Strasmore Research
市場回顧 Matt Connor作者： Matt Connor · 更新於 2026-09-05 · data as of September 5, 2026 · refreshed weekly

2026年漲幅最大與跌幅最深的股票排名

依交易所真實成交與流動性排名2026年漲跌幅最大的股票，剔除股票分割與槓桿型基金，查看哪些公司真正跑贏或落後市場。

2026年至今表現最佳的股票由 SNDK 領漲，從今年首個交易日開盤至最近一個已完成交易日上漲 536.4%。本頁根據交易所成交紀錄，而非資料供應商摘要，評比2026年真正有交易的股票中漲幅最大者與跌幅最大者，並會隨年度進展持續更新。排名前會先剔除股票分割與槓桿型基金，這正是多數年初至今排行榜容易出錯的地方。

2026年漲幅最大的股票

以下每檔股票在排名前，均先通過流動性門檻：過去一個月中，每個完整交易日的平均成交金額至少為1億美元。若一檔幾乎無人交易的股票出現很高的漲幅百分比，那只是報價，不代表實際交易結果。

查詢2026年漲幅最大的股票：截至目前交易量最大的股票中，年初至今排名前十
股票代碼年初至今報酬率 (%)日均成交金額（百萬美元）
SNDK536.415431
MRNA3995598
TWST305.4202
DELL301.83566
TXG287.5142
AEHR262.8208
MXL233.4114
AXTI226.9525
MU224.820455
AMLX183.5131
每個數據背後的精確 SQL 語法
WITH complete AS (
    SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= toDateTime('2026-01-01 00:00:00')
      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 count() >= 380
),
universe AS (
    SELECT ticker,
           sum(toFloat64(close) * toFloat64(volume)) / uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) AS adv
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE window_start >= now() - INTERVAL 21 DAY
      AND toDate(toTimeZone(window_start, 'America/New_York')) >= today() - 20
      AND toDate(toTimeZone(window_start, 'America/New_York')) IN (SELECT d FROM complete)
      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 ticker
    HAVING adv >= 100000000
),
edges AS (
    SELECT ticker,
        argMinIf(toFloat64(open), toTimeZone(window_start, 'America/New_York'), toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT min(d) FROM complete)) AS year_open,
        argMaxIf(toFloat64(close), toTimeZone(window_start, 'America/New_York'), toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT max(d) FROM complete)) AS latest_close,
        countIf(toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT min(d) FROM complete)) AS bars_open,
        countIf(toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT max(d) FROM complete)) AS bars_close
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ((window_start >= toDateTime('2026-01-01 00:00:00') AND window_start < toDateTime('2026-01-10 00:00:00'))
        OR (window_start >= now() - INTERVAL 8 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
      AND ticker NOT IN ('SPCX')
      AND ticker NOT IN ('KORU','SOXL','SOXS','SOXY','TQQQ','SQQQ','QQQU','SPXL','SPXS','UPRO','SPXU','SPYU','LABU','LABD','FAS','FAZ','TNA','TZA','YINN','YANG','UDOW','SDOW','BOIL','KOLD','UCO','SCO','USD','SSO','SDS','QLD','QID','ERX','ERY','DRN','DRV','CURE','MUU','SNXX','UVXY','SVXY','UVIX','SVIX','BULZ','WEBL','WEBS','DPST','DRIP','GUSH','AGQ','ZSL','GDXU','GDXD','FNGU','FNGD','DUST','JNUG','JDST','NUGT','BITX','BITU','SBIT','ETHU','ETHT','NVDL','NVDS','NVD','NVDX','NVDU','NVDD','NVDQ','TSLL','TSLQ','TSLZ','TSLR','TSLT','TSLS','TSDD','AAPU','AAPD','MSFU','MSFD','GGLL','GGLS','AMZU','AMZD','METU','METD','PLTU','PLTD','SMCX','SMCZ','CONL','CONI','MSTX','MSTU','MSTZ','BRKU','AMDL','AMUU','AMDD','ELIL','ELIS','HOOX','AVGX','AVGU','TSMX','TSMZ','MULL')
      AND ticker NOT IN (SELECT ticker FROM global_markets.stocks_splits
                         WHERE execution_date BETWEEN toDate('2026-01-01') AND today())
    GROUP BY ticker
    HAVING bars_open >= 100 AND bars_close >= 100
)
SELECT e.ticker AS ticker,
    round((e.latest_close / e.year_open - 1) * 100, 1) AS ytd_return_pct,
    round(u.adv / 1e6, 0) AS avg_daily_dollar_m
FROM edges AS e
INNER JOIN universe AS u ON e.ticker = u.ticker
WHERE e.year_open >= 10
ORDER BY (e.latest_close / e.year_open) DESC
LIMIT 10
自己執行這個查詢

