摩根士丹利-市场中的群体智慧：预测、博彩与股票市场中的群体行为 The Wisdom of Crowds in Markets Crowd Behavior in Prediction,Betting,and Stock Markets

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CounterpointGlobalInsights

TheWisdomofCrowdsinMarkets

CrowdBehaviorinPrediction,Betting,andStockMarkets

CONSILIENTOBSERVER|August5,2026

Introduction

In1932,BernardBaruch,awealthyfinancierwhomadehisfortuneonWallStreetintheearly20thcentury,contributedtheforewordtoareprintofthe1852editionofCharlesMackay’sclassicbookonmarkets,MemoirsofExtraordinaryPopularDelusionsandtheMadnessofCrowds.

InvokingadictumfromFriedrichvonSchiller,aGermanpoetandphilosopher,Baruchwrote:“Anyonetakenasanindividual,istolerablysensibleandreasonable—asamemberofacrowd,heatoncebecomesablockhead.”Headded,“Withoutduerecognitionofcrowd-thinking(whichoftenseemscrowd-madness)ourtheoriesofeconomicsleavemuchtobedesired.”1

About40yearslater,EugeneFama,aprofessoroffinanceattheUniversityofChicagoandawinneroftheNobelPrizeinEconomics,published“EfficientCapitalMarkets:AReviewofTheoryandEmpiricalWork.”Itisamongthemostfamouspaperseverwritteninfinance.ThismightbeconsideredthetheoryBaruchhadinmind.Famaposited,“Amarketinwhichpricesalways‘fullyreflect’availableinformationiscalled‘efficient.’”2

Famafoundthatstrategiesinvestorscommonlyappliedtotrytooutperformthemarket,includingusingpastpricepatternstoprojectthefutureanddoingfundamentalanalysistodistinguishbetweenpriceandvalue,failedintheirobjective.Inotherwords,thereisnoreliablewaytotakeadvantageoftheblockheads.

Nearlyallthosewhostudymarketscarefullyagreethattheyappearsensibleforthemostpart,astheorywouldhaveit,butperiodicallygobonkers.3Havingoneframeworktoaccommodatebothrealitiesisuseful.

JamesSurowieckiwroteaboutsuchanapproachin2004.4RiffingonMackay’smadnessofcrowds,Surowieckicalledhisbook,TheWisdomofCrowds.Heshowedthatcrowdscanberemarkablyaccurateinreflectingobjectivevaluesoroutcomes.Indeed,thepricesgeneratedbycollectivescommonlyconvergeonthepropertheoreticalpriceinexperimentalsettings.5Thisthinkingrunsagainsttheideathatindividualsarereasonableandcrowdsmad.

AUTHORS

MichaelJ.Mauboussin

michael.mauboussin@

DanCallahan,CFA

dan.callahan1@

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ButkeytoSurowiecki’scaseisthatthewisdomofcrowdsdependsonsatisfyingcertainconditions.Whenthoseconditionsareineffect,crowdsaregenerallywise.Whenoneormoreofthoseconditionsareviolated,crowdscanbemad.

Thisreportspecifiesthoseconditions,identifiesvarioustypesofproblems,andexamineshowtheyapplytopredictionmarkets,sportsbetting,parimutuelbetting,andthestockmarket.Thegoalistoseehowtheconditionsfunctionineachmarket,andwheretheyarethesameordifferentforeach.

Theseconceptsareusefulforinvestorsforafewreasons.First,thewisdom(andmadness)ofcrowdsisasoundwaytoexplainmarketbehavior.Practitionershavehadasenseofthisforcenturiesandacademicsnowtaketheideaseriously.6Second,predictionmarketsprovidereal-timeprobabilitiesforeventsthatmaybehelpfultoinvestors.

Finally,theconditionsforcollectiveintelligenceapplywithinorganizationsaswell,whichhasrelevanceforhiringandtrainingemployeesaswellasstructuringmeetingsandmakingdecisions.Thereremainsalargegapbetweenwhatresearchrevealsasbestpracticesandwhatmostorganizationsactuallydo.

ConditionsforCrowdstoBeWise

Wediscussthreeconditionsforcrowdstobewise:diversity,aggregation,andincentives.

