摩根士丹利-全球科技：创新下一代存储器-Innovating the Next-Generation Memory-20260716

Morganstanley

RESEARCHGLoBALlNslGHT

July16,202601:22AMGMT

GlobalTechnology

InnovatingtheNext-GenerationMemory

RisingAI-drivenmemorydemandislikelytoacceleratethedevelopmentofnext-genmemories.AsAIsystemsscale,constraintsincreasinglyextendbeyondcomputetotheefficientstorage,movement,andaccessofdata.Weidentifywherethenextwaveofdifferentiation,growthandalphacouldemerge.

MorganStanleydoesandseekstodobusinesswithcompaniescoveredinMorganStanleyResearch.Asaresult,investorsshouldbeawarethatthefirmmayhaveaconflictofinterestthatcouldaffecttheobjectivityofMorganStanleyResearch.InvestorsshouldconsiderMorganStanleyResearchasonlyasinglefactorinmakingtheirinvestment

decision.

Foranalystcertificationandotherimportantdisclosures,refertotheDisclosureSection,locatedattheendofthisreport.

+=Analystsemployedbynon-U.S.affiliatesarenotregisteredwithFINRA,maynotbeassociatedpersonsofthememberandmaynotbesubjecttoFINRArestrictionsoncommunicationswithasubjectcompany,publicappearancesandtradingsecuritiesheldbyaresearchanalystaccount.

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Morganstanley

RESEARCH

GLoBALINsiGHt

INDustRyViEw

GreaterChinaTechnologySemiconductors|AsiaPacific

Attractive

WHAT’sCHANGED

From

MontageTechnologyCoLtd(6809.HK)PriceTargetHK$310.00

MontageTechnologyCoLtd(688008.SS)PriceTargetRmb274.00

To

HK$432.00

Rmb377.00

KeyTakeaways

•AIcomputepowercontinuestoimproverapidly,butmemorycapacityremainsconstrained,bandwidthislimited,andcostsareelevated.

•Thisreportaddressesthissimplebutcriticalquestion:howcantheindustryovercomethememorybottlenecksoAIcancontinuetoscale?

•ThechallengeextendswellbeyondHBM.Innovationwillberequiredacrossdesign,process,packaging,peripherals,integrationandmaterials.

•Enablersoftheentirememoryecosystem,acrossinterface,connectivity,packaging,systemdesign,couldseere-ratingopportunities—notjusttraditionalmemoryvendors.

AIisenteringanewphase,withthefocusshiftingfromcomputescalingtodataefficiency:GenerativeAIhasdrivenstrongHBMdemand,andagenticAIissettofurtherincreasememoryrequirements

(RiseoftheAIAgent–GlobalImplications)

.IfGPUsdeterminehowfastAIcanrun,memorydetermineshowfaritcanscale.

Memoryisbecomingakeymonetizationpillar,wethink,withagenticAIpotentiallydriving26–77%ofincrementalDRAMdemandby2030.Basedonourcurrent

forecasts,cloudmemoryspendingcouldreachUS$418bnby2030,implying8%CAGRfrom2026.

Thememorywallisemergingasakeybottleneck,drivenbyconstraintsin

capacity,bandwidthandcost:WhileAImodelscontinuetoscale,memorysupplyisstrugglingtokeeppace,creatingstructuralimbalances.Weestimatememory

spendingcouldaccountfor40%ofcloudcapexin2027,upfrom12%in2023priortotheAI-drivencloudcapexboom,whilecapex-to-EBITDAcouldreach88.2%in

2027vs32.4%in2017.Atthesametime,memorybandwidthimprovements(+14%,from44.8GB/sperchannelin2024forDDR5-5600to51.2GB/sperchannelin

2026forDDR5-6400)stilllagtokengrowth(over320x,10TtokenspermonthinApr2024vs3,200TinJune2026forGCP),andcurrentcostlevelsalsolimitedgeAIdeployment.Together,thesetrendssuggestthechallengeisincreasingly

systemicratherthanincremental.

