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.
| ticker | annualized_vol_pct | worst_day_pct |
|---|---|---|
| COIN | 68 | 13.34 |
| TSLA | 46.6 | 14.63 |
| NVDA | 36.5 | 6.22 |
| MSFT | 31.5 | 10.02 |
| AAPL | 25.8 | 7.44 |
| KO | 18.8 | 3.96 |
| JNJ | 18.4 | 3.65 |
| SPY | 12.7 | 2.69 |
- Rows × columns
- 8 × 3
- 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 |
|---|---|---|---|
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.
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 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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