Strasmore Research
Muhtasari wa soko Matt ConnorNa Matt Connor · Imeboreshwa 2026-07-24 · data as of July 24, 2026 · refreshed weekly

Hisa zinazopata faida na hasara zaidi 2026

Orodha ya hisa zinazofanya vizuri zaidi na zinazopata hasara kubwa mwaka wa 2026 kulingana na ukwasi wa soko, bila kujumuisha stock splits na leveraged funds.

Hapa kuna hisa zinazofanya vizuri zaidi mwaka wa 2026 hadi sasa, zikiongozwa na SNDK, ikiwa imepanda 554.9% tangu kikao cha kwanza cha mwaka hadi kikao cha hivi karibuni kilichokamilika. Ukurasa huu unaorodhesha hisa zinazopata faida kubwa na zinazopata hasara kubwa mwaka wa 2026 miongoni mwa majina yanayofanya biashara halisi, yakipimwa kupitia rekodi za soko badala ya muhtasari wa mtoa huduma, na unajifanya upya mwaka unapoendelea. Mgawanyo wa hisa (stock splits) na mifuko ya mkopo (leveraged funds) huondolewa kabla ya kuanza kuorodhesha, jambo ambalo ni sababu ya orodha nyingi za hadi sasa kukosea.

Hisani kubwa zaidi ya hisa za 2026

Kila jina hapa chini lilifikia kiwango cha ukwasi kabla ya kuorodheshwa: wastani wa angalau $100 million za hisa zilizobadilishwa mikono kwa kila kikao kilichokamilika katika mwezi uliopita. Asilimia kubwa kwenye hisa isiyofanyiwa biashara ni nukuu tu, siyo matokeo.

UlizaHisa zinazopata faida kubwa zaidi 2026: top ten YTD miongoni mwa majina yenye biashara nyingi
SQL halisi nyuma ya kila namba
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

SNDK inaongoza mwaka kwa 554.9%, huku MXL ikifuata kwa 386.3% na AEHR ikiwa ya tatu kwa 345%. Nafasi ya kumi kwenye orodha, AAOI, bado imepanda kwa 204.3%, hivyo jedwali zima limepiga hatua kubwa zaidi kuliko indeksi yoyote pana.

Safu ya dola kando ya kila mabadiliko ina taarifa nyingi kama asilimia. AAOI inafanya wastani wa takriban $817 million za mzunguko wa biashara kwa siku. SNDK iliyo juu ya orodha inafanya wastani wa $18348 million. Kila jina hapa linapita $100 million kwa siku, na tofauti kati ya kiwango hicho na juu yake ni kubwa kiasi kwamba asilimia ile ile inaweza kumaanisha mambo mawili tofauti kulingana na upande wake. Hisa yenye ukwasi mdogo ni rahisi kusukumwa lakini ni ngumu kutoka kwa bei iliyoonyeshwa kwenye skrini.

Hisa zilizoanguka zaidi mwaka wa 2026

Kipimo kilekile, kikiwa kimegeuzwa: kushuka kwa thamani kwa kiasi kikubwa zaidi tangu mwanzo wa mwaka miongoni mwa majina yanayovuka kiwango kilekile cha ukwasi.

UlizaHisa zinazopata hasara kubwa zaidi 2026: worst ten YTD miongoni mwa majina yenye biashara nyingi
SQL halisi nyuma ya kila namba
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

Kushuka kwa thamani kwa kiasi kikubwa zaidi tangu mwanzo wa mwaka ni kwa EOSE katika -65.9%, kikifuatiwa na CSGP katika -58.7%. Wa kumi kwenye orodha, TEAM, yuko katika -47.3%. Majina kadhaa hapa ni kampuni kubwa zinazomilikiwa na watu wengi badala ya kampuni ndogo za uvumbuzi, jambo ambalo ni la kushangiza katika orodha ya washindi wasiofanikiwa. Ukwasi na uchambuzi wa wataalamu hauwezi kuweka ukomo wa chini kwa bei ya hisa. Mtu yeyote anayemiliki moja ya hizi kama sehemu kubwa ya mkoba wake wa uwekezaji amepata athari kamili, ambayo ukurasa wa hatari ya kumiliki hisa moja unapima kwa kutumia takwimu za volatility na drawdown.

