STRASMORE/EXPLORE 2,882 QUERIES

late_drift

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 2026-10-01, from index-rebalance-day-closing-auction.

as of ranking 12×3read in context →
late_drift — 12 rows by 3 columns, computed from US exchange, SIP and OPRA data.
labelevent_drift_bpstypical_drift_bps
AAPL S&P quarterly Dec-2025110.615.2
KO S&P quarterly Dec-202537.76.2
MSFT Russell recon Jun-202537.48.1
KO Russell recon Jun-202633.48.1
MSFT Russell recon Jun-202633.318.8
MSFT S&P quarterly Mar-2026248.4
AAPL Russell recon Jun-202521.49.5
AAPL S&P quarterly Mar-202616.217.9
KO S&P quarterly Mar-202614.76.8
AAPL Russell recon Jun-2026617.2
KO Russell recon Jun-20255.710.9
MSFT S&P quarterly Dec-20253.915
Rows × columns
12 × 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 late_drift, derived from the stored result.
ColumnTypeRangeNotes
label text 12 distinct values
event_drift_bps number 3.9 to 110.6
typical_drift_bps number 6.2 to 18.8

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 marks AS
(
    SELECT
        ticker,
        toDate(toTimeZone(window_start, 'America/New_York')) AS session_date,
        anyIf(toFloat64(close),
              toHour(toTimeZone(window_start, 'America/New_York')) = 15
              AND toMinute(toTimeZone(window_start, 'America/New_York')) = 50) AS px_350,
        anyIf(toFloat64(close),
              toHour(toTimeZone(window_start, 'America/New_York')) = 16
              AND toMinute(toTimeZone(window_start, 'America/New_York')) = 0)  AS px_close
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('AAPL', 'MSFT', 'KO')
      AND window_start >= '2025-05-01'
      AND window_start <  '2026-06-29'
      AND toHour(toTimeZone(window_start, 'America/New_York')) IN (15, 16)
    GROUP BY ticker, session_date
    HAVING px_350 > 0
       AND px_close > 0
),
drift AS
(
    SELECT
        ticker,
        session_date,
        round(10000 * abs(px_close / px_350 - 1), 1)                  AS drift_bps,
        row_number() OVER (PARTITION BY ticker ORDER BY session_date) AS n
    FROM marks
),
events AS
(
    SELECT
        ticker,
        drift_bps,
        n,
        multiIf(session_date = '2025-06-27', 'Russell recon Jun-2025',
                session_date = '2025-12-19', 'S&P quarterly Dec-2025',
                session_date = '2026-03-20', 'S&P quarterly Mar-2026',
                                             'Russell recon Jun-2026') AS event
    FROM drift
    WHERE session_date IN ('2025-06-27', '2025-12-19', '2026-03-20', '2026-06-26')
)
SELECT
    concat(e.ticker, ' ', e.event)                         AS label,
    e.drift_bps                                            AS event_drift_bps,
    round(quantileDeterministic(0.5)(b.drift_bps, b.n), 1) AS typical_drift_bps
FROM events AS e
INNER JOIN drift AS b ON b.ticker = e.ticker
WHERE b.n >= e.n - 20
  AND b.n <= e.n - 1
GROUP BY e.ticker, e.event, e.drift_bps
ORDER BY event_drift_bps DESC
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