SNDK以536.4%的漲幅領先全年，MRNA以399%居次，TWST以305.4%排名第三。榜單第十名的AMLX仍上漲183.5%，因此整張榜單的表現都遠遠超越任何廣泛型指數。

每檔股票旁的美元成交額欄位，資訊量不亞於漲幅百分比。AMLX的日均成交額約為131百萬美元。榜首SNDK的日均成交額為15431百萬美元。榜上每檔股票的日均成交額都超過1億美元，而高於這項門檻的區間相當寬，因此同樣的標題漲幅，在區間兩端代表的意義並不相同。成交清淡的股票較容易被推高，也較難以畫面上的價格出場。

2026年跌幅最大的股票

採用相同指標，但方向相反：在達到相同流動性門檻的股票中，統計年初至今跌幅最大的標的。

查詢2026年跌幅最大的股票：截至目前交易量最大的股票中，年初至今排名後十
股票代碼年初至今報酬率 (%)日均成交金額（百萬美元）
TTD-60.5192
WING-54.4103
APP-54.11257
CSGP-52.8144
FLUT-52.7140
STLA-51.5105
BSX-51763
KLAR-50.4145
RBLX-49.1303
JOBY-48.8153
每個數據背後的精確 SQL 語法
WITH complete AS (
    SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= toDateTime('2026-01-01 00:00:00')
      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 count() >= 380
),
universe AS (
    SELECT ticker,
           sum(toFloat64(close) * toFloat64(volume)) / uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) AS adv
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE window_start >= now() - INTERVAL 21 DAY
      AND toDate(toTimeZone(window_start, 'America/New_York')) >= today() - 20
      AND toDate(toTimeZone(window_start, 'America/New_York')) IN (SELECT d FROM complete)
      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 ticker
    HAVING adv >= 100000000
),
edges AS (
    SELECT ticker,
        argMinIf(toFloat64(open), toTimeZone(window_start, 'America/New_York'), toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT min(d) FROM complete)) AS year_open,
        argMaxIf(toFloat64(close), toTimeZone(window_start, 'America/New_York'), toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT max(d) FROM complete)) AS latest_close,
        countIf(toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT min(d) FROM complete)) AS bars_open,
        countIf(toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT max(d) FROM complete)) AS bars_close
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ((window_start >= toDateTime('2026-01-01 00:00:00') AND window_start < toDateTime('2026-01-10 00:00:00'))
        OR (window_start >= now() - INTERVAL 8 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
      AND ticker NOT IN ('SPCX')
      AND ticker NOT IN ('KORU','SOXL','SOXS','SOXY','TQQQ','SQQQ','QQQU','SPXL','SPXS','UPRO','SPXU','SPYU','LABU','LABD','FAS','FAZ','TNA','TZA','YINN','YANG','UDOW','SDOW','BOIL','KOLD','UCO','SCO','USD','SSO','SDS','QLD','QID','ERX','ERY','DRN','DRV','CURE','MUU','SNXX','UVXY','SVXY','UVIX','SVIX','BULZ','WEBL','WEBS','DPST','DRIP','GUSH','AGQ','ZSL','GDXU','GDXD','FNGU','FNGD','DUST','JNUG','JDST','NUGT','BITX','BITU','SBIT','ETHU','ETHT','NVDL','NVDS','NVD','NVDX','NVDU','NVDD','NVDQ','TSLL','TSLQ','TSLZ','TSLR','TSLT','TSLS','TSDD','AAPU','AAPD','MSFU','MSFD','GGLL','GGLS','AMZU','AMZD','METU','METD','PLTU','PLTD','SMCX','SMCZ','CONL','CONI','MSTX','MSTU','MSTZ','BRKU','AMDL','AMUU','AMDD','ELIL','ELIS','HOOX','AVGX','AVGU','TSMX','TSMZ','MULL')
      AND ticker NOT IN (SELECT ticker FROM global_markets.stocks_splits
                         WHERE execution_date BETWEEN toDate('2026-01-01') AND today())
    GROUP BY ticker
    HAVING bars_open >= 100 AND bars_close >= 100
)
SELECT e.ticker AS ticker,
    round((e.latest_close / e.year_open - 1) * 100, 1) AS ytd_return_pct,
    round(u.adv / 1e6, 0) AS avg_daily_dollar_m
FROM edges AS e
INNER JOIN universe AS u ON e.ticker = u.ticker
WHERE e.year_open >= 10
ORDER BY (e.latest_close / e.year_open) ASC
LIMIT 10
自己執行這個查詢