Ni kiasi gani cha soko kimepanda katika 2026

Jedwali la kiongozi huonyesha upande wa juu na chini pekee. Upana wa soko (breadth) huonyesha hali halisi: jinsi ulimwengu mzima uliochujwa, ikiwemo mifuko ya kieleuzi (index funds), ilivyo divided kati ya majina yanayopanda na yanayoshuka, kulingana na ukubwa wa mabadiliko.

UlizaBreadth YTD: usambazaji wa ulimwengu uliochujwa katika makundi ya faida
SQL halisi nyuma ya kila namba
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

61.9% ya majina yaliyochujwa yamepanda mwaka huu na 38.1% yamepungua. Usambazaji huu ndio unaoficha ukweli uliopo kwenye jedwali la juu kumi. 22 majina yako kwenye bucket ya Down 40%+ upande mmoja na 130 kwenye bucket ya Up 50%+ upande mwingine, dhidi ya 146 katika Down 0-10% na 159 katika Up 0-10% pande zote mbili za majina yasiyobadilika. Sehemu kubwa ya soko hufanya mabadiliko ya kawaida katika mwaka wowote, na majina kwenye majedwali mawili hapo juu ni mbali na wastani.

Hali ya soko kwa ujumla

Utendaji wa hisa moja kwa mwaka ni tofauti na hali ya soko kwa ujumla. Mifumo minne mikuu ya ETF, katika kipindi kilekile:

UlizaETF kuu nne za index, YTD, katika kipindi kilekile kilichopimwa
SQL halisi nyuma ya kila namba
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

Mbao zote na paneli lililo juu yote yamepimwa katika kipindi kimoja: kikao cha kwanza kamili cha 2026 (2026-01-02) hadi kikao cha hivi karibuni kilichokamilika (2026-07-22). Katika kipindi hicho Russell 2000 (IWM) ilirudisha 18.6% na Dow (DIA) ilirudisha 8.2%. Kila jina kwenye jedwali la wenye faida lilivuka mifumo hiyo minne kwa kiasi kikubwa, jambo linalotokana na mchanganuo wa index: mamia ya hisa zimeunganishwa kuwa mstari mmoja, ambapo mabadiliko ya kila hisa yanajighatua kiasi. Tofauti iliyo chini ya mstari huo ilikuwa kubwa zaidi kuliko mstari wenyewe, na mchanganuo wa sekta kwa nusu ya kwanza unaoanisha sekta zote kumi na moja.

The stock split that fakes a year-to-date move

A split changes the share count and the per-share price without changing what a holding is worth. Over a window this long many companies split, and an unadjusted year-to-date calculation reads the change in the per-share price as performance. The names below each carried a 2026 split or stock dividend large enough to move that price by at least a fifth, and each cleared the same liquidity floor, so each was eligible for the boards above before the split filter removed it.

UlizaZilizotolewa kwenye mbao: splits za 2026 zenye ukubwa wa kuleta upotofu wa YTD
SQL halisi nyuma ya kila namba
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

BKNG would print -96.7% on an unadjusted screen after a forward split moved its per-share price -96%, and CVNA would print -85.1% after a forward split moved its price -80%. No holder of either lost anything on the day the split took effect. The per-share price was divided and the share count was multiplied by the same factor. The split effect column isolates the price change the split alone accounts for, which is the part an unadjusted screen reads as performance.

The last row of the panel runs the other way: DD shows 245.3% after a reverse split lifted its per-share price 200%, raising the price instead of cutting it. Any list that skips this step publishes fiction at the top and the bottom simultaneously, which is why the screen sets split tickers aside rather than trying to patch their prices. A fund can land in this panel as easily as a company: index funds split their shares too, and this screen covers both.

