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Survivors-only average vs whole-cohort average, by starting year

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 Survivorship Bias in Stock Data, Explained.

as of table 7×6read in context →
Survivors-only average vs whole-cohort average, by starting year — 7 rows by 6 columns, computed from US exchange, SIP and OPRA data.
cohort_yearcohort_sizegone_countsurvivors_only_pctfull_universe_pctgap_pct
20162728974196.714056.7
20172522823151.5111.140.4
20182669829112.882.630.1
20192646701130.610723.5
2020266964581.769.112.6
2021341696559.144.514.6
2022337870329.621.38.3
Rows × columns
7 × 6
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 Survivors-only average vs whole-cohort average, by starting year, derived from the stored result.
ColumnTypeRangeNotes
cohort_year text 7 distinct values (2016, 2017, 2018…)
cohort_size number 2,522 to 3,416
gone_count number 645 to 974 count
survivors_only_pct number 29.6 to 196.7 percent
full_universe_pct number 21.3 to 140 percent
gap_pct number 8.3 to 56.7 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
    entry AS
    (
        SELECT
            ticker,
            toYear(date)                   AS cohort_start,
            argMin(toFloat64(close), date) AS entry_close
        FROM global_markets.stocks_daily_aggs
        WHERE toMonth(date) = 1
          AND date BETWEEN '2016-01-01' AND '2022-01-31'
          AND ticker NOT IN ('SPCX')
        GROUP BY ticker, cohort_start
        HAVING argMin(toFloat64(close), date) >= 5
           AND avg(volume) >= 250000
    ),
    outcome AS
    (
        SELECT
            ticker,
            argMax(toFloat64(close), date) AS final_close,
            max(date)                      AS last_bar
        FROM global_markets.stocks_daily_aggs
        WHERE date >= '2016-01-01'
        GROUP BY ticker
    )
SELECT
    toString(e.cohort_start)                                                             AS cohort_year,
    count()                                                                              AS cohort_size,
    countIf(o.last_bar < today() - 45)                                                   AS gone_count,
    round(100 * avgIf(o.final_close / e.entry_close - 1, o.last_bar >= today() - 45), 1) AS survivors_only_pct,
    round(100 * avg(o.final_close / e.entry_close - 1), 1)                               AS full_universe_pct,
    round(100 * (avgIf(o.final_close / e.entry_close - 1, o.last_bar >= today() - 45)
                 - avg(o.final_close / e.entry_close - 1)), 1)                           AS gap_pct
FROM entry AS e
INNER JOIN outcome AS o ON o.ticker = e.ticker
GROUP BY e.cohort_start
HAVING countIf(o.last_bar >= today() - 45) > 0
ORDER BY e.cohort_start
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