年初至今跌幅最大的是 TTD，跌幅為 -60.5%；其次是 WING，跌幅為 -54.4%。排名第十的 JOBY，跌幅為 -48.8%。這份名單中的若干標的是大型、廣泛持有的公司，而非投機性極高的小型股。這正是跌幅榜令人意外之處。流動性與分析師覆蓋並不能替股價設下底線。若投資人持有其中任何一檔股票，且其占投資組合比重過高，就會完整承受這段跌幅；持有單一股票的風險頁面則以波動率與回撤數據衡量這項風險。

2026年市場有多少部分上漲

排行榜只呈現兩端。市場廣度則展現整體：經篩選的全部標的，包括指數基金，如何依漲跌幅分組，分布在上漲與下跌兩側。

查詢年初至今市場廣度：篩選股票池在各報酬率區間的分布
區間名稱方向占比 (%)
Down 40%+1835.5
Down 20-40%6935.5
Down 10-20%7835.5
Down 0-10%16235.5
Up 0-10%15264.5
Up 10-25%19864.5
Up 25-50%14264.5
Up 50%+10364.5
每個數據背後的精確 SQL 語法
WITH complete AS (
    SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= toDateTime('2026-01-01 00:00:00')
      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 count() >= 380
),
universe AS (
    SELECT ticker,
           sum(toFloat64(close) * toFloat64(volume)) / uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) AS adv
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE window_start >= now() - INTERVAL 21 DAY
      AND toDate(toTimeZone(window_start, 'America/New_York')) >= today() - 20
      AND toDate(toTimeZone(window_start, 'America/New_York')) IN (SELECT d FROM complete)
      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 ticker
    HAVING adv >= 100000000
),
edges AS (
    SELECT ticker,
        argMinIf(toFloat64(open), toTimeZone(window_start, 'America/New_York'), toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT min(d) FROM complete)) AS year_open,
        argMaxIf(toFloat64(close), toTimeZone(window_start, 'America/New_York'), toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT max(d) FROM complete)) AS latest_close,
        countIf(toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT min(d) FROM complete)) AS bars_open,
        countIf(toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT max(d) FROM complete)) AS bars_close
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ((window_start >= toDateTime('2026-01-01 00:00:00') AND window_start < toDateTime('2026-01-10 00:00:00'))
        OR (window_start >= now() - INTERVAL 8 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
      AND ticker NOT IN ('SPCX')
      AND ticker NOT IN ('KORU','SOXL','SOXS','SOXY','TQQQ','SQQQ','QQQU','SPXL','SPXS','UPRO','SPXU','SPYU','LABU','LABD','FAS','FAZ','TNA','TZA','YINN','YANG','UDOW','SDOW','BOIL','KOLD','UCO','SCO','USD','SSO','SDS','QLD','QID','ERX','ERY','DRN','DRV','CURE','MUU','SNXX','UVXY','SVXY','UVIX','SVIX','BULZ','WEBL','WEBS','DPST','DRIP','GUSH','AGQ','ZSL','GDXU','GDXD','FNGU','FNGD','DUST','JNUG','JDST','NUGT','BITX','BITU','SBIT','ETHU','ETHT','NVDL','NVDS','NVD','NVDX','NVDU','NVDD','NVDQ','TSLL','TSLQ','TSLZ','TSLR','TSLT','TSLS','TSDD','AAPU','AAPD','MSFU','MSFD','GGLL','GGLS','AMZU','AMZD','METU','METD','PLTU','PLTD','SMCX','SMCZ','CONL','CONI','MSTX','MSTU','MSTZ','BRKU','AMDL','AMUU','AMDD','ELIL','ELIS','HOOX','AVGX','AVGU','TSMX','TSMZ','MULL')
      AND ticker NOT IN (SELECT ticker FROM global_markets.stocks_splits
                         WHERE execution_date BETWEEN toDate('2026-01-01') AND today())
    GROUP BY ticker
    HAVING bars_open >= 100 AND bars_close >= 100
),
rets AS (
    SELECT e.ticker AS ticker, (e.latest_close / e.year_open - 1) * 100 AS ret
    FROM edges AS e
    INNER JOIN universe AS u ON e.ticker = u.ticker
    WHERE e.year_open >= 10
)
SELECT bucket,
       names,
       round(100 * sum(names) OVER (PARTITION BY side) / sum(names) OVER (), 1) AS side_share_pct
FROM (
    SELECT tup.1 AS bucket, tup.2 AS names, tup.3 AS ord, tup.4 AS side
    FROM (
        SELECT arrayJoin([
            ('Down 40%+',   countIf(ret < -40),               1, 'down'),
            ('Down 20-40%', countIf(ret >= -40 AND ret < -20), 2, 'down'),
            ('Down 10-20%', countIf(ret >= -20 AND ret < -10), 3, 'down'),
            ('Down 0-10%',  countIf(ret >= -10 AND ret < 0),   4, 'down'),
            ('Up 0-10%',    countIf(ret >= 0 AND ret < 10),    5, 'up'),
            ('Up 10-25%',   countIf(ret >= 10 AND ret < 25),   6, 'up'),
            ('Up 25-50%',   countIf(ret >= 25 AND ret < 50),   7, 'up'),
            ('Up 50%+',     countIf(ret >= 50),                8, 'up')
        ]) AS tup
        FROM rets
    )
)
ORDER BY ord
自己執行這個查詢