Jinsi mchujio huu unavyopimwa

Kila hatua ya mchujio, pamoja na idadi ya majina yanayobaki baada ya hatua hiyo:

UlizaScreen, hatua kwa hatua: majina yanayobaki baada ya kila filter
SQL halisi nyuma ya kila namba
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
)

Njia inayotumika, ikiwa imeelezwa kikamilifu:

  • Kipindi cha muda. Kipindi cha kwanza kamili cha biashara cha 2026 hadi kipindi cha mwisho kamili kwenye tape. Ncha zote mbili husomwa kutoka kwenye minute bars. Kipindi kinajumuishwa tu ikiwa kina idadi kamili ya regular-hours bars, hivyo siku inayozingatia bado haichukuliwi kama imekamilika.
  • Faida (Return). Bei ya kufungua kipindi cha kwanza cha regular-session cha mwaka dhidi ya bei ya kufunga kwa kipindi cha mwisho cha regular-session, inayopatikana kutoka kwenye minute bars. Bei za premarket na after-hours hazijumuishwi. Hizi ni price returns; gawadi (dividends) hazijumlishwi, hivyo jina lenye high-yield litaonekana kuwa na matokeo duni kidogo hapa kuliko takwimu ya total-return.
  • Kiwango cha ukwasi (Liquidity floor). Wastani wa angalau $100 million ya turnover ya regular-hours kwa kila kipindi katika siku 20 za kalenda zilizopita, ikijumuisha vipindi vilivyofanya kazi kuanzia mwanzo hadi mwisho. Kipindi kisichokamilika kingegawanya sehemu ya dola za siku moja kwa siku nzima na kupunguza thamani ya turnover ya kila jina. Chujio hilo pekee linapunguza idadi ya tickers kutoka 4492 hadi 1036.
  • Kiwango cha bei (Price floor). Hisa ilifungua mwaka juu ya $10 kwa kila hisa. Majina yenye chini ya $10 hutoa asilimia kubwa kutokana na mabadiliko madogo ya bei.
  • Fedha za mkopo (Leveraged and inverse funds) zimeondolewa kupitia orodha iliyochujwa, iliyoonyeshwa kikamilifu kwenye SQL chini ya kila jedwali. Inajumuisha fedha zinazozingatia index na fedha za hisa moja zinazozidisha mabadiliko ya kila siku ya kampuni moja. Geared fund inaweza kuwa juu ya orodha yoyote ya movers bila hata habari moja ya kampuni. Orodha hii inadhibitiwa kwa mkono, jambo ambalo ni udhaifu wake: fund iliyoanzishwa mwezi huu itaondolewa tu baada ya mtu kuiongeza.
  • Fedha za kawaida hazichujwi. ETF ya index au sector isiyo na leverage inayopita viwango vya ukwasi na bei inapangwa hapa pamoja na kampuni zinazofanya kazi, na inajumuishwa pia katika hesabu za breadth. Fund ni kikundi cha majina ambayo tayari yamehesabiwa katika ulimwengu huo huo, hivyo soma safu hizo kama matokeo ya kikundi badala ya mwaka wa kampuni moja.
  • Mgawanyo wa hisa (Splits). Ticker yoyote yenye split au stock dividend inayotumika wakati wa 2026 inawekwa pembeni, hata kama ratio ni ndogo kiasi gani. Hii ni chaguo la tahadhari: inawapunguza baadhi ya wafanyaji vizuri nafasi kwenye ubao, na haichukui mabadiliko ya idadi ya hisa kama return. Panel iliyo juu inaonyesha majina yaliyofutwa ambayo split yao ilikuwa kubwa kiasi cha kuleta mabadiliko ya bandia.
  • Uorodheshaji wa late. Kampuni iliyoorodheshwa baada ya kipindi cha kwanza cha mwaka haina bei ya Januari na haipo kwenye majedwali haya, jambo ambalo ni pengo halisi katika mwaka wenye kalenda kubwa ya uorodheshaji mpya.
  • Matokeo. Majina 954 yanapangwa, na kumi ya juu na kumi ya chini ni mabodi mawili kwenye ukurasa huu.

