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Twelve months of daily moves: annualized volatility and worst session, eight names

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 2026-08-02, from Learn Quant Trading From an Open Source Book.

as of ranking 8×3read in context →
Twelve months of daily moves: annualized volatility and worst session, eight names — 8 rows by 3 columns, computed from US exchange, SIP and OPRA data.
tickerannualized_vol_pctworst_day_pct
COIN6813.34
TSLA46.614.63
NVDA36.56.22
MSFT31.510.02
AAPL25.87.44
KO18.83.96
JNJ18.43.65
SPY12.72.69
Rows × columns
8 × 3
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 Twelve months of daily moves: annualized volatility and worst session, eight names, derived from the stored result.
ColumnTypeRangeNotes
ticker text 8 distinct values (AAPL, COIN, JNJ…)
annualized_vol_pct number 12.7 to 68 percent
worst_day_pct number 2.69 to 14.63 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 session,
           argMax(close, window_start) AS session_close
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker IN ('SPY', 'KO', 'JNJ', 'MSFT', 'AAPL', 'NVDA', 'TSLA', 'COIN')
      AND toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2025-08-01')
      AND toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-07-31')
      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
           + toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
    GROUP BY ticker, session
),
rets AS (
    SELECT ticker,
           toFloat64(session_close) AS close_px,
           toFloat64(lagInFrame(session_close) OVER (PARTITION BY ticker ORDER BY session)) AS prev_close
    FROM daily
)
SELECT ticker,
       round(stddevSamp(close_px / prev_close - 1) * sqrt(252) * 100, 1) AS annualized_vol_pct,
       round(abs(min(close_px / prev_close - 1)) * 100, 2) AS worst_day_pct
FROM rets
WHERE prev_close > 0
GROUP BY ticker
ORDER BY annualized_vol_pct DESC

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