Diversity.Inorganizations,itiscommontounderstanddiversityasareflectionofsocialcategoriessuchasgender,age,ethnicity,andreligion.Effectivecollectivedecision-makingreliesoncognitivediversity,whichcaptureshowgroupmembersdifferintheirinformation,knowledge,heuristics,representations,andmentalmodels.

ScottE.Page,aprofessorofcomplexsystems,politicalscience,andeconomicsattheUniversityofMichigan,isoneoftheleadingresearchersondiversity.7Aswewillseeinamoment,Pagealsoshowsthemathofhowandwhycognitivediversityreducescollectiveerror.

HerearetheelementsofcognitivediversitythatPagefeatures:

•Informationconsistsoffactsabouttheworld.FriedrichHayek,whoreceivedtheNobelPrizeinEconomics,madethepointthatinformationtendstobeincompleteandlocal.Itcanalsobecontradictory.8Informationisnotjustdatabutrathersomethinganindividualinterpretsasmeaningful.

Pricesreflectallinformationinanefficientmarket.Yethavingbetterinformationthanotherscanbeasourceofadvantageinallofthemarketsthatwewilldiscuss.

•Knowledgehastodowithstructuralunderstandingandentailsatheoreticalorempiricalcomprehensionofhowthingswork.Itistiedtocriticalthinkingandcanbespecifictoadomain.Relyingontheoutputofgenerativeartificialintelligence(GenAI)withoutthebenefitofknowledgecreatestheriskofmisunderstanding.

•Heuristicsarerulesofthumb,approaches,ortechniquestosolveproblemsandgenerateideas.Adiversesetofheuristicscontributestocollectiveresultsbecausedifferentheuristicsworkfordifferentproblems.Youcanlearnheuristicsinanyorderandtheyoftenapplyacrossdisciplines.

•Representationscapturetheperspectivesandcategorizationsindividualsusewhentheyconsiderasubject.Peoplewithdifferentpointsofviewwilltakealternativeapproachestosolvingaproblem.For

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instance,askagroupofpeopletolistthelargestcountriesintheworld.Onemightcreatealistbasedonlandmass,anotheronpopulation,andathirdongrossdomesticproduct.Thesedifferentperspectivescanproduceinsight.

•Mentalmodelsareframeworksthathelpindividualsthinkabouthowtheworldworks.Theyarebasedonunderstandingandexperience.Mentalmodelsareinternalrepresentationsofexternalrealitiesthattradespecificsforspeed.9

Categorizationsareimportantbecausehumansthinkinanalogies.10Groupingcompaniesbasedonindustryorpositioningisacaseinpoint.NordstromandDollarGeneralareretailers,andFerrariandSuzukiareautomobilemanufacturers.AclassificationbasedonbrandwouldlinkNordstromandFerrariaspremiumandDollarGeneralandSuzukiaslow-cost.Differentcategorizationscanallowcollectivestobetterassessalternativesandoutcomes.

Collectiveerrortendstobesmallwhenindividualmembersarecognitivelydiverseandtheirviewsareproperlyaggregated.

Diversityisthemostlikelyconditiontobeviolatedinfinancialmarketsbecauseinvestingisaninherentlysocialactivity.Pricescanbeasourceofinformationaswellasinfluence.Asaresult,thebehaviorofinvestorsiscorrelatedfromtimetotime,leadingtoboomsandbusts.Wediscussdiversitybreakdownsineachofthemarketsweconsider.

Aggregation.Havingdiverseinformationhelpsuncoverthetruthonlywhenitcanbeeffectivelyaggregated.Thevariousmarketswewilldiscussuseseveralaggregationmethods.Ineachcase,theoutputoftheaggregationisaquantitythatreflectsthelikelihoodofaparticularoutcome.Assuch,aggregationisessentialforpricediscovery,theprocessoffindinganasset’sfairpricethroughtheinteractionofbuyersandsellersonanexchange.

