Eight declared sector baskets, three names each: July 9 close-over-close, equal-weighted
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 2026-07-26, from Market Recap: July 9, 2026, The Day in Numbers.
| sector | names | avg_pct_chg | worst_name_pct | best_name_pct | gap_to_best_sector_pct |
|---|---|---|---|---|---|
| Semiconductors | 3 | 4.24 | 3.2 | 5.68 | 0 |
| Financials | 3 | 1.88 | 1.46 | 2.61 | -2.36 |
| Industrials | 3 | 0.42 | -1 | 1.4 | -3.82 |
| Healthcare | 3 | 0.22 | -1.62 | 1.41 | -4.02 |
| Big tech | 3 | 0.17 | -0.76 | 0.93 | -4.07 |
| Staples | 3 | -0.91 | -1.04 | -0.75 | -5.15 |
| Utilities | 3 | -0.96 | -1.28 | -0.41 | -5.21 |
| Energy | 3 | -2.01 | -2.54 | -1.06 | -6.25 |
- Rows × columns
- 8 × 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 |
|---|---|---|---|
sector |
text | 8 distinct values (Big tech, Energy, Financials…) | |
names |
number | every row is 3 | |
avg_pct_chg |
number | -2.01 to 4.24 | percent |
worst_name_pct |
number | -2.54 to 3.2 | percent |
best_name_pct |
number | -1.06 to 5.68 | percent |
gap_to_best_sector_pct |
number | -6.25 to 0 | 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.
SELECT
sector,
count() AS names,
round(avg(pct_chg), 2) AS avg_pct_chg,
round(min(pct_chg), 2) AS worst_name_pct,
round(max(pct_chg), 2) AS best_name_pct,
round(avg(pct_chg) - max(avg(pct_chg)) OVER (), 2) AS gap_to_best_sector_pct
FROM (
SELECT
ticker,
multiIf(ticker IN ('AMD', 'AVGO', 'KLAC'), 'Semiconductors',
ticker IN ('AAPL', 'MSFT', 'GOOGL'), 'Big tech',
ticker IN ('JPM', 'BAC', 'GS'), 'Financials',
ticker IN ('CAT', 'HON', 'GE'), 'Industrials',
ticker IN ('XOM', 'CVX', 'COP'), 'Energy',
ticker IN ('JNJ', 'UNH', 'PFE'), 'Healthcare',
ticker IN ('KO', 'PG', 'WMT'), 'Staples',
'Utilities') AS sector,
(toFloat64(argMaxIf(close, window_start, window_start >= '2026-07-09 13:30:00' AND window_start < '2026-07-09 20:00:00'))
/ toFloat64(argMaxIf(close, window_start, window_start >= '2026-07-08 13:30:00' AND window_start < '2026-07-08 20:00:00')) - 1) * 100 AS pct_chg
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker IN ('AMD', 'AVGO', 'KLAC', 'AAPL', 'MSFT', 'GOOGL', 'JPM', 'BAC', 'GS', 'CAT', 'HON', 'GE',
'XOM', 'CVX', 'COP', 'JNJ', 'UNH', 'PFE', 'KO', 'PG', 'WMT', 'NEE', 'DUK', 'SO')
AND window_start >= '2026-07-08 13:30:00' AND window_start < '2026-07-09 20:00:00'
GROUP BY ticker
)
GROUP BY sector
ORDER BY avg_pct_chg DESC
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