One stock, one session, three definitions of the IV input
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 2026-08-22, from IV Rank vs IV Percentile: Formulas Explained.
| iv_series | current_iv_pct | low_52w_iv_pct | high_52w_iv_pct | iv_rank | iv_percentile |
|---|---|---|---|---|---|
| Wide net, any expiry | 32.07 | 26.15 | 75.78 | 11.9 | 31.6 |
| Front month ATM | 26.14 | 16.63 | 107.16 | 10.5 | 38.3 |
| Near 30 day ATM | 24.89 | 18.98 | 45.92 | 21.9 | 45.5 |
- Rows × columns
- 3 × 6
- 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 |
|---|---|---|---|
iv_series |
text | 3 distinct values | |
current_iv_pct |
number | 24.89 to 32.07 | percent |
low_52w_iv_pct |
number | 16.63 to 26.15 | percent |
high_52w_iv_pct |
number | 45.92 to 107.16 | percent |
iv_rank |
number | 10.5 to 21.9 | ratio or rate |
iv_percentile |
number | 31.6 to 45.5 | ratio or rate |
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 contracts AS
(
SELECT
date,
days_to_expiry,
abs(toFloat64(strike_price) / toFloat64(underlying_close) - 1) AS moneyness,
toFloat64(implied_volatility) * 100 AS iv_pct
FROM global_markets.options_greeks
WHERE underlying_symbol = 'AAPL'
AND date >= today() - 371
AND iv_converged = 1
AND volume > 0
),
defs AS
(
SELECT
spec.1 AS iv_series,
spec.2 AS min_dte,
spec.3 AS max_dte,
spec.4 AS max_moneyness
FROM
(
SELECT arrayJoin([
('Near 30 day ATM', 20, 45, 0.05),
('Front month ATM', 1, 19, 0.05),
('Wide net, any expiry', 1, 400, 0.30)
]) AS spec
)
),
daily AS
(
SELECT
s.iv_series AS iv_series,
c.date AS date,
avg(c.iv_pct) AS atm_iv
FROM contracts AS c
CROSS JOIN defs AS s
WHERE c.days_to_expiry BETWEEN s.min_dte AND s.max_dte
AND c.moneyness < s.max_moneyness
GROUP BY iv_series, date
),
latest AS
(
SELECT
iv_series,
argMax(atm_iv, date) AS iv_now
FROM daily
GROUP BY iv_series
)
SELECT
d.iv_series AS iv_series,
round(l.iv_now, 2) AS current_iv_pct,
round(min(d.atm_iv), 2) AS low_52w_iv_pct,
round(max(d.atm_iv), 2) AS high_52w_iv_pct,
round(100 * (l.iv_now - min(d.atm_iv)) / nullIf(max(d.atm_iv) - min(d.atm_iv), 0), 1) AS iv_rank,
round(100 * countIf(d.atm_iv < l.iv_now) / count(), 1) AS iv_percentile
FROM daily AS d
INNER JOIN latest AS l ON l.iv_series = d.iv_series
GROUP BY d.iv_series, l.iv_now
ORDER BY current_iv_pct DESC
Run your own version of this
The same 22 years of US equities and 12 years of options data are queryable in SQL or plain English. A free account runs 100 queries a day and takes no card.
More from this analysisIV Rank vs IV Percentile: Formulas Explained
IV rank vs IV percentile, eight liquid names, 52 week lookback
table 8×5
→
Current, 52 week low and 52 week high ATM IV for each name
table 8×6
→
AAPL at the money implied volatility, weekly, trailing 52 weeks
series 53×5
→
The same session scored at five different lookback windows
ranking 5×4
→
Where IV percentile sits furthest above IV rank, latest session
table 12×6
→
The same reading against each name's own 52-week implied volatility range (July 28, 2026)
table 11×5
→
See all 2,170 queries →