Strongest and weakest sleeve versus SPY, by calendar month
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 2026-09-26, from ETF Relative Strength and Alpha Attribution.
| month | leading_etf | leader_excess_pct | laggard_excess_pct |
|---|---|---|---|
| 2025-08 | IWM | 5.67 | -5.48 |
| 2025-09 | GLD | 5.13 | -5.35 |
| 2025-10 | XLK | 3.61 | -3.95 |
| 2025-11 | XLV | 9.13 | -5.2 |
| 2025-12 | XLF | 3.31 | -3.78 |
| 2026-01 | XLE | 10.54 | -4 |
| 2026-02 | GLD | 14.61 | -3.46 |
| 2026-03 | XLE | 12.65 | -6.93 |
| 2026-04 | XLK | 8.55 | -12.91 |
| 2026-05 | XLK | 13.04 | -9.55 |
| 2026-06 | XLV | 8.87 | -8.87 |
| 2026-07 | XLE | 12.59 | -5.7 |
| 2026-08 | GLD | 8.64 | -6.04 |
- Rows × columns
- 13 × 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 |
|---|---|---|---|
month |
text | 13 distinct values (2025-08, 2025-09, 2025-10…) | |
leading_etf |
text | 6 distinct values (GLD, IWM, XLE…) | |
leader_excess_pct |
number | 3.31 to 14.61 | percent |
laggard_excess_pct |
number | -12.91 to -3.46 | 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 monthly AS
(
SELECT
toStartOfMonth(date) AS m,
ticker,
argMin(toFloat64(close), date) AS first_close,
argMax(toFloat64(close), date) AS last_close
FROM global_markets.stocks_daily_aggs
WHERE ticker IN ('SPY', 'QQQ', 'IWM', 'XLK', 'XLE', 'XLF', 'XLV', 'XLU', 'GLD', 'EFA')
AND date >= toStartOfMonth(today() - 400)
AND date < toStartOfMonth(today())
GROUP BY m, ticker
)
SELECT
formatDateTime(x.m, '%Y-%m') AS month,
argMax(x.ticker, x.excess_pct) AS leading_etf,
round(max(x.excess_pct), 2) AS leader_excess_pct,
round(min(x.excess_pct), 2) AS laggard_excess_pct
FROM
(
SELECT
sleeve.m AS m,
sleeve.ticker AS ticker,
(sleeve.last_close / sleeve.first_close - 1) * 100
- (bench.spy_last / bench.spy_first - 1) * 100 AS excess_pct
FROM monthly AS sleeve
INNER JOIN
(
SELECT
m,
first_close AS spy_first,
last_close AS spy_last
FROM monthly
WHERE ticker = 'SPY'
) AS bench USING (m)
WHERE sleeve.ticker != 'SPY'
) AS x
GROUP BY x.m
ORDER BY x.m
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