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The index against the names inside it: calendar years 2021 to 2025, a 34-name large-cap basket

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 2026-07-31, from What Is the Efficient Market Hypothesis?.

as of table 5×5read in context →
The index against the names inside it: calendar years 2021 to 2025, a 34-name large-cap basket — 5 rows by 5 columns, computed from US exchange, SIP and OPRA data.
yearindex_return_pctmedian_stock_return_pctstocks_measuredpct_beating_index
202128.718.93438.2
2022-20-13.33458.8
202324.89.83441.2
20242412.73432.4
202516.610.13435.3
Rows × columns
5 × 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 The index against the names inside it: calendar years 2021 to 2025, a 34-name large-cap basket, derived from the stored result.
ColumnTypeRangeNotes
year text 5 distinct values (2021, 2022, 2023…)
index_return_pct number -20 to 28.7 percent
median_stock_return_pct number -13.3 to 18.9 percent
stocks_measured number every row is 34
pct_beating_index number 32.4 to 58.8 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 daily AS (
    SELECT ticker,
           toDate(toTimeZone(window_start, 'America/New_York')) AS dt,
           argMax(toFloat64(close), window_start) AS close_px
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('SPY','AAPL','MSFT','NVDA','AMZN','GOOGL','META','TSLA','JPM','XOM','JNJ','WMT','PG','KO','PEP','HD','MRK','LLY','COST','CVX','ORCL','CSCO','INTC','VZ','MCD','NKE','DIS','CAT','HON','TXN','AMD','NFLX','MO','LMT','UNH')
      AND toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2021-01-01')
      AND toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2025-12-31')
      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
           + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
    GROUP BY ticker, dt
),
per_year AS (
    SELECT ticker, toYear(dt) AS yr,
           argMin(close_px, dt) AS first_px,
           argMax(close_px, dt) AS last_px
    FROM daily
    GROUP BY ticker, yr
),
perf AS (
    SELECT yr, ticker, (last_px / first_px - 1) * 100 AS ret_pct FROM per_year
),
bench AS (
    SELECT yr, ret_pct AS index_pct FROM perf WHERE ticker = 'SPY'
)
SELECT toString(perf.yr) AS year,
       round(any(bench.index_pct), 1) AS index_return_pct,
       round(median(perf.ret_pct), 1) AS median_stock_return_pct,
       countIf(perf.ticker != 'SPY') AS stocks_measured,
       round(100 * countIf(perf.ticker != 'SPY' AND perf.ret_pct > bench.index_pct)
             / countIf(perf.ticker != 'SPY'), 1) AS pct_beating_index
FROM perf
INNER JOIN bench ON perf.yr = bench.yr
GROUP BY perf.yr
ORDER BY perf.yr

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