經篩選的標的中，64.5%今年以來上漲，35.5%下跌。這種分布是前十大排行榜無法呈現的。漲幅一端有 18 個標的落在 Down 40%+ 區間，另一端則有 103 個標的落在 Up 50%+ 區間；相較之下，不變動上下兩側分別有 162 個標的位於 Down 0-10%，以及 152 個標的位於 Up 0-10%。在任何一年，多數市場標的都呈現一般性的走勢；上方兩張表中的標的則是構成平均值的例外。

市場本身的表現

單一股票的年度表現，放在整體市場的表現中比較，會呈現不同面貌。四檔主要指數 ETF 在完全相同期間的表現如下：

查詢四大主要指數 ETF：同一衡量期間的年初至今表現
標籤年初至今報酬率 (%)起始計算日截至計算日
Russell 2000 (IWM)19.22026-01-022026-09-03
Nasdaq 100 (QQQ)15.72026-01-022026-09-03
S&P 500 (SPY)12.72026-01-022026-09-03
Dow (DIA)11.42026-01-022026-09-03
每個數據背後的精確 SQL 語法
WITH complete AS (
    SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= toDateTime('2026-01-01 00:00:00')
      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 count() >= 380
),
edges AS (
    SELECT ticker,
        argMinIf(toFloat64(open), toTimeZone(window_start, 'America/New_York'), toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT min(d) FROM complete)) AS year_open,
        argMaxIf(toFloat64(close), toTimeZone(window_start, 'America/New_York'), toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT max(d) FROM complete)) AS latest_close,
        countIf(toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT min(d) FROM complete)) AS bars_open,
        countIf(toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT max(d) FROM complete)) AS bars_close
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ((window_start >= toDateTime('2026-01-01 00:00:00') AND window_start < toDateTime('2026-01-10 00:00:00'))
        OR (window_start >= now() - INTERVAL 8 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
      AND ticker IN ('SPY', 'QQQ', 'DIA', 'IWM')
    GROUP BY ticker
    HAVING bars_open >= 100 AND bars_close >= 100
)
SELECT multiIf(ticker = 'SPY', 'S&P 500 (SPY)', ticker = 'QQQ', 'Nasdaq 100 (QQQ)',
               ticker = 'DIA', 'Dow (DIA)', ticker = 'IWM', 'Russell 2000 (IWM)', ticker) AS label,
    round((latest_close / year_open - 1) * 100, 1) AS ytd_return_pct,
    (SELECT toString(min(d)) FROM complete) AS measured_from_date,
    (SELECT toString(max(d)) FROM complete) AS measured_through_date
FROM edges
ORDER BY ytd_return_pct DESC
自己執行這個查詢

