Unusual options activity: last completed session vs. each underlying's own 20-session average
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 2026-10-08, from Unusual Options Activity: Last Session.
| ticker | vol_ratio | session_volume_k | baseline_volume_k | prior_high_volume_k | session_label | session_id | baseline_session_count |
|---|---|---|---|---|---|---|---|
| MMED | 10.9 | 60.4 | 5.6 | 42.3 | Oct 6 | 20261006 | 20 |
| BRUN | 7.1 | 54.4 | 7.7 | 35.3 | Oct 6 | 20261006 | 20 |
| HTZ | 6.7 | 208.2 | 31 | 225.8 | Oct 6 | 20261006 | 20 |
| FCEL | 5.8 | 66.8 | 11.6 | 38.1 | Oct 6 | 20261006 | 20 |
| MAT | 5.4 | 34.7 | 6.4 | 40.2 | Oct 6 | 20261006 | 20 |
| STZ | 5.1 | 28.7 | 5.6 | 13.1 | Oct 6 | 20261006 | 20 |
| CEG | 5 | 52.8 | 10.7 | 24.8 | Oct 6 | 20261006 | 20 |
| URA | 4.6 | 45.5 | 10 | 37.4 | Oct 6 | 20261006 | 20 |
| HUM | 4.4 | 28.7 | 6.6 | 15.6 | Oct 6 | 20261006 | 20 |
| NN | 4.2 | 73.1 | 17.4 | 120.8 | Oct 6 | 20261006 | 20 |
- Rows × columns
- 10 × 8
- 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 | 10 distinct values (BRUN, CEG, FCEL…) | |
vol_ratio |
number | 4.2 to 10.9 | ratio or rate |
session_volume_k |
number | 28.7 to 208.2 | count |
baseline_volume_k |
number | 5.6 to 31 | count |
prior_high_volume_k |
number | 13.1 to 225.8 | US dollars |
session_label |
text | 1 distinct value (Oct 6) | |
session_id |
number | every row is 20,261,006 | |
baseline_session_count |
number | every row is 20 | count |
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 tape AS (
SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d,
sum(toFloat64(volume)) AS vol
FROM global_markets.options_minute_aggs
WHERE window_start >= toDateTime(today() - 45, 'America/New_York')
GROUP BY d
),
ranked AS (
SELECT d, vol, row_number() OVER (ORDER BY d DESC) AS raw_rn
FROM tape
),
cal AS (
SELECT d, vol, rn, sum(if(rn BETWEEN 2 AND 21, 1, 0)) OVER () AS baseline_sessions
FROM (
SELECT d, vol, row_number() OVER (ORDER BY d DESC) AS rn
FROM ranked
WHERE vol >= 0.75 * (SELECT quantileExact(0.5)(vol) FROM ranked WHERE raw_rn > 1)
)
),
day_root AS (
SELECT substring(ticker, 3, length(ticker) - 17) AS root,
toDate(toTimeZone(window_start, 'America/New_York')) AS d,
sum(toFloat64(volume)) AS vol
FROM global_markets.options_minute_aggs
WHERE window_start >= toDateTime(today() - 45, 'America/New_York')
GROUP BY root, d
),
scored AS (
SELECT r.root AS root,
sumIf(r.vol, c.rn = 1) AS last_vol,
avgIf(r.vol, c.rn BETWEEN 2 AND 21) AS base_vol,
maxIf(r.vol, c.rn BETWEEN 2 AND 21) AS prior_high,
countIf(c.rn BETWEEN 2 AND 21) AS root_sessions,
max(c.baseline_sessions) AS baseline_session_count,
maxIf(toYYYYMMDD(c.d), c.rn = 1) AS session_id,
maxIf(formatDateTime(c.d, '%b %e'), c.rn = 1) AS session_label
FROM day_root r INNER JOIN cal c ON r.d = c.d
WHERE c.rn <= 21
AND r.root NOT IN ('SPCX')
AND r.root NOT IN ('KORU','SOXL','SOXS','TQQQ','SQQQ','NVDL','NVDS','NVD','TSLL','TSLQ','TSLZ','SPXL','SPXS','UPRO','SPXU','LABU','LABD','FAS','FAZ','TNA','TZA','YINN','YANG','UDOW','SDOW','BOIL','KOLD','UCO','SCO','USD','SSO','SDS','QLD','QID','ERX','ERY','DRN','DRV','CURE','SOXY','MUU','SNXX','UVXY','SVXY','UVIX','SVIX','BULZ','WEBL','WEBS','DPST','DRIP','GUSH','AGQ','ZSL','BITX','ETHU','MSTX','MSTU','CONL','DUST','JNUG','JDST','NUGT')
GROUP BY r.root
HAVING last_vol >= 25000 AND base_vol >= 5000 AND root_sessions >= 18
)
SELECT root AS ticker,
round(last_vol / base_vol, 1) AS vol_ratio,
round(last_vol / 1000, 1) AS session_volume_k,
round(base_vol / 1000, 1) AS baseline_volume_k,
round(prior_high / 1000, 1) AS prior_high_volume_k,
session_label,
session_id,
baseline_session_count
FROM scored
ORDER BY vol_ratio DESC, ticker ASC
LIMIT 10
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