STRASMORE/EXPLORE 3,293 QUERIES

trend_months

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 2026-09-16, from soxl-and-soxs-volatility-decay.

as of table 17×5read in context →
trend_months — 17 rows by 5 columns, computed from US exchange, SIP and OPRA data.
labelindex_pctthree_x_pctsoxl_pctsoxl_gap_pct
2026年4月40.4121.216543.8
2026年5月23.37076.76.7
2025年6月16.549.455.35.9
2023年11月16.148.353.14.8
2025年9月10.531.633.82.2
2023年1月164850.22.1
2026年1月1545472
2022年7月16.549.551.41.8
2023年5月15.74748.61.6
2023年12月12.236.537.71.2
2024年2月11.333.833.5-0.3
2023年3月8.525.524.9-0.6
2024年5月9.428.127.3-0.8
2025年5月11.534.433-1.5
2022年11月18.956.654.9-1.6
2025年10月13.139.237.1-2.1
2026年6月12.637.818.9-18.9
Rows × columns
17 × 5
Computed
Completeness
No missing values
Source
US exchange, SIP and OPRA market data
Licence
Strasmore terms · free, no signup
Formats
JSON · CSV · the SQL below

What each column holds

Column definitions for trend_months, derived from the stored result.
ColumnTypeRangeNotes
label text 17 distinct values (2022年11月, 2022年7月, 2023年11月…)
index_pct number 8.5 to 40.4 percent
three_x_pct number 25.5 to 121.2 percent
soxl_pct number 18.9 to 165 percent
soxl_gap_pct number -18.9 to 43.8 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
daily AS
(
    SELECT
        ticker,
        date,
        anyLast(toFloat64(close)) AS c
    FROM global_markets.stocks_daily_aggs
    WHERE ticker IN ('SOXX', 'SOXL', 'SOXS')
      AND date >= '2021-12-15'
      AND date <  '2026-09-01'
    GROUP BY ticker, date
),
lagged AS
(
    SELECT
        ticker,
        date,
        c,
        lagInFrame(c, 1) OVER (PARTITION BY ticker ORDER BY date ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS prev_c
    FROM daily
),
rets AS
(
    SELECT
        ticker,
        date,
        c / prev_c - 1 AS r
    FROM lagged
    WHERE prev_c > 0
      AND abs(c / prev_c - 1) < 0.75
      AND date >= '2022-01-01'
      AND (ticker, date) NOT IN
      (
          SELECT ticker, toDate(execution_date)
          FROM global_markets.stocks_splits
          WHERE ticker IN ('SOXX', 'SOXL', 'SOXS')
      )
),
monthly AS
(
    SELECT
        toStartOfMonth(date)                        AS m,
        exp(sumIf(log(1 + r), ticker = 'SOXX')) - 1 AS soxx,
        exp(sumIf(log(1 + r), ticker = 'SOXL')) - 1 AS soxl,
        exp(sumIf(log(1 + r), ticker = 'SOXS')) - 1 AS soxs
    FROM rets
    GROUP BY m
    HAVING countIf(ticker = 'SOXX') >= 15
       AND countIf(ticker = 'SOXL') >= 15
       AND countIf(ticker = 'SOXS') >= 15
)
SELECT
    concat(toString(toYear(m)), '年', toString(toMonth(m)), '月') AS label,
    round(soxx * 100, 1)                                        AS index_pct,
    round(soxx * 300, 1)                                        AS three_x_pct,
    round(soxl * 100, 1)                                        AS soxl_pct,
    round((soxl - 3 * soxx) * 100, 1)                           AS soxl_gap_pct
FROM monthly
WHERE soxx > 0.08
ORDER BY soxl_gap_pct DESC
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