上方的兩個表格與圖表，均以同一期間衡量：自2026年的第一個完整交易時段（2026-01-02）起，至最近一個已完成的交易時段（2026-09-03）止。在此期間，Russell 2000 (IWM)上漲19.2%，Dow (DIA)上漲11.4%。上漲股榜單中的每一檔股票，漲幅都大幅超越這四檔 ETF。這正是指數運作的算術結果：數百檔成分股的表現被平均為一條數據線，個別股票的漲跌會部分相互抵銷。該數據線背後的個股表現差距，遠大於指數本身的波動；上半年產業評分表則將十一個產業相互比較排名。

造成年初至今漲跌幅失真的股票分割

股票分割會改變流通股數與每股價格，但不會改變持股的價值。在這麼長的期間內，許多公司會進行股票分割；若未調整年初至今的計算方式，就會把每股價格的變化誤讀為績效。下列標的在2026年進行了股票分割或股票股利，幅度大到足以使價格變動至少五分之一；同時也都符合相同的流動性門檻。因此，在分割篩選條件排除這些標的前，它們原本都符合上方榜單的資格。

查詢排除項目：2026年足以扭曲年初至今漲跌幅的股票分割
股票代碼未調整年初至今 (%)分割價格影響 (%)分割類型分割日期
BKNG-96.4-96forward split2026-04-06
KLAC-86.3-90forward split2026-06-12
VGT-84.1-87.5forward split2026-04-21
CVNA-82.6-80forward split2026-05-08
VUG-81.9-83.3forward split2026-04-21
HDV-75.6-80forward split2026-04-29
IWF-74.1-75forward split2026-04-29
VO-71.7-75forward split2026-04-21
CRWD-54.6-75stock dividend2026-07-02
MNST-42.5-50stock dividend2026-08-11
APH-40.1-50stock dividend2026-09-03
MVLL4.3-66.7forward split2026-06-26
HON6.1100reverse split2026-06-29
DD224.3200reverse split2026-06-24
每個數據背後的精確 SQL 語法
WITH complete AS (
    SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= toDateTime('2026-01-01 00:00:00')
      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 count() >= 380
),
universe AS (
    SELECT ticker,
           sum(toFloat64(close) * toFloat64(volume)) / uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) AS adv
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE window_start >= now() - INTERVAL 21 DAY
      AND toDate(toTimeZone(window_start, 'America/New_York')) >= today() - 20
      AND toDate(toTimeZone(window_start, 'America/New_York')) IN (SELECT d FROM complete)
      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 ticker
    HAVING adv >= 100000000
),
split_terms AS (
    SELECT ticker,
        argMax(split_to, execution_date) AS new_shares,
        argMax(split_from, execution_date) AS old_shares,
        round((old_shares / new_shares - 1) * 100, 1) AS split_price_effect_pct,
        replaceAll(argMax(adjustment_type, execution_date), '_', ' ') AS split_type,
        toString(max(execution_date)) AS split_date
    FROM global_markets.stocks_splits
    WHERE execution_date BETWEEN toDate('2026-01-01') AND today()
    GROUP BY ticker
    HAVING new_shares > 0 AND old_shares > 0
       AND greatest(new_shares / old_shares, old_shares / new_shares) >= 1.25
),
edges AS (
    SELECT ticker,
        argMinIf(toFloat64(open), toTimeZone(window_start, 'America/New_York'), toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT min(d) FROM complete)) AS year_open,