Addressingthebottleneckrequiressystem-levelinnovationratherthan

incrementalscaling:Historically,theintroductionof3DNANDdemonstratedhowmemoryinnovationcanovercomestructuralconstraintsbyimprovingstorage

densityandenablingend-marketexpansion,whilealsoreshapingthesupplychain.Similarly,webelievetoday’schallengeisnotjustacomponent-levellimitation,butabroadersystemconstrainttiedtohowdataisstored,movedandaccessed,

makingmemoryacentralconsiderationacrosstheAIstack.

Howshouldinvestorsthinkaboutthefutureofmemoryinnovation?Weidentifysixkeyvectors:design,process,packaging,peripherals,integration,andmaterials.Whilenodemigrationremainsimportant,otherleversarebecomingincreasingly

relevant.HBMcanscalethroughhigherstackingandadvancedbasedies,whileLPUmayleverage3DSRAMstacking.WeestimatetheTAMforemergingmemory

technologiescouldexpandtoUS$23.0bnby2030,fromUS$1.2bnin2025.

Mainstreammemoryplayersarethekeybeneficiaries,whileemerging

innovatorscouldgainshareasadoptionbroadens.WecontinuetolikeSamsung(coveredbyShawnKim;

Memory-ExponentialAgentic)

,Kioxia(coveredbyKazuoYoshikawa),andSanDiskandMicron(coveredbyJoeMoore;

NAND–AIEraFinally

ComestoNAND)

.Morebroadly,theopportunityextendsbeyondtraditional

memorysupplierstothebroaderecosystem,includinginterfaces,connectivity,packagingandsystemdesign.Examples:3Dstackingandadvancedpackaging-GigaDevice,Winbond,APMemory,PSMC.Next-generationinterconnects-

Montage,Renesas,Marvell.

Morganstanley

RESEARCH

GLoBALlNslGHT

MoRGANSTANLEyREsEARcH3

Contributors

MoRGANSTANLEyTAiwANLimiTEd+

DanielYen,CFA

EquityAnalyst

+88622730-2863

Daniel.Yen@

MoRGANSTANLEyTAiwANLimiTEd+

CharlieChan

EquityAnalyst

+88622730-1725

Charlie.Chan@

MoRGANSTANLEy&Co.INTERNATioNALpLc+

ShawnKim

EquityAnalyst

+44207677-1018

Shawn.Kim@

MoRGANSTANLEy&Co.LLC

JosephMoore

EquityAnalyst+1212761-7516

Joseph.Moore@

MoRGANSTANLEyMUFGSEcuRiTiEsCo.,LTd.+

KazuoYoshikawa,CFA

EquityAnalyst

+8136836-8408

Kazuo.Yoshikawa@

MoRGANSTANLEy&Co.INTERNATioNALpLc+

LeeSimpson

EquityAnalyst

+44207425-3378

Lee.Simpson@

MoRGANSTANLEyAsiALimiTEd+

DaisyDai,CFAEquityAnalyst

+8522848-7310

Daisy.Dai@

4

Contents

5NextGenMemoryinSixCharts

8ExecutiveSummary-Memory:TheNext

ConstraintinAI

17ImplicationforAsiaandEuropeTechnology

18ImplicationsforUSSemis

19ImplicationsforJapanSemis

20SummaryofSixInnovationPathways

25CaseStudyandDetailedPathstoMemory

Innovations

46Whataboutsystemandsoftwareoptimization?

47Montage:EstimateRevisionSummary

48Montage:ValuationMethodology

49RiskReward-MontageTechnology

Morganstanley

RESEARCH

GLoBALlNslGHT

MoRGANSTANLEyREsEARcH5

NextGenMemoryinSixCharts

Exhibit1:Tokengrowthchart–AgenticAIhasdrivenupthetokengrowth

Source:MorganStanleyResearch,companydata.Note:Chinatotal&Bytedancenumbersrepresentmonthlyrun-ratebasedondailynumbers

Exhibit3:Memorypricinghasrisensharply,withDRAMpricingperGBbackto30yearhigh

Source:MorganStanleyResearch

Exhibit2:Memorycouldaccountfor40%ofcloudcapexspendingby2027e

45%

40%

35%

30%

25%

20%

15%

10%

5%

0%

1,800

1,600

1,400

1,200

1,000

800

400

200

-

600

20262027202820292030

Cloudtotalspending(excl.memory)(US$bn)