Thereisevidencethatthechosenapproachtoaggregationaffectsaccuracy.11Straightforwardmethodssuchasaveragingtheanswersofagroupofexpertsormodelscanimproveforecasts.12Accuracycanbeboostedfurtherbyusingmorecomplextechniquessuchasweightedaveragesorextremizingalgorithmsthatpushforecastsawayfromthesimpleaveragewhenthereisevidencethattheoriginalforecastsaretooconservative.13

Informationaggregationisprominentinnature,wheregettingtoagoodanswercanbethedifferencebetweenlifeanddeath.Forexample,honeybeesusewaggledancestocommunicatethedirection,distance,andqualityoffoodsources.(“Onaverage,onesecondofthecombinedbody-waggling/wing-buzzingrepresentssome1,000meters[six-tenthsofamile]offlight.”)14Whenscoutsreturntothehivewithconflictinginformation,thecolony’sactiondependsontheintensityanddurationofcompetingdances.

Antcoloniesdosomethingsimilarwithpheromonetrailsastheyforage.Pathsofhigherqualitygetreinforcedfaster,whichallowsthecolonytoconvergeontheshortestpathtothefood.15Flocksofbirdsandschoolsoffishhavealsoevolvedsophisticatedmeanstoshareinformation.16

Incentives.Ononelevel,theimportanceofincentives,rewardsforbeingrightandpenaltiesforbeingwrong,isself-evident.Inmarkets,wecanmeasureincentiveswithmoney.Ifanindividual’sgoalistomakemoney(orexcessreturnsinequitymarkets),theyshouldparticipateonlyiftheybelievetheyhaveanedge,orawell-foundedviewthatisdifferentthanwhatispricedintothemarket.

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AsScottPagewrites,“Informationmarketscreateincentivesforlessconfidentpeopletostayout,andforconfidentpeopletobetmore.”17Inotherwords,yourbetsizeshouldreflectyourconfidenceinyouredge.

Famasuggestedthatanefficientmarketisonewherethepricecapturesallavailableinformation.Twoeconomists,SanfordGrossmanandJosephStiglitz(StiglitzwontheNobelPrize),demonstratedthatmarketscannotbefullyinformationallyefficientbecausethereisacosttocollectinginformationandreflectingitinprices.Asaresult,thereshouldbeaproportionatebenefitintheformofexcessreturnstoincentivizeparticipants.18

Inanutshell,theGrossman-Stiglitzparadoxsaysthatinvestorswouldhavenoincentivetocollectinformationifmarketswereperfectlyefficient,butinformedtradersarenecessaryformarketstobeefficient.LassePedersen,aprofessoroffinance,suggestsmarketsmustbe“efficientlyinefficient.”Skilledparticipantscanearnexcessreturnsbyidentifyingandtradingoninefficiencies,buttheireffortsmakemarketsmoreefficient.

Gatheringinformationisbutonecost.Reflectingitinpricesisanother.Transactioncostsandmarketimpact,wheretheactofbuyingandsellingmovesthemarketandreducesexpectedreturn,canbemeaningful.Edgehastobesufficienttoovercomecosts.

Wewillalsolookatthedistributionofwinnersacrossmarkets.Predictionmarkets,sportsbettingmarkets,andparimutuelmarketsareallzerosuminthesensethatthepayoffstowinnersandlosersnettozerobeforeexpenses.Wewillseethatasmallnumberofparticipantsmakemoneyinthesemarkets.

Thestockmarketiszerosumforrelativeresults,whichmeansthatexcessreturnsnettonilbeforecosts.Butitisapositivesummarketoverallbecausestockstendtoriseovertime.Thestockmarket’spositiveexpectedreturnreflectstheratethatthosewhowanttoconsumenowmustpayandtheratethosewillingtodefertheirconsumptionwillearn.Thismeansthatwhilesomestockmarketinvestorsmayhavenegativeexcessreturns,theywillstillhavepositiveexpectedreturnsonanabsolutebasisoverthelongterm.

ProblemTypes

Understandingthetypeofproblemyoufaceisanimportantfirststepindetermininghowbesttosolveit.Insomecases,acrowdmaybemoreofahindrancethanahelp.

TaketheexampleofEbbsfleetUnited,asoccerteamthatcompetesinthelowertiersoftheEnglishleaguesystem.19Startingin2007,agroupcalledMyFootballClubwasorganizedtoownandruntheteam.Atonepoint,morethan20,000fanshadavoiceinmanagingtheclub,includingmakingdecisionsaboutplayers.