        argMaxIf(toFloat64(close), toTimeZone(window_start, 'America/New_York'), toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT max(d) FROM complete)) AS latest_close,
        countIf(toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT min(d) FROM complete)) AS bars_open,
        countIf(toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT max(d) FROM complete)) AS bars_close
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ((window_start >= toDateTime('2026-01-01 00:00:00') AND window_start < toDateTime('2026-01-10 00:00:00'))
        OR (window_start >= now() - INTERVAL 8 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
      AND ticker NOT IN ('SPCX')
      AND ticker NOT IN ('KORU','SOXL','SOXS','SOXY','TQQQ','SQQQ','QQQU','SPXL','SPXS','UPRO','SPXU','SPYU','LABU','LABD','FAS','FAZ','TNA','TZA','YINN','YANG','UDOW','SDOW','BOIL','KOLD','UCO','SCO','USD','SSO','SDS','QLD','QID','ERX','ERY','DRN','DRV','CURE','MUU','SNXX','UVXY','SVXY','UVIX','SVIX','BULZ','WEBL','WEBS','DPST','DRIP','GUSH','AGQ','ZSL','GDXU','GDXD','FNGU','FNGD','DUST','JNUG','JDST','NUGT','BITX','BITU','SBIT','ETHU','ETHT','NVDL','NVDS','NVD','NVDX','NVDU','NVDD','NVDQ','TSLL','TSLQ','TSLZ','TSLR','TSLT','TSLS','TSDD','AAPU','AAPD','MSFU','MSFD','GGLL','GGLS','AMZU','AMZD','METU','METD','PLTU','PLTD','SMCX','SMCZ','CONL','CONI','MSTX','MSTU','MSTZ','BRKU','AMDL','AMUU','AMDD','ELIL','ELIS','HOOX','AVGX','AVGU','TSMX','TSMZ','MULL')
      AND ticker IN (SELECT ticker FROM split_terms)
    GROUP BY ticker
    HAVING bars_open >= 100 AND bars_close >= 100
),
ranked AS (
    SELECT e.ticker AS ticker,
        round((e.latest_close / e.year_open - 1) * 100, 1) AS unadjusted_ytd_pct,
        s.split_price_effect_pct AS split_price_effect_pct,
        s.split_type AS split_type,
        s.split_date AS split_date
    FROM edges AS e
    INNER JOIN split_terms AS s ON e.ticker = s.ticker
    WHERE e.year_open >= 10 AND e.ticker IN (SELECT ticker FROM universe)
)
SELECT ticker, unadjusted_ytd_pct, split_price_effect_pct, split_type, split_date
FROM (
    SELECT ticker, unadjusted_ytd_pct, split_price_effect_pct, split_type, split_date,
           row_number() OVER (ORDER BY unadjusted_ytd_pct ASC) AS rn_low,
           row_number() OVER (ORDER BY unadjusted_ytd_pct DESC) AS rn_high
    FROM ranked
)
WHERE rn_low <= 14 OR rn_high = 1
ORDER BY unadjusted_ytd_pct ASC
自己執行這個查詢

