STRASMORE/EXPLORE 2,707 QUERIES

Annualized historical volatility over three lookback windows

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 2026-09-26, from Historical Volatility vs Implied Volatility.

as of ranking 6×4read in context →
Annualized historical volatility over three lookback windows — 6 rows by 4 columns, computed from US exchange, SIP and OPRA data.
symbolhv_20d_pcthv_60d_pcthv_252d_pct
TSLA43.954.746.5
NVDA32.539.137.6
MSFT25.138.632.3
AAPL22.228.424.6
KO12.921.618.8
SPY10.811.213
Rows × columns
6 × 4
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 Annualized historical volatility over three lookback windows, derived from the stored result.
ColumnTypeRangeNotes
symbol text 6 distinct values (AAPL, KO, MSFT…)
hv_20d_pct number 10.8 to 43.9 percent
hv_60d_pct number 11.2 to 54.7 percent
hv_252d_pct number 13 to 46.5 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
    paths AS
    (
        SELECT
            ticker,
            arraySort(x -> tupleElement(x, 1), groupArray((date, toFloat64(close)))) AS path
        FROM global_markets.stocks_daily_aggs
        WHERE ticker IN ('AAPL', 'KO', 'MSFT', 'NVDA', 'SPY', 'TSLA')
          AND date >= today() - 500
          AND date <  today()
        GROUP BY ticker
        HAVING count() >= 300
    ),
    log_returns AS
    (
        SELECT
            ticker,
            arrayMap(i -> log(tupleElement(path[i + 1], 2) / tupleElement(path[i], 2)),
                     range(1, length(path))) AS r
        FROM paths
    )
SELECT
    ticker                                                                     AS symbol,
    round(100 * sqrt(252) * arrayReduce('stddevSamp', arraySlice(r, -20)), 1)  AS hv_20d_pct,
    round(100 * sqrt(252) * arrayReduce('stddevSamp', arraySlice(r, -60)), 1)  AS hv_60d_pct,
    round(100 * sqrt(252) * arrayReduce('stddevSamp', arraySlice(r, -252)), 1) AS hv_252d_pct
FROM log_returns
ORDER BY hv_252d_pct DESC
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