SPY move from Tuesday close to Friday close, the age of a COT snapshot
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 2026-09-20, from How to Read the COT Report: Columns Explained.
| year | session_pair_count | median_gap_move_pct | p90_gap_move_pct |
|---|---|---|---|
| 2016 | 51 | 0.88 | 2.2 |
| 2017 | 50 | 0.33 | 1.11 |
| 2018 | 50 | 1.14 | 2.71 |
| 2019 | 51 | 0.88 | 2.35 |
| 2020 | 48 | 1.24 | 4.21 |
| 2021 | 50 | 0.75 | 2.08 |
| 2022 | 51 | 1.72 | 4.32 |
| 2023 | 50 | 0.88 | 2.8 |
| 2024 | 52 | 1.04 | 2.17 |
| 2025 | 50 | 0.84 | 2.43 |
| 2026 | 23 | 1.26 | 2.92 |
- Rows × columns
- 11 × 4
- 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 |
|---|---|---|---|
year |
text | 11 distinct values (2016, 2017, 2018…) | |
session_pair_count |
number | 23 to 52 | count |
median_gap_move_pct |
number | 0.33 to 1.72 | percent |
p90_gap_move_pct |
number | 1.11 to 4.32 | 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 spy AS
(
SELECT
date,
toFloat64(close) AS close_px
FROM global_markets.stocks_daily_aggs
WHERE ticker = 'SPY'
AND date >= '2016-01-01'
AND date < '2026-07-01'
)
SELECT
toString(toYear(tue.date)) AS year,
count() AS session_pair_count,
round(quantileDeterministic(0.5)(abs(fri.close_px / tue.close_px - 1) * 100,
toUInt64(toUnixTimestamp(tue.date))), 2) AS median_gap_move_pct,
round(quantileDeterministic(0.9)(abs(fri.close_px / tue.close_px - 1) * 100,
toUInt64(toUnixTimestamp(tue.date))), 2) AS p90_gap_move_pct
FROM spy AS tue
INNER JOIN spy AS fri ON fri.date = tue.date + 3
WHERE toDayOfWeek(tue.date) = 2
GROUP BY year
ORDER BY year
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