92 | 1.05 |
| DASH | 3.59 | 3.57 | 0.99 |
| LYFT | 6.44 | 5.97 | 0.93 |
- Rows × columns
- 9 × 4
- Computed
- Completeness
- No missing values
- Source
- US exchange, SIP and OPRA market data
- Licence
- Strasmore terms · free, no signup
What each column holds
| Column | Type | Range | Notes |
|---|---|---|---|
ticker |
text | 9 distinct values (ABNB, BIRK, CAVA…) | |
baseline_volume_m |
number | 0.52 to 18.09 | count |
window_volume_m |
number | 0.55 to 38.41 | count |
volume_ratio |
number | 0.93 to 4.53 | 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 ipos AS (
SELECT tupleElement(pair, 1) AS ticker,
toDate(tupleElement(pair, 2)) AS pricing_date
FROM (
SELECT arrayJoin([('LYFT', '2019-03-28'), ('UBER', '2019-05-09'),
('DASH', '2020-12-08'), ('ABNB', '2020-12-09'),
('HOOD', '2021-07-28'), ('RIVN', '2021-11-09'),
('CAVA', '2023-06-14'), ('BIRK', '2023-10-10'),
('RDDT', '2024-03-20')]) AS pair
)
),
daily AS (
SELECT ticker,
toDate(toTimeZone(window_start, 'America/New_York')) AS session_date,
toFloat64(sum(volume)) AS shares
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('LYFT', 'UBER', 'DASH', 'ABNB', 'HOOD', 'RIVN', 'CAVA', 'BIRK', 'RDDT')
AND window_start >= toDateTime('2019-07-01 00:00:00')
AND window_start < toDateTime('2024-11-01 00:00:00')
GROUP BY ticker, session_date
)
SELECT d.ticker AS ticker,
round(avgIf(d.shares, dateDiff('day', i.pricing_date, d.session_date) BETWEEN 120 AND 170) / 1e6, 2) AS baseline_volume_m,
round(avgIf(d.shares, dateDiff('day', i.pricing_date, d.session_date) BETWEEN 171 AND 200) / 1e6, 2) AS window_volume_m,
round(avgIf(d.shares, dateDiff('day', i.pricing_date, d.session_date) BETWEEN 171 AND 200)
/ avgIf(d.shares, dateDiff('day', i.pricing_date, d.session_date) BETWEEN 120 AND 170), 2) AS volume_ratio
FROM daily AS d
INNER JOIN ipos AS i ON d.ticker = i.ticker
GROUP BY d.ticker
HAVING countIf(dateDiff('day', i.pricing_date, d.session_date) BETWEEN 120 AND 170) >= 20
AND countIf(dateDiff('day', i.pricing_date, d.session_date) BETWEEN 171 AND 200) >= 10
ORDER BY volume_ratio DESC
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