在未調整的篩選畫面中，BKNG在forward split使其每股價格變動-96%後，年初至今漲跌幅會顯示為-96.4%；KLAC則在forward split使其價格變動-90%後，會顯示為-86.3%。兩者的持有人都沒有因分割生效而在當日蒙受損失。每股價格按照相同比例除減，流通股數則按相同比例增加。分割影響欄單獨列出股票分割本身造成的價格變動，也就是未調整篩選畫面會誤讀為績效的部分。

面板最後一列呈現相反情況：DD在reverse split使其每股價格上升200%後，顯示為224.3%；分割提高了價格，而非壓低價格。任何略過這項調整的榜單，都會同時在排名頂端與底端發布失真的結果。因此，該篩選會將進行股票分割的 ticker 另行排除，而不是嘗試修補其價格。基金同樣可能出現在這個面板中，因為指數基金也會分割其股份；本篩選同時涵蓋公司與基金。

篩選方法

篩選的各個階段，以及通過該階段後仍入選的標的數量：

查詢篩選流程：各篩選條件後剩餘的股票數量
篩選步驟名稱
Traded the first and the last full session4471
Averaging $100m+ a day over the past month1000
Opened 2026 above $10 a share970
Not on the excluded-fund list938
No split or stock dividend in 2026922
每個數據背後的精確 SQL 語法
WITH complete AS (
    SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS d
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ticker = 'SPY'
      AND window_start >= toDateTime('2026-01-01 00:00:00')
      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 count() >= 380
),
universe AS (
    SELECT ticker
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE window_start >= now() - INTERVAL 21 DAY
      AND toDate(toTimeZone(window_start, 'America/New_York')) >= today() - 20
      AND toDate(toTimeZone(window_start, 'America/New_York')) IN (SELECT d FROM complete)
      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 ticker
    HAVING sum(toFloat64(close) * toFloat64(volume)) / uniqExact(toDate(toTimeZone(window_start, 'America/New_York'))) >= 100000000
),
edges AS (
    SELECT ticker,
        argMinIf(toFloat64(open), toTimeZone(window_start, 'America/New_York'), toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT min(d) FROM complete)) AS year_open,
        argMaxIf(toFloat64(close), toTimeZone(window_start, 'America/New_York'), toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT max(d) FROM complete)) AS latest_close,
        countIf(toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT min(d) FROM complete)) AS bars_open,
        countIf(toDate(toTimeZone(window_start, 'America/New_York')) = (SELECT max(d) FROM complete)) AS bars_close
    FROM global_markets.delayed_stocks_minute_aggs
    WHERE ((window_start >= toDateTime('2026-01-01 00:00:00') AND window_start < toDateTime('2026-01-10 00:00:00'))
        OR (window_start >= now() - INTERVAL 8 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 ticker
    HAVING bars_open >= 100 AND bars_close >= 100
),
flagged AS (
    SELECT ticker,
        year_open,
        ticker IN (SELECT ticker FROM universe) AS liquid,
        ticker NOT IN ('SPCX','KORU','SOXL','SOXS','SOXY','TQQQ','SQQQ','QQQU','SPXL','SPXS','UPRO','SPXU','SPYU','LABU','LABD','FAS','FAZ','TNA','TZA','YINN','YANG','UDOW','SDOW','BOIL','KOLD','UCO','SCO','USD','SSO','SDS','QLD','QID','ERX','ERY','DRN','DRV','CURE','MUU','SNXX','UVXY','SVXY','UVIX','SVIX','BULZ','WEBL','WEBS','DPST','DRIP','GUSH','AGQ','ZSL','GDXU','GDXD','FNGU','FNGD','DUST','JNUG','JDST','NUGT','BITX','BITU','SBIT','ETHU','ETHT','NVDL','NVDS','NVD','NVDX','NVDU','NVDD','NVDQ','TSLL','TSLQ','TSLZ','TSLR','TSLT','TSLS','TSDD','AAPU','AAPD','MSFU','MSFD','GGLL','GGLS','AMZU','AMZD','METU','METD','PLTU','PLTD','SMCX','SMCZ','CONL','CONI','MSTX','MSTU','MSTZ','BRKU','AMDL','AMUU','AMDD','ELIL','ELIS','HOOX','AVGX','AVGU','TSMX','TSMZ','MULL') AS not_geared,
        ticker NOT IN (SELECT ticker FROM global_markets.stocks_splits
                       WHERE execution_date BETWEEN toDate('2026-01-01') AND today()) AS no_split
    FROM edges
)
SELECT tup.1 AS screen_step, tup.2 AS names
FROM (
    SELECT arrayJoin([
        ('Traded the first and the last full session', count()),
        ('Averaging $100m+ a day over the past month', countIf(liquid)),
        ('Opened 2026 above $10 a share', countIf(liquid AND year_open >= 10)),
        ('Not on the excluded-fund list', countIf(liquid AND year_open >= 10 AND not_geared)),
        ('No split or stock dividend in 2026', countIf(liquid AND year_open >= 10 AND not_geared AND no_split))
    ]) AS tup
    FROM flagged
)
自己執行這個查詢