Afterabitofearlysuccess,theexperimentwentsouth.Theviolationoftheconditionsforcrowdwisdomexplainswhy.Thebaselineknowledgeofthefanswaspoor,inpartbecausetheclubplayedinalowtierandthecentralforumsfordiscussionledtocorrelatedviews.Thevotingstructurewascumbersome.Andwhilefanspaidamodest£35subscriptionfee,itwasinsufficienttoactasacompellingincentive.Theclubwaslatersoldatafractionofthepurchaseprice.20

Wedescribethefirstproblemasfindinganeedle-in-a-haystack.Inthiscase,anobjectiveanswerexistsandsomememberswithinthecollectiveknowit.AppendixAshowshowcrowdscananswerthesequestions.Buttechnology,suchassearchenginesorGenAI,doessomorequickly.

Thesecondtypeofproblemisestimatingastate.Inthiscase,noonewithinthecollectiveknowstheanswer,butitexistsandislaterrevealed.Toopenhisbook,SurowieckioffersanexampleofthistypethroughthestoryofFrancisGalton,apolymathintheUnitedKingdom’sVictorianera,andtheweightofanox.21

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InDecember1906,theWestofEnglandFatStock&PoultrySocietyhelditsannualshowinPlymouth,England.Theshowincludedacompetitiontoguessthedressedweightofanox.Participantspaidsixpence(about$5today)foraticketandwrotetheirestimate.Eighthundredticketsweresold,andGalton’ssamplewas787because13ofthemwere“defectiveorillegible.”

Aftertheawardswerepassedout,Galtonborrowedtheticketstoexaminethem.Hewasexcitedaboutthedatabecausethe“judgmentswereunbiasedbypassionanduninfluencedbyoratory.”Participants“includedbutchersandfarmers,someofwhomwerehighlyexpertinjudgingtheweightofcattle”andothers“probablyguidedbysuchinformationastheymightpickup,andbytheirownfancies.”

Notethattheconditionsforthewisdomofcrowdswereinplace:diversityinthenatureoftheguesses,aggregationviaGalton’scalculations,andincentives,includingacosttoparticipateandaprizeforaccuracy(“thesixpennyfeedeterredpracticaljoking”and“thehopeofaprizepromptedeachcompetitortodohisbest.”)

Theaverageguessofthecollectivewas1,197pounds,equaltotheactualweightoftheox.(Galtonincorrectlytranscribeditinthearticleas1,198,whichisthenumberSurowieckiuses.)22Galtoncomesacrossasabitsurprised,writing,“Thisresultis,Ithink,morecreditabletothetrustworthinessofademocraticjudgmentthanmighthavebeenexpected.”

ScottPageofferswhathecallsthe“diversitypredictiontheorem”asawaytoexplainresultssuchasthoseofGalton.23Itstates:

Collectiveerror=averageindividualerror–predictiondiversity

Translatedintosimplerterms,thetheoremsaysthewisdomofcrowds(collectiveerror)comesfromindividualsmarts(averageindividualerror)anddiversity(predictiondiversity).

Thetheoremhastwoimplications.Thefirstisthatacollectivewithanydiversitywillbemoreaccuratethantheaverageindividualwithinthecollective.

Thesecondisthatcollectivewisdomisacombinationofbothsmartsanddiversity.Youcanmakethecrowdsmarterbyreducingindividualerrororincreasingdiversity.

AppendixBappliesthediversitypredictiontheoremtoGalton’sdata.Weusethefullsampleof787guesses.

OneofthepointsthatGaltonmadeaboutthedataisthatitdidnotfollowanormaldistribution,whereresultstaketheshapeofabellwiththetopdefinedastheaverageandthewidthofthebellasthestandarddeviation.Exhibit1comparestheGaltondatatotheexpectednormaldistribution.

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Exhibit1:TheGuessesoftheOx’sWeightDoNotFollowaNormalDistribution

Frequency(PercentofTotal)

888

913

938

963

988

1,013

1,038

1,063

1,088

1,113

1,138

1,163

1,188

1,213

1,238

1,263

1,288

1,313

1,338

1,363

1,388

1,413

1,438

1,463

1,488

1,513

ExpectedNormalFrequencyObservedFrequency

20

18

16

14

12

10

8

6

4

2

0

WeightinPounds(Midpointof25-PoundBin)

Source:KennethF.Wallis,“RevisitingFrancisGalton'sForecastingCompetition,”StatisticalScience,Vol.29,No.3,August2014,420-424.

