The publication lag in one row: fastest, median and slowest across incrementally-delivered settlements
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 2026-09-20, from When Is Short Interest Released?.
- Rows × columns
- 1 × 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 |
|---|---|---|---|
settlements_measured |
number | every row is 12 | |
fastest_lag_days |
number | every row is 10 | |
median_lag_days |
number | every row is 14 | |
slowest_lag_days |
number | every row is 26 |
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 first_arrival AS (
SELECT settlement_date,
toDate(min(_ingest_time)) AS arrived
FROM global_markets.stocks_short_interest
GROUP BY settlement_date
),
bulk_days AS (
SELECT arrived
FROM first_arrival
GROUP BY arrived
HAVING count() > 5
),
organic AS (
SELECT settlement_date,
dateDiff('day', settlement_date, arrived) AS lag
FROM first_arrival
WHERE arrived NOT IN (SELECT arrived FROM bulk_days)
)
SELECT count() AS settlements_measured,
min(lag) AS fastest_lag_days,
round(quantileDeterministic(0.5)(lag, cityHash64(settlement_date)), 1) AS median_lag_days,
max(lag) AS slowest_lag_days
FROM organic