Qualifying large caps as the distance band and the P/E ceiling widen
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 2026-08-22, from Low P/E Stocks Near 52-Week Lows.
| distance_band | names_pe_under_15 | names_pe_under_25 |
|---|---|---|
| within 5% | 1 | 12 |
| within 10% | 9 | 37 |
| within 15% | 21 | 64 |
| within 20% | 31 | 91 |
| within 25% | 41 | 116 |
| within 30% | 45 | 143 |
- Rows × columns
- 6 × 3
- 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 |
|---|---|---|---|
distance_band |
text | 6 distinct values (within 10%, within 15%, within 20%…) | |
names_pe_under_15 |
number | 1 to 45 | |
names_pe_under_25 |
number | 12 to 143 |
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.
the exact SQL behind every number
WITH ratios AS
(
SELECT
ticker,
argMax(price_to_earnings, date) AS pe,
argMax(market_cap, date) AS mcap,
argMax(average_volume, date) AS adv
FROM global_markets.stocks_ratios
WHERE date >= today() - 14
AND ticker NOT IN ('SPCX')
GROUP BY ticker
),
band AS
(
SELECT
ticker,
min(low) AS low_52w,
argMax(close, date) AS last_close
FROM global_markets.stocks_daily_aggs
WHERE date >= today() - 372
AND ticker NOT IN ('SPCX')
GROUP BY ticker
),
universe AS
(
SELECT
b.ticker AS ticker,
toFloat64(b.last_close) / toFloat64(b.low_52w) * 100 - 100 AS pct_above_low,
r.pe AS pe
FROM band AS b
INNER JOIN ratios AS r ON r.ticker = b.ticker
WHERE r.mcap >= 10000000000
AND r.adv >= 1000000
AND r.pe > 0
AND b.low_52w > 0
)
SELECT
concat('within ', toString(cutoff), '%') AS distance_band,
countIf(pct_above_low <= cutoff AND pe <= 15) AS names_pe_under_15,
countIf(pct_above_low <= cutoff AND pe <= 25) AS names_pe_under_25
FROM
(
SELECT
pct_above_low,
pe,
arrayJoin([5, 10, 15, 20, 25, 30]) AS cutoff
FROM universe
)
GROUP BY cutoff
ORDER BY cutoff
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