JackTreynor,aneconomistandluminaryintheinvestmentindustry,wroteapaperusingtheproblemofestimatingastateasawaytoillustrateapathtomarketefficiency.Ratherthanguessingtheweightofanox,Treynorhadhisstudentsguessthenumberofbeansinajar.HehadaresultsimilartothatofGalton,albeitwithamuchsmallersample.24

Applyingthelessontofinancialmarkets,Treynorexplainedthattheresult“comesfromthefaultyopinionsofalargenumberofinvestorswhoerrindependently.Iftheirerrorsarewhollyindependent,thestandarderrorinequilibriumpricedeclineswithroughlythesquarerootofthenumberofinvestors.”ThisoriginatesfromanequationderivedbytherenownedFrenchmathematician,AbrahamdeMoivre.

Theimportantimplicationisthatsmallsamplesofalargeanddiversepopulationcanproducemeaningfuldeviationsfromtruevaluebecausethedrawmightrandomlyhavemorehighorlowguesses.25

Thethirdtypeofproblemisapredictionaboutanoutcomethatisresolvedinatimelymanner.Inthiscase,nooneknowstheanswerinadvance,butaneventoccursthatsettlesthescore.Predictionmarkets,sportsbetting,andparimutuelbettingareexamplesofwaystosolveproblemsofprediction.Weknowtheresultsafteranelectionisheld,agameisplayed,oraraceisrun.

Thefourthtypeofproblemisapredictionaboutanoutcomethatremainsunresolved.Thestockmarketisacaseinpoint.Thevalueofacompany,whichintheoryshouldbeequaltoitsmarketprice,isbasedonthepresentvalueoffuturecashflows.Butbecausenooneknowswhatthefutureholds,thereisnoresolutionunlessacompanyisacquiredorgoesbankrupt.

Aperpetualfuturescontract,aformofderivativethatprovideseconomicexposuretothepriceofanasset,isanotherexample.TheCommodityFuturesTradingCommission(CFTC)recentlyapprovedaperpetualcontractthatreferencesthespotpriceofbitcoin.26

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Wenowturntohowthewisdomormadnessofcrowdsappliestothefourmarkets.Ineachcase,wedescribethemarket,offerabriefhistory,discussitsaccuracy,specifytheaggregationmechanism,considerdiversity,andassessincentives,includingthecosttoplayaswellasthedistributionofprofits.

Bettingmarketsshareseveralcharacteristicswithfinancialmarkets,includinglargenumbersofparticipants,widespreadaccesstoinformation,andmeaningfulfinancialincentives.Buttheyaredifferentbecausethereareoutcomesthatprovideawaytomeasureefficiency.27

TheWisdom(orMadness)ofCrowdsbyMarket

Predictionmarkets.Predictionmarketsaggregateinformationandgenerateforecastsaboutfutureevents.Participantsbuyorsellacontractthathasapayoffthatreflectstheresult.Whiletherearevariousformsofcontracts,mostarebinary.28Forexample,thecontractforcandidateAinanelectionpays$1.00ifshewinsand$0ifsheloses.

Thecontractprice,whichisupdatedcontinuouslythroughtrading,reflectstheprobabilitythataparticularoutcomeoccurs.Theinterpretationofacontracttradingat$0.70isthatthereisa70percentprobabilitytheeventwilloccur.Thosewhobelievethelikelihoodishigherwillbeinclinedtobuy,andthosewhobelieveitislowerwillsell.

Briefhistory.Bettingonoutcomeshasbeenaroundforalongtime.Forinstance,therewerequotesonbettingoddsforthepopeoftheCatholicChurchin1503(PiusIIIwaselected),andthattypeofwageringwasalreadyviewedas“anoldpractice.”29

Wetracethreeerasofmodernpredictionmarkets.

