Median move after the split, same cohort, at 20, 60 and 120 sessions

Name: Median move after the split, same cohort, at 20, 60 and 120 sessions
Creator: Strasmore
Published: 2026-09-20
License: https://www.strasmore.com/terms/

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 What Happens After a Reverse Stock Split?.

as of 2026-09-20 ranking 3×4read in context →

Median move after the split, same cohort, at 20, 60 and 120 sessions — 3 rows by 4 columns, computed 2026-09-20 from US exchange, SIP and OPRA data.
horizon	names_count	median_return_pct	share_below_split_close_pct
20 sessions after	586	-12.7	69.5
60 sessions after	557	-26	73.1
120 sessions after	513	-38.6	75.6

Rows × columns: 3 × 4
Computed: 2026-09-20
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 Median move after the split, same cohort, at 20, 60 and 120 sessions, derived from the stored result.
Column	Type	Range	Notes
`horizon`	text	3 distinct values
`names_count`	number	513 to 586	count
`median_return_pct`	number	-38.6 to -12.7	percent
`share_below_split_close_pct`	number	69.5 to 75.6	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 2026-09-20, 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
reverse_splits AS
(
    SELECT ticker, toDate(execution_date) AS execution_date
    FROM global_markets.stocks_splits
    WHERE split_to < split_from
      AND toDate(execution_date) >= '2025-03-01'
      AND toDate(execution_date) <  '2026-03-01'
      AND ticker NOT IN ('SPCX')
    GROUP BY ticker, execution_date
),
post_split_closes AS
(
    SELECT
        d.ticker                                                                                   AS ticker,
        r.execution_date                                                                           AS execution_date,
        arrayMap(x -> tupleElement(x, 2), arraySort(groupArray((d.date, toFloat64(d.close)))))    AS closes
    FROM global_markets.stocks_daily_aggs AS d
    INNER JOIN reverse_splits AS r ON r.ticker = d.ticker
    WHERE d.ticker IN (SELECT ticker FROM reverse_splits)
      AND d.date >= '2025-03-01'
      AND d.date <  '2026-10-01'
      AND d.date >= r.execution_date
      AND d.date <  r.execution_date + 200
      AND d.close > 0
    GROUP BY d.ticker, r.execution_date
)
SELECT
    horizon,
    count()                                                                AS names_count,
    round(quantileDeterministic(0.5)(return_pct, cityHash64(ticker)), 1)   AS median_return_pct,
    round(100 * countIf(return_pct < 0) / count(), 1)                      AS share_below_split_close_pct
FROM
(
    SELECT
        ticker,
        sessions_after,
        concat(toString(sessions_after), ' sessions after')    AS horizon,
        100 * (closes[sessions_after + 1] / closes[1] - 1)     AS return_pct
    FROM post_split_closes
    ARRAY JOIN [20, 60, 120] AS sessions_after
    WHERE length(closes) > sessions_after
)
GROUP BY horizon
ORDER BY min(sessions_after)

SQL to run

WITH
reverse_splits AS
(
    SELECT ticker, toDate(execution_date) AS execution_date
    FROM global_markets.stocks_splits
    WHERE split_to < split_from
      AND toDate(execution_date) >= '2025-03-01'
      AND toDate(execution_date) <  '2026-03-01'
      AND ticker NOT IN ('SPCX')
    GROUP BY ticker, execution_date
),
post_split_closes AS
(
    SELECT
        d.ticker                                                                                   AS ticker,
        r.execution_date                                                                           AS execution_date,
        arrayMap(x -> tupleElement(x, 2), arraySort(groupArray((d.date, toFloat64(d.close)))))    AS closes
    FROM global_markets.stocks_daily_aggs AS d
    INNER JOIN reverse_splits AS r ON r.ticker = d.ticker
    WHERE d.ticker IN (SELECT ticker FROM reverse_splits)
      AND d.date >= '2025-03-01'
      AND d.date <  '2026-10-01'
      AND d.date >= r.execution_date
      AND d.date <  r.execution_date + 200
      AND d.close > 0
    GROUP BY d.ticker, r.execution_date
)
SELECT
    horizon,
    count()                                                                AS names_count,
    round(quantileDeterministic(0.5)(return_pct, cityHash64(ticker)), 1)   AS median_return_pct,
    round(100 * countIf(return_pct < 0) / count(), 1)                      AS share_below_split_close_pct
FROM
(
    SELECT
        ticker,
        sessions_after,
        concat(toString(sessions_after), ' sessions after')    AS horizon,
        100 * (closes[sessions_after + 1] / closes[1] - 1)     AS return_pct
    FROM post_split_closes
    ARRAY JOIN [20, 60, 120] AS sessions_after
    WHERE length(closes) > sessions_after
)
GROUP BY horizon
ORDER BY min(sessions_after)

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