Cloudmemoryspending(US$bn)

Memorypercentage

Source:MorganStanleyResearchestimates

Exhibit4:Thememorypyramid

Source:MorganStanleyResearch

Morganstanley

RESEARCH

GLoBALlNslGHT

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Exhibit5:HighGMprofileforallthememorycompanies

1Q11

4Q11

3Q12

2Q13

1Q14

4Q14

3Q15

2Q16

1Q17

4Q17

3Q18

2Q19

1Q20

4Q20

3Q21

2Q22

1Q23

4Q23

3Q24

2Q25

1Q26

4Q26

3Q27

2Q28

120%

100%

80%

60%

40%

20%

0%

-20%

-40%

SamsungSKhynixMicronNanyaTechWinbond

Source:MorganStanleyResearch

Exhibit6:HighOPMprofileforallthememorycompanies

1Q11

4Q11

3Q12

2Q13

1Q14

4Q14

3Q15

2Q16

1Q17

4Q17

3Q18

2Q19

1Q20

4Q20

3Q21

2Q22

1Q23

4Q23

3Q24

2Q25

1Q26

4Q26

3Q27

2Q28

80%

60%

40%

20%

0%

-20%

-40%

SamsungSKhynixMicronNanyaTechWinbond

Source:MorganStanleyResearch

Morganstanley

RESEARCH

GLoBALlNslGHT

Exhibit7:Memoryvendorsandtheirmemoryinnovations

MoRGANSTANLEyREsEARcH7

Source:Companydata丿MorganStanleyResearch

8

Morganstanley

RESEARCH

GLoBALINsight

ExecutiveSummary-Memory:TheNextConstraintinAl

Acentraldebateabouttodriveinnovation

WebelievememoryismovingfromtheperipheryoftheAIdebatetothecenter.AsAI

systemsscale,theconstraintisnolongerjustcomputepower.Itisincreasinglyabouthowefficientlydatacanbestored,accessedandmovedacrossthesystem.AccordingtoShawnKim

(Chipflation–NavigatingAMemoryCrisis)

,AIisturningmemoryintoastructural

bottleneck.AIdemandisrisingacrossHBM,DRAMandenterpriseSSDs,drivingasharp

increaseinmemorypricing,withsomesegmentsseeingpricesriseasmuchassix-foldoverthepastyear.

Exhibit8:DRAMsupply/demand

30%DRAMSupply/Demand%

20%

10%

0%

-10%

-20%

-30%

-40%

Oversupply

SupplyShortage

115,000

105,000

95,000

85,000

75,000

65,000

55,000

45,000

35,000

25,000

15,000

1Q21

2Q21

3Q21

4Q21

1Q22

2Q22

3Q22

4Q22

1Q23

2Q23

3Q23

4Q23

1Q24

2Q24

3Q24

4Q24

1Q25

2Q25

3Q25

4Q25e

1Q26e

2Q26e

3Q26e

4Q26e

Source:Gartner,DRAMeXchange,MorganStanleyResearchestimates

Exhibit10:DDR4supply/demand

Source:Companydata,IDC,MorganStanleyResearchestimates

Exhibit9:NANDsupply/demand

NANDSupply/Demand

NANDSupply/Demand%(RHS)TotalDemandTotalSupply,MSe

Oversupply

SupplyShortage

(mngigabit)

380,000

330,000

280,000

230,000

180,000

130,000

80,000

30,000-15%

20%

15%

10%

5%

0%

-5%

-10%

1Q17

2Q17

3Q17

4Q17

1Q18

2Q18

3Q18

4Q18

1Q19

2Q19

3Q19

4Q19

1Q20

2Q20

3Q20

4Q20

1Q21

2Q21

3Q21

4Q21

1Q22

2Q22

3Q22

4Q22

1Q23

2Q23

3Q23

4Q23

1Q24

2Q24

3Q24

4Q24

1Q25

2Q25

3Q25

4Q25e

1Q26e

2Q26e

3Q26e

4Q26e

Source:Gartner,DRAMeXchange,MorganStanleyResearchestimates

Exhibit11:NORflashsupply/demand

Source:Companydata,IDC,MorganStanleyResearchestimates

MoRGANSTANLEyREsEARcH9

Morganstanley

RESEARCH

GloBAlINsigHT

TheShiftfromComputetoSystemConstraints,LedbyMemory

AIgrowthisnolongerlimitedbyprocessorperformancealone.Instead,itisincreasinglyconstrainedbysystem-levelefficiency.LargeAImodelsrequirevastamountsofdata,

longercontextwindowsandfasterresponsetimes.Whilecomputeperformancehas

scaledaggressively,memorycapacityandbandwidthhavenotkeptup,andcostsremainelevated.Thisimbalanceiscreatingastructuralbottleneckthatisbeginningtolimitreal-worlddeploymentandscalability.

Exhibit13:DDR516Gb2Gx8ASPevolution

Exhibit12:TLC512GbASPevolution

Source:DRAMeXchange

Source:DRAMeXchange

Exhibit14:

MemoryBOMcostestimatesforCPUserver丿NotebookPCandsmartphone

73%

5,300

41%39%

740410

511262

CPUserverNotebookPCSmartphone

Memorycost(US$)Non-memorycost(US$)MemoryBOM%

80%

70%

60%

50%

40%

30%

20%

10%

0%

25,000

20,000

15,000

10,000

14,004

5,000

-

Source:DRAMeXchange丿MorganStanleyestimates.Note:Assumingcurrentcontractpriceformemorycost.

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Morganstanley

RESEARCH

GLobALINsiGHT

Understandingthe“MemoryWall”

Atthecoreofthisreportistheconceptofthe“memorywall.”AImodelsrequire

exponentiallymoredata,whilecomputeperformancecontinuestoimproveatarapid

pace.However,memorysystemscannotdeliverdataatthesamespeedorscale.Thisgapbetweencomputecapabilityandmemoryperformanceiswidening.Asaresult,evenif

computecontinuestoadvance,overallsystemperformanceisincreasinglyconstrainedbymemorylimitations.Putsimply,AIcanscaleonlyasfastasmemoryallows.

Exhibit15:Computevs.Memorycomparison

Source:APMemory丿MorganStanleyResearch.

WhatWeAreSolvingFor-ASystem-LevelChallenge

Thisreportfocusesonasingle,criticalquestion:howcantheindustryovercomethe

memorybottleneckandenablethenextphaseofAIscaling?WeidentifymemoryasakeyconstraintinAIandmapthepathwaysthroughwhichthisbottleneckmayberesolved.

ThisisimportantbecauseitshiftstheinvestmentlenstowardwhatwebelieveisanincreasinglyimportantlimitingfactorinAIinfrastructure.

Weshowthatthememorybottleneckisnotsimplyasupplyissue.Itisnotjustabout

producingmoreDRAMorexpandingHBMcapacity.Instead,itisasystem-widechallengerequiringcoordinatedinnovationacrossthefullmemorystack.Thisincludesarchitectures,packaging,interfaces,computemodelsandmaterials.Addressinganysinglelayerin

isolationisunlikelytobesufficient.Instead,progresswillrequireamoreholisticapproach.

WhyThisMattersforInvestors-ANewInvestmentQuestion

Solvingthememoryconstraintfundamentallychangeswhereinvestorsmayneedtolookforthenextphaseofreturns.Ifthedebateisframednarrowly,theopportunityappearsconcentratedamongtraditionalmemorysuppliersandHBMcapacity.However,when

viewedasasystem-levelchallenge,amuchlargerecosystembecomesrelevant.This

includesconnectivity,packaging,architecturesandsystemdesign.Theseareasareearlier-stage,lesscrowdedandoftenunder-owned,potentiallycreatingopportunitiesfor

differentiatedalphageneration.

TheAIinvestmentdebateisevolving.Thequestionisnolongersimply“whobuildsthefastestchips?”Instead,itisbecoming“whocanmove,storeandaccessdatamost

efficiently?”Thisshiftiscriticalbecausesystemefficiency,ratherthanrawcomputeperformancealone,islikelytoplayanincreasinglyimportantroleindeterminingAIscalabilityandeconomics.

Morganstanley

RESEARCH

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MoRGANSTANLEyREsEARcH11

FromMemoryChipstotheMemoryEcosystem

ThisreportarguesthattherealopportunityinAIisexpandingbeyondchipsalonetotheentirememoryecosystem,wheresolvingthe“memorywall”ispotentiallyunlockingabroaderandmoreattractivesetofinvestmentopportunities.

Wegobeyondthetraditionalfocusonmemorychips,suchasDRAMandNAND,andshowthatsolvingthememorywallrequiresinnovationacrosstheentiresystem:design,

packaging,connectivityandmaterials.

Wemapwherethesebreakthroughsarehappening,quantifythepotentialscaleoftheopportunityandhighlightwhereinvestorsmayfindthenextwaveofdifferentiationandreturns,acrossabroaderecosystemthatenablesfasterandmoreefficientAIsystems.

Weidentifywherethemostimportantinnovationsareoccurringacrossthisbroadermemoryecosystem,ratherthansolelywithintraditionalmemorychips:

•Advancedmemorytypes,includingHBM:MemoryisbeingplacedclosertoAIchipsandoptimizedforspeedratherthanstoragealone.

•3Dstackingandadvancedpackaging:Chipsarebeingstackedvertically,dramaticallyshorteningdistancesandimprovingperformance.

•Next-generationinterconnects:Fasterlinks,likehighways,allowchipstocommunicateatmuchhigherspeeds.

•System-levelco-design:Chips,memoryandsoftwareareincreasinglydesignedtogether,notseparately,tooptimizeoverallAIperformance.

•Emergingmaterialsandarchitectures:Newwaystobuildmemorycanreducepowerconsumptionandimproveefficiency.

PotentialbeneficiariesmayextendbeyondtraditionalDRAMandNANDleaderstothe

broadermemoryecosystem.Thisincludescompaniesenablingadvancedpackagingand

stacking;firmsdrivinghigh-speedconnectivityandinterconnects;andselectmaterialsandequipmentproviderscriticaltothesenewarchitectures.

WehighlightstockswithexposuretothesethemesinthesectionWheretheAlphaIsEmerging—KeyStockstoPlaytheTheme.

AStructuredFrameworkforInnovation

Tobringclaritytoacomplexandfragmentedspace,weintroduceasix-pathframeworkformemoryinnovation.Thisframeworkencompassesadvancesindesign,process,

packaging,peripherals,integrationandmaterials.Itprovidesastructuredwayfor

investorstoevaluatedevelopmentsacrosstheecosystemandidentifywhichtechnologiesarescalable,andcommerciallyrelevant.

Morganstanley

RESEARCH

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Exhibit16:Summaryofdifferentpathsofinnovation

Source:Companydata丿MorganStanleyResearch

ItHappenedBefore:3DNANDasaDisruptiveInnovation

3DNANDdisruptedtraditional2DplanarNANDbyovercomingthephysicalscalinglimitsthatconstrainedfurthercapacityexpansioninplanararchitectures.ItalsopressuredpartsoftheNORflashmarket,particularlyinstorage-orientedapplications,butitdidnot

replaceNORoutright.As3DNANDimproveddensityandcostperbit,itaccelerated

NAND’sadoptioninhigh-capacitymobileandembeddedstoragesockets,includingcaseswherecodeimagesarestoredinNANDandthencopiedintoRAMforexecutionthroughcodeshadowing.However,NORremainsimportantforboot/codestorage,execute-in-

place,securefirmware,fastrandomreads,andreliability-sensitiveautomotive,industrial,IoT,andnetworkingapplications.Thus,while3DNANDreducedNOR’saddressable

marketincertainmobileandembeddedstorageusecases,itdidnoteliminateNOR’sroleinapplicationsrequiringdeterministiccodeexecutionandhighreliability.

EmergenceofaNewEcosystem-WhatWillBethePotentialTAM?

Akeyoutcomeofthistransitionistheemergenceofanewecosystemaroundmemory

innovation.GrowthisnolongerlimitedtotraditionalDRAMandNANDsupply.Instead,itisexpandingintoareassuchasadvancedpackaging,memoryinterfaces,high-bandwidthstorageandsystem-leveloptimization.Thiscouldcreateamulti-billion-dollaropportunitysetthatextendswellbeyondlegacymemorymarkets.

Morganstanley

RESEARCH

GLoBALlNslGHT

MoRGANSTANLEyREsEARcH13

Wedefineprocessmigrationasthetraditionalpathway,whiletheotherfivepaths

representmemoryinnovations.ExcludingHBM,ourbasecasescenariosuggestsUS

$23.0bnTAMby2030,mainlyledbypackagingandperipherals.Ourbull/bearcase

scenariossuggestUS$41.4bn/US$16.9bnTAMby2030respectively.IncludingHBM,ourbasecasescenariosuggestsUS$276bnTAMby2030,andourbull/bearcasescenariossuggestUS$342bn/US$160bnTAMby2030respectively.

Exhibit17:MemoryInnovationTAMestimates-excludingHBM,basecase(US$mn)

Source:MorganStanleyresearchestimates

Exhibit18:MemoryInnovationTAMestimates-excludingHBM,bullcase(US$mn)

Source:MorganStanleyresearchestimates

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Exhibit19:MemoryInnovationTAMestimates-excludingHBM,bearcase(US$mn)

Source:MorganStanleyresearchestimates

WheretheAlphaIsEmerging—KeyStockstoPlaytheTheme

AsthememorybottleneckincreasinglybecomesthedefiningconstraintonAIscaling,theinvestmentopportunityextendswellbeyondtheobviousbeneficiaries.Atthecoreremainthemainstreammemoryleaders:SamsungElectronics,Micron,KioxiaandSanDisk,whicharepositionedtobenefitfromtighterDRAM,NANDandHBMsupplyandstrongerpricing.Asummaryofourviewsisprovidedbelow:

Samsung

WekeepOWratingonSamsungElectronics(TopPick)asakeybeneficiaryofAIcomputeandagenticAItrends

(AgenticAI–TheSurgeBegins)

.WeforecastDRAMpricehikesofmorethan20-30%in3Q26,enoughtokeeptheYoYrateofchangeaccelerating.PricingpoweristranslatingintoearningsrevisionsthatinturnsupportP/Estability–at5.2x

2027eearnings.

However,wearemindfuloftherateofchangethatstillmattersformemorystocks.WithYoYpricinglikelytoplateauin4Q26vs.supplydisciplinevisibilityin2028,webelievethestocksmightlacknear-termcyclicalcatalystsuntilthesupplyanddemanddynamics

becomeclearerinto2028andbeyond.However,themultiplescancontinuetore-rateonthebackoffavorableLTAs.

Kioxia

WeremainOverweight(TopPick)onKIOXIA,asthecompanyisaddressingAIdemandacrossbandwidth,latency,IOPS,andcapacitythroughitsSSDportfolio.TheCMSeriestargetshigh-bandwidth,low-latencyKVcacheapplicationsusingTLCNAND.TheGP

Series,poweredbyXL-FLASHanddesignedfordirectGPUintegration,targetsultra-low-latency,SuperHighIOPSworkloadsandcouldcomplementHBMbyeasingmemory

capacityconstraints.TheLCSeriesaddressestherapidgrowthinAIdatavolumeswith245TBQLCSSDs,providinghigh-capacity,cost-efficientstorageforlarge-scaleAI

infrastructure.

MoRGANSTANLEyREsEARcH15

Micron

WeremainOverweightwithapricetargetof$1,200,reflectinga30xmultipleonthrough-cycleearningspowerof$40—apremiumtohistorythatcapturesMicron'sexpanding

roleintheAIcycle.DRAMfundamentalsarein"unchartedterritory,"withAI-driven

datacenterdemandexpectedtokeepsupply/demandtightwellbeyond2027,supportingamulti-yearearningsupcycle.Micron'sexecutiononHBMisunderappreciated,andwe

expectthecompanytomaintainHBMshareinCY26,drivinggrossmarginstoward90%whichwarrantsahighermultiplethanpriorcycles.Strategiccustomeragreements(16deals,$22bninfinancialcommitments)addrevenuevisibility,whileacommitmenttoreturn100%ofexcesscashtoshareholdersenhancesthecapitalreturnstory.