ThefirstreflectsbettingonpoliticaloutcomesintheU.S.fromthe1880stothe1920s.PaulRhodeandKolemanStrumpf,professorsofeconomics,notethatthesemarketswereactiveandwellfollowed.The1916presidentialelectionhadbettingvolumeexceeding$300million(in2026dollars),andprominentnewspaperssuchasTheNewYorkTimesprovidedpricequotationsonthecandidatesnearlyeveryday.

RhodeandStrumpfshow“thatthemarketdidaremarkablejobforecastingelections,”identifyingthewinningcandidateinallbutonepresidentialelectionfrom1884to1940.30

Despitetheiraccuracy,bettingmarketswerealwaystarnishedbytheirassociationwithgambling.TheLiteraryDigest,aweeklymagazine,introducedanon-scientificpollthatsuccessfullycalledthepresidentialelectionsfrom1916to1932.GeorgeGallupcreatedascientificpollthatfamouslycalledthe1936electioncorrectlywhileTheLiteraryDigestgotitwrong.

Overtime,mediacoveragecametofocusmoreheavilyonpollingresultsthanonpredictionmarkets.RhodeandStrumpfnotethatthereweremorearticlesaboutTheLiteraryDigestpollsthanbettingmarketsinTheWashingtonPostin1924andinTheNewYorkTimesin1928.CoverageoftheGalluppollstartedin1936andexceededthatofbothTheLiteraryDigestpollandbettingmarketsby1940.31

ThelaunchoftheIowaElectronicMarkets(IEM)inApril1988markedthebeginningofthesecondera.32ThemarketwasthebrainchildofthreeeconomistsattheUniversityofIowaandoperatedunderexemptionfromgamblinglawsinthestate.Whilethemarketusedrealmoney,theeconomistscappedtheindividualstakesat$500.TheIEMisdesignedtopredictthepopularvote.

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Inthe1988election,theIEM’sclosingpricesweremoreaccuratethanthepollspublishedbyTheGallupOrganization,HarrisandAssociates,CNN/USAToday,ABC/WashingtonPost,NBC/WallStreetJournal,andCBS/NewYorkTimes.TheIEMhasconsistentlybeenbetterthanpollssincethenwiththeexceptionof2024.33

WhiletheIEMcameoutofacademia,commercialpredictionmarketsemergedinthiseraaswell.Thedevelopmentoftheinternetfacilitatedthesemarkets.

Intrade,whichoperatedfrom2001to2013,createdcontractsforelections,economicindicators,andgeopoliticalevents.HollywoodStockExchangewasfoundedin1996andhascontractsonmovieopeningsandentertainmentawards.TradeSports,startedbythefoundersofIntrade,operatedsporadicallyfromtheearly2000sthrough2015andtradedinsportsandotherevents.

Asinthepriorera,thesemarketsprovedtobemoreaccuratethancommonalternativessuchaspollsandexpertforecasts.34Buttheyfacedregulatoryscrutinyand,similartothepast,sufferedfromthestigmaofgambling.

AnothersetbackforpredictionmarketsoccurredwhentheDefenseAdvancedResearchProjectsAgency,aresearchanddevelopmentagencywithintheU.S.DepartmentofDefense,proposedwhatcametobecalledthePolicyAnalysisMarketin2001.35Thismarketwasintendedtobetterassessgeopoliticalrisk,atopiconthemindsofanalystsandpolicymakersinthewakeofintelligencefailuresprecedingtheterroristattacksonSeptember11,2001.Inthesummerof2003,theplanwasroundlydenouncedbyU.S.senatorsandsubsequentlyscuttled.

Thethirderastartedaboutadecadeagoandhasbenefitedfromongoingtechnologicaladvancements,suchasblockchainplatforms,andevenmoresignificantlyfromregulatoryrelief.MarketleadersbytradingvolumeincludePolymarket,Kalshi,andForecastEx.

TheCFTCspecifieswhichexchangesaredesignatedcontractmarkets(DCMs),whichmeanstheyoperateundertheCFTC’sregulatoryoversight.Historically,theCFTCallowedplatformssuchastheIEMtooperateunderstrictexemptions,includinglimitingindividualinvestments.TheCFTCalsopermittedtheDCMstoself-certifycontractsbutretainedtherