STRASMORE/EXPLORE 2,170 QUERIES

Biggest stock gainers this month (companies trading $1B+ over the window)

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 2026-08-25, from Biggest Stock Movers This Month.

as of ranking 10×3read in context →
Biggest stock gainers this month (companies trading $1B+ over the window) — 10 rows by 3 columns, computed from US exchange, SIP and OPRA data.
tickermonth_return_pctmonth_dollar_bn
MRNA193.929
AMLX110.61.6
TEAM92.413.3
HTFL80.71.2
RNG69.92.5
U56.68.9
FBRX53.53.1
P53.14.8
PAYC52.93.3
CACI492.9
Rows × columns
10 × 3
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 Biggest stock gainers this month (companies trading $1B+ over the window), derived from the stored result.
ColumnTypeRangeNotes
ticker text 10 distinct values (AMLX, CACI, FBRX…)
month_return_pct number 49 to 193.9 percent
month_dollar_bn number 1.2 to 29

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 window_days AS (
    SELECT d
    FROM (
        SELECT d, max(d) OVER () AS last_full
        FROM (
            SELECT d
            FROM (
                SELECT d, bars, medianExact(bars) OVER () AS typical_bars
                FROM (
                    SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d, count() AS bars
                    FROM global_markets.delayed_stocks_minute_aggs
                    WHERE window_start >= now() - INTERVAL 34 DAY
                      AND toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York')) >= 570
                      AND toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York')) < 960
                    GROUP BY d
                    HAVING d < toDate(toTimeZone(now(), 'America/New_York'))
                )
            )
            WHERE bars >= 0.85 * typical_bars
        )
    )
    WHERE d > last_full - 30
)
SELECT ticker,
       round((argMax(c, d) / argMin(o, d) - 1) * 100, 1) AS month_return_pct,
       round(sum(dollars) / 1e9, 1) AS month_dollar_bn
FROM (
    SELECT ticker,
           toDate(toTimeZone(window_start, 'America/New_York')) AS d,
           argMin(toFloat64(open), window_start) AS o,
           argMax(toFloat64(close), window_start) AS c,
           sum(toFloat64(close) * toFloat64(volume)) AS dollars
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE window_start >= now() - INTERVAL 34 DAY
      AND toDate(toTimeZone(window_start, 'America/New_York')) IN (SELECT d FROM window_days)
      AND toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York')) >= 570
      AND toHour(toTimeZone(window_start, 'America/New_York')) * 60 + toMinute(toTimeZone(window_start, 'America/New_York')) < 960
      AND ticker NOT IN ('SPCX')
      AND ticker NOT IN ('KORU','SOXL','SOXS','TQQQ','SQQQ','NVDL','NVDS','NVD','TSLL','TSLQ','TSLZ','SPXL','SPXS','UPRO','SPXU','LABU','LABD','FAS','FAZ','TNA','TZA','YINN','YANG','UDOW','SDOW','BOIL','KOLD','UCO','SCO','USD','SSO','SDS','QLD','QID','ERX','ERY','DRN','DRV','CURE','SOXY','MUU','SNXX','UVXY','SVXY','UVIX','SVIX','BULZ','WEBL','WEBS','DPST','DRIP','GUSH','AGQ','ZSL','BITX','ETHU','MSTX','MSTU','CONL','DUST','JNUG','JDST','NUGT')
      AND ticker IN (SELECT ticker FROM global_markets.stocks_ratios
                     WHERE market_cap > 0)
      AND ticker NOT IN (SELECT ticker FROM global_markets.stocks_splits
                         WHERE execution_date BETWEEN today() - 45 AND today())
    GROUP BY ticker, d
)
GROUP BY ticker
HAVING sum(dollars) >= 1000000000 AND argMin(o, d) >= 10 AND count() >= 15
ORDER BY argMax(c, d) / argMin(o, d) DESC
LIMIT 10

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