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Survivorship, measured: March cohorts of US symbols still trading in late July 2026

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 2026-08-05, from Local A-Share Data Lake for AI Agents.

as of table 10×5read in context →
Survivorship, measured: March cohorts of US symbols still trading in late July 2026 — 10 rows by 5 columns, computed from US exchange, SIP and OPRA data.
yearnames_on_tape_countstill_trading_countgone_countstill_trading_pct
201681014061404050.1
201781354273386252.5
201882984576372255.1
201984914932355958.1
202087925422337061.7
202199815937404459.5
2022115536914463959.8
2023110967479361767.4
2024107038310239377.6
2025110849614147086.7
Rows × columns
10 × 5
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 Survivorship, measured: March cohorts of US symbols still trading in late July 2026, derived from the stored result.
ColumnTypeRangeNotes
year number 2,016 to 2,025
names_on_tape_count number 8,101 to 11,553 count
still_trading_count number 4,061 to 9,614 count
gone_count number 1,470 to 4,639 count
still_trading_pct number 50.1 to 86.7 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.

the exact SQL behind every number 
WITH on_tape_now AS (
    SELECT ticker
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2026-07-20')
      AND toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-07-31')
    GROUP BY ticker
),
cohort AS (
    SELECT toYear(toTimeZone(window_start, 'America/New_York')) AS cohort_year,
           ticker
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE toYear(toTimeZone(window_start, 'America/New_York')) BETWEEN 2016 AND 2025
      AND toMonth(toTimeZone(window_start, 'America/New_York')) = 3
      AND toDayOfMonth(toTimeZone(window_start, 'America/New_York')) BETWEEN 10 AND 14
    GROUP BY cohort_year, ticker
)
SELECT c.cohort_year AS year,
       count() AS names_on_tape_count,
       countIf(n.ticker != '') AS still_trading_count,
       count() - countIf(n.ticker != '') AS gone_count,
       round(100 * countIf(n.ticker != '') / count(), 1) AS still_trading_pct
FROM cohort AS c
LEFT JOIN on_tape_now AS n ON c.ticker = n.ticker
GROUP BY year
ORDER BY year

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