SanDisk

WeremainOverweightwithapricetargetof$1,750,valuingthestockat28xthrough-

cycleEPSof$62.50.ThecorethesiscentersonAIfundamentallytransformingtheNANDmarket:surginginferencedemandispullingNANDupthememoryhierarchytoserveLLMKVcacheandcontextwindowstorageneedsthatDRAMalonecannotsatisfy,shifting

cloudtobecomeNAND'slargestendmarket.Thisstructuralrepricing—awayfromprice-sensitivePC/mobilecustomerstowardlessprice-sensitivehyperscalers—underpins

durablemarginexpansion,withSandiskhavingalreadylockedinoverone-thirdofFY27bitsunderNewBusinessModel(NBM)agreementsat80%+grossmargins.WithminimalnewcapacityinvestmentandalongrunwayforupwardEPSrevisions,weseepeak-cycleFCFasunderappreciated,withthestocktradingatjust~10.5xCY27EPS.

Themoredifferentiatedopportunitiesmayliewithintheenablerecosystem,whereinnovationishappeningfasterandwherepositioningappearslesscrowded.

Inmemoryinterfacesandconnectivity,MontageTechnologystandsoutasahigh-convictionidea,givenitsexposuretoCXL,MRDIMM,DDR6andAIservercontentexpansion.Itiseffectivelyleveragedtothe“plumbing”ofnext-generationmemorysystems.

InadvancedpackagingandedgeAIintegration,companiessuchasWinbond,GigaDeviceandAPMemoryarepositionedtobenefitfromwafer-on-waferstackingandspecialtymemoryusecasesthatimprovebandwidth,powerefficiencyandformfactor.

Morebroadly,theecosystemextendstocompaniesexposedtoCXLmemoryexpansion,MRDIMMbandwidthscaling,andPIM/CIMarchitectures,manyofwhichremainatanearlystageofadoption,under-ownedandarenotfullyreflectedinconsensusexpectations.

ThisiswhereincrementalalphaislikelytoemergebeyondthecrowdedAIbeneficiaries,asinvestorsbegintopricethefullsystem-levelimplicationsofthememorybottleneck.

16

Exhibit20:Globalmemorycomparablestable

Ticker

Company

Price7/10/2026

Curr

ency

PriceTarget

Upside/Downside

Rating

Dividend

Yield(%)

FCF

Yield(%)

Market

Cap

(US$M)

3MAvg.

Daily

Trading

(US$M)

P/ERatio(x)

EPSGrowth

ROAE

P/BRatio(x)

2026e

2027e

2028e

2026e

2027e

2028e

2026e

2027e

2028e

2026e

2027e

2028e

Memory

005930.KS

SamsungElectronics

285,000

KRW

381,000

34%

O

1.4%

2.9%

1,411,827

5,603.3

5.9

4.3

4.3

722%

38%

0%

61%

50%

34%

2.5

1.6

1.1

000660.KS

SKhynix

2,180,000

KRW

2,600,000

19%

O

0.5%

7.6%

1,162,083

6,690.7

6.8

4.7

4.4

437%

44%

9%

100%

65%

42%

4.6

2.3

1.5

MU.O

Micron

979.3

USD

1,200.0

23%

O

0.0%

NA

1,138,198

41,306.3

9.4

5.4

NM

863%

75%

NA

88%

89%

47%

8.4

3.9

2.8

285A.T

Kioxia

77,000.0

CNY

110,000.0

43%

O

0.0%

NA

281,941

21,475.6

10.6

8.0

8.5

2259%

33%

-6%

145%

73%

42%

8.1

4.4

3.2

SNDK.O

Sandisk

1,915.9

USD

1,750.0

-9%

O

0.0%

NA

276,850

20,568.8

13.9

9.8

NM

321%

41%

NA

68%

93%

41%

14.5

5.3

3.5

603986.SS

GigaDevice

612.0

CNY

888.0

45%

O

0.3%