完整方法如下：

  • 觀察區間。 從2026年的第一個完整交易時段，到行情資料中最近一個完整交易時段。兩個端點都取自分鐘線資料；只有具備完整正常交易時段分鐘線數量的交易日才會計入，因此尚未結束的交易日不會被視為已完成。
  • 報酬率。 以年初第一個正常交易時段的開盤價，對比最後一個正常交易時段的收盤價，並根據分鐘線資料計算。不計入盤前與盤後成交。這是價格報酬率，不加回股息，因此高殖利率標的在此處的表現會略差於總報酬率所呈現的結果。
  • 流動性門檻。 過去20個日曆日內，每個正常交易時段的平均成交金額至少為1億美元，且只計入從開盤至收盤完整運作的交易時段。否則，部分交易時段的成交金額會被除以完整一天，導致所有標的的成交金額都被低估。這項單一篩選條件將標的範圍從4471個 ticker 縮減至1000個。
  • 價格門檻。 股票在年初開盤時的股價高於10美元。股價低於10美元的標的，往往只要小幅變動就會產生很大的百分比。
  • 槓桿型與反向基金透過一份人工整理的清單排除；該清單完整列在每張表格下方的 SQL 中。清單涵蓋以指數為標的的槓桿型基金，以及放大單一公司每日股價變動的單一股票基金。槓桿型基金可能在完全沒有公司新聞的情況下，登上原始漲跌幅排行榜。這份清單由人工維護，弱點也在於此：本月成立的基金，必須等有人將其加入清單後才會被排除。
  • 一般基金不予排除。 未使用槓桿的指數或產業 ETF，只要通過流動性與價格門檻，就會與營運公司一同排名，也會計入市場廣度統計。基金是由同一投資範圍內已計入的多個標的組成的一籃子，因此這些列應解讀為該籃子整體的表現，而不是單一公司的全年表現。
  • 分割。 任何在2026年內生效、進行股票分割或股票股利的 ticker，不論比例多小，一律另行排除。這是較保守的做法：它會讓少數真正表現出色的標的無法上榜，但也不會把股數變動公布為報酬率。上方面板顯示因分割幅度大到足以製造虛假漲幅而被排除的標的。
  • 晚近上市。 在年初第一個交易時段之後上市的公司沒有1月股價，因此不會出現在這些表格中；在新上市活動密集的年份，這確實形成資料缺口。
  • 結果。 共排名922個標的，其中前十名與後十名分別構成本頁的兩張榜單。

三個時間窗口的同一個問題

今年以來的表現是投資階梯中的一級，而股價走勢在不同期間下會呈現不同樣貌。本週視角是本週漲幅最大與跌幅最大的股票，本月視角是本月股價波動最大的股票，本頁則聚焦今年以來的表現。每一級的篩選門檻不同：本頁要求過去一個月平均每日成交額達1億美元；週榜與月榜則以各自期間內的累計成交額作為篩選標準。因此，某檔股票可能通過其中一個榜單的門檻，卻未能通過另一個榜單。某檔股票可能因一次財報後的市場反應登上週榜首位，但在全年排名中僅位居中段。若要了解今年以來更完整的市場脈絡，上半年市場回顧涵蓋指數、利率與產業板塊的細節；槓桿 ETF 如何運作則說明為何本頁排除槓桿型基金。

常見問題

2026年表現最佳的股票是哪一檔？

在日均交易額至少達1億美元、年初開盤價高於10美元、2026年未進行股票分割，且不在槓桿型基金名單內的股票中，SNDK是截至目前2026年表現最佳的股票，自年初第一個交易日上漲536.4%。MRNA排名第二，漲幅為399%。

2026年跌幅最大的股票有哪些？

在本篩選條件下，TTD是2026年表現最差的股票，跌幅為-60.5%；WING居次，跌幅為-54.4%。2026年跌幅最大的股票完整名單列於上方第二張表，並會隨年初至今的市場表現更新。

如何計算股票的年初至今報酬率？

年初至今報酬率，是比較最新價格與曆年年初價格，並將變化表示為百分比。本文採用2026年第一個正常交易時段的開盤價，與最近一個已完成交易時段的收盤價相比。年內進行股票分割的股票會予以排除，而不進行調整，因此讀者看到的價格資料與市場實際成交紀錄之間，不會插入任何調整因子。

2026年漲幅排行榜是否包含槓桿型 ETF？

不包含。槓桿型或反向基金會放大指數或單一股票的每日變動，因此即使沒有任何公司消息，也經常在原始漲跌幅排行榜中名列前茅。排名前會先依名稱排除這些基金，完整名單則可在各表格下方的 SQL 中查看。一般指數 ETF 與產業 ETF 則不同：它們和個股一樣，必須符合相同的篩選門檻，因此會納入排名，基金也可能出現在任一排行榜中。

本文每張表都是附有 SQL 的 stored query。展開任一面板即可稽核篩選條件，也可在 Strasmore terminal 上使用自訂門檻重新建立查詢。

#market movers#gainers and losers#year to date#stock splits#market breadth