Swali lile lile katika madirisha matatu

Kiwango cha mwaka hadi sasa ni ngazi moja, na mabadiliko yanaonekana tofauti kulingana na muda. Mtazamo wa wiki ni hisamali zinazopata faida na hasara kubwa zaidi wiki hii, mtazamo wa mwezi ni hisamali zinazocheza zaidi mwezi huu, na ukurasa huu ni wa mwaka. Viwango vya chini vinatofautiana kwa kila ngazi: ukurasa huu unachuja kwa wastani wa $100 million kwa siku katika mwezi uliopita, wakati kurasa za wiki na mwezi zinachuja kwa jumla ya thamani iliyofanyiwa biashara ndani ya madirisha yao, hivyo hisamali inaweza kufanya vizuri kwenye jedwali moja lakini ikashindwa lingine. Hisamali inayoshika nafasi ya kwanza kwenye jedwali la wiki kutokana na athari za mapato inaweza kuwa katikati ya jedwali kwa mwaka mzima. Kwa maelezo mapana zaidi ya soko hadi sasa, muhtasari wa soko wa nusu ya kwanza unatoa maelezo ya index, viwango vya riba, na sekta, na jinsi ETFs zenye leverage zinavyofanya kazi inaelezea kwa nini mifuko yenye leverage imewekwa kando hapa.

Maswali Yanayoulizwa Mara kwa Mara

Ni hisa gani yenye utendaji bora zaidi mwaka wa 2026?

Miongoni mwa majina yanayofanya biashara ya wastani wa angalau $100 million kwa siku, yanayofungua mwaka juu ya $10, yasiyo na split ya 2026 na yasiyokuwa kwenye orodha ya mifuko ya leveraged, SNDK ndiyo hisa yenye utendaji bora zaidi ya 2026 hadi sasa, ikiwa imepanda 554.9% tangu kikao cha kwanza cha mwaka. MXL inashika nafasi ya pili ikiwa imepanda 386.3%.

Ni hisa zipi zilizoshuka zaidi mwaka wa 2026?

EOSE ndiyo hisa yenye utendaji duni zaidi ya 2026 kwenye kigezo hiki ikiwa imeshuka -65.9%, ikimtanguliza CSGP aliye katika -58.7%. Orodha kamili ya hisa zinazopoteza thamani zaidi mwaka wa 2026 ipo kwenye jedwali la pili hapo juu, inayofanyiwa maboresho kadiri mwaka unavyoendelea.

Faida ya hisa ya mwaka hadi sasa (year-to-date) inatungwa vipi?

Faida ya mwaka hadi sasa inalinganisha bei ya hivi karibuni na bei ya mwanzoni mwa mwaka wa kalenda na kuonyesha mabadiliko hayo kama asilimia. Hapa inalinganishwa bei ya kufungua kikao cha kawaida cha kwanza cha 2026 dhidi ya bei ya kufunga ya kikao cha hivi karibuni kilichokamilika. Hisa ambazo zilifanya split wakati wa mwaka hazijaliwi badala ya kurekebishwa, hivyo hakuna kigezo cha marekebisho kati ya msomaji na data ya soko.

Je, ETFs za leveraged zimejumuishwa kwenye orodha ya washindi wa 2026?

Hapana. Mfuko wa leveraged au inverse unazidisha mabadiliko ya kila siku ya index au hisa moja, hivyo mara nyingi hufika juu ya orodha ya washindi bila kuwa na habari yoyote ya kampuni nyuma yake. Mifuko hiyo huondolewa kwa jina kabla ya kupanga nafasi, na orodha hiyo inaonekana kwenye SQL chini ya kila jedwali. ETFs za kawaida za index na sector ni tofauti: hupita vigezo vilevile kama hisa nyingine na hupangwa hapa, hivyo mfuko unaweza kuonekana kwenye bodi yoyote.

Kila jedwali hapa ni query iliyohifadhiwa ikiwa na SQL yake iliyoambatishwa. Panua jopo lolote ili kukagua kigezo, au ujenzi upya kwa kutumia vigezo vyako kwenye terminal ya Strasmore.

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