Santa Claus window vs. the rest of December vs. the whole month, SPY, all years on record
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 2026-11-01, from Santa Claus Rally: Hit Rate and Returns by Year.
| label | years_measured | up_years | hit_rate_pct | mean_pct | median_pct | worst_pct | worst_year |
|---|---|---|---|---|---|---|---|
| Santa Claus window | 23 | 16 | 69.6 | 0.61 | 0.53 | -2.9 | 2014 |
| December before the window | 23 | 17 | 73.9 | 0.21 | 0.85 | -12.68 | 2018 |
| Calendar December | 23 | 15 | 65.2 | 0.45 | 0.7 | -9.33 | 2018 |
- Rows × columns
- 3 × 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 |
|---|---|---|---|
label |
text | 3 distinct values | |
years_measured |
number | every row is 23 | |
up_years |
number | 15 to 17 | |
hit_rate_pct |
number | 65.2 to 73.9 | percent |
mean_pct |
number | 0.21 to 0.61 | percent |
median_pct |
number | 0.53 to 0.85 | percent |
worst_pct |
number | -12.68 to -2.9 | percent |
worst_year |
text | 2 distinct values (2014, 2018) |
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_days AS
(
SELECT
date,
toYear(date) AS y,
toMonth(date) AS m,
argMax(toFloat64(close), _ingest_time) AS close
FROM global_markets.stocks_daily_aggs
WHERE ticker = 'SPY'
AND toMonth(date) IN (11, 12, 1)
GROUP BY date
),
ranked AS
(
SELECT
date,
y,
m,
close,
row_number() OVER (PARTITION BY y, m ORDER BY date DESC) AS sessions_from_end,
row_number() OVER (PARTITION BY y, m ORDER BY date ASC) AS sessions_from_start
FROM spy_days
),
windows AS
(
SELECT
toUInt16(if(m = 1, y - 1, y)) AS year,
anyIf(close, m = 11 AND sessions_from_end = 1) AS november_close,
anyIf(close, m = 12 AND sessions_from_end = 6) AS base_close,
anyIf(close, m = 12 AND sessions_from_end = 1) AS december_close,
anyIf(close, m = 1 AND sessions_from_start = 2) AS end_close
FROM ranked
GROUP BY year
HAVING countIf(m = 11 AND sessions_from_end = 1) = 1
AND countIf(m = 12 AND sessions_from_end = 6) = 1
AND countIf(m = 1 AND sessions_from_start = 2) = 1
),
unpivoted AS
(
SELECT
year,
arrayJoin([
('Santa Claus window', (end_close / base_close - 1) * 100),
('December before the window', (base_close / november_close - 1) * 100),
('Calendar December', (december_close / november_close - 1) * 100)
]) AS pair,
tupleElement(pair, 1) AS label,
tupleElement(pair, 2) AS return_pct
FROM windows
)
SELECT
label,
count() AS years_measured,
countIf(return_pct > 0) AS up_years,
round(countIf(return_pct > 0) * 100 / count(), 1) AS hit_rate_pct,
round(avg(return_pct), 2) AS mean_pct,
round(quantileDeterministic(0.5)(return_pct, toUInt32(year)), 2) AS median_pct,
round(min(return_pct), 2) AS worst_pct,
toString(argMin(year, return_pct)) AS worst_year
FROM unpivoted
GROUP BY label
ORDER BY label DESC
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