The January 2019 universe, grouped by what happened to each name
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 2026-08-22, from Survivorship Bias in Stock Data, Explained.
| outcome_label | cohort_size | avg_return_pct | share_above_entry_pct |
|---|---|---|---|
| Last bar in 2019 | 119 | 12.2 | 72.3 |
| Last bar in 2020 | 90 | 20.9 | 53.3 |
| Last bar in 2021 | 97 | 62.1 | 79.4 |
| Last bar in 2022 | 97 | 56 | 66 |
| Last bar in 2023 | 83 | 33.2 | 56.6 |
| Last bar in 2024 | 76 | 19.7 | 53.9 |
| Last bar in 2025 | 84 | 70.3 | 52.4 |
| Last bar in 2026 | 49 | 75.5 | 63.3 |
| Still trading | 1951 | 138.1 | 72.4 |
- Rows × columns
- 9 × 4
- Computed
- Completeness
- No missing values
- Source
- US exchange, SIP and OPRA market data
- Licence
- Strasmore terms · free, no signup
What each column holds
| Column | Type | Range | Notes |
|---|---|---|---|
outcome_label |
text | 9 distinct values | |
cohort_size |
number | 49 to 1,951 | |
avg_return_pct |
number | 12.2 to 138.1 | percent |
share_above_entry_pct |
number | 52.4 to 79.4 | 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
entry AS
(
SELECT
ticker,
argMin(toFloat64(close), date) AS entry_close
FROM global_markets.stocks_daily_aggs
WHERE date BETWEEN '2019-01-01' AND '2019-01-31'
AND ticker NOT IN ('SPCX')
GROUP BY ticker
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 >= '2019-01-01'
GROUP BY ticker
)
SELECT
if(o.last_bar >= today() - 45,
'Still trading',
concat('Last bar in ', toString(toYear(o.last_bar)))) AS outcome_label,
count() AS cohort_size,
round(100 * avg(o.final_close / e.entry_close - 1), 1) AS avg_return_pct,
round(100 * countIf(o.final_close > e.entry_close) / count(), 1) AS share_above_entry_pct
FROM entry AS e
INNER JOIN outcome AS o ON o.ticker = e.ticker
GROUP BY outcome_label
ORDER BY outcome_label
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