STRASMORE/EXPLORE 3,256 QUERIES

How often the settlement wait is overnight, and how often it is longer

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 2026-10-09, from Limited Margin in an IRA: Rules and Limits.

as of ranking 4×3read in context →
How often the settlement wait is overnight, and how often it is longer — 4 rows by 3 columns, computed from US exchange, SIP and OPRA data.
settlement_waitfrequencyshare_pct
1 calendar day38977.6
2 calendar days81.6
3 calendar days9118.2
4 calendar days132.6
Rows × columns
4 × 3
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 How often the settlement wait is overnight, and how often it is longer, derived from the stored result.
ColumnTypeRangeNotes
settlement_wait text 4 distinct values
frequency number 8 to 389
share_pct number 1.6 to 77.6 percent

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 sessions AS
(
    SELECT date
    FROM global_markets.stocks_daily_aggs
    WHERE ticker = 'SPY'
      AND date >= today() - 730
    GROUP BY date
),
paired AS
(
    SELECT
        date,
        any(date) OVER (ORDER BY date ASC ROWS BETWEEN 1 FOLLOWING AND 1 FOLLOWING) AS next_session
    FROM sessions
),
gaps AS
(
    SELECT dateDiff('day', date, next_session) AS wait_days
    FROM paired
    WHERE next_session > date
),
tallied AS
(
    SELECT
        wait_days,
        count() AS frequency
    FROM gaps
    GROUP BY wait_days
)
SELECT
    concat(toString(wait_days), if(wait_days = 1, ' calendar day', ' calendar days')) AS settlement_wait,
    frequency,
    round(100 * frequency / sum(frequency) OVER (), 1)                                AS share_pct
FROM tallied
ORDER BY wait_days
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