STRASMORE/EXPLORE 2,500 QUERIES

iv_percentiles

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 2026-09-23, from gld-implied-volatility.

as of ranking 5×3read in context →
iv_percentiles — 5 rows by 3 columns, computed from US exchange, SIP and OPRA data.
percentilegld_iv_pctspy_iv_pct
5th11.8611.96
25th14.3513.48
50th15.8315.6
75th18.3819.28
95th26.8626.43
Rows × columns
5 × 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 iv_percentiles, derived from the stored result.
ColumnTypeRangeNotes
percentile text 5 distinct values (25th, 50th, 5th…)
gld_iv_pct number 11.86 to 26.86 percent
spy_iv_pct number 11.96 to 26.43 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
            underlying_symbol                        AS sym,
            date                                     AS d,
            avg(toFloat64(implied_volatility)) * 100 AS atm_iv
        FROM global_markets.options_greeks
        WHERE underlying_symbol IN ('GLD', 'SPY')
          AND date >= '2021-09-01'
          AND date <  '2026-09-01'
          AND iv_converged = 1
          AND volume > 0
          AND days_to_expiry BETWEEN 20 AND 45
          AND abs(toFloat64(strike_price) / toFloat64(underlying_close) - 1) < 0.05
        GROUP BY sym, d
    ),
    curves AS
    (
        SELECT
            sym,
            quantilesDeterministic(0.05, 0.25, 0.5, 0.75, 0.95)(atm_iv, toUInt64(d)) AS qs
        FROM daily
        GROUP BY sym
    )
SELECT
    ['5th', '25th', '50th', '75th', '95th'][idx] AS percentile,
    round(anyIf(qs, sym = 'GLD')[idx], 2)        AS gld_iv_pct,
    round(anyIf(qs, sym = 'SPY')[idx], 2)        AS spy_iv_pct
FROM curves
ARRAY JOIN [1, 2, 3, 4, 5] AS idx
GROUP BY idx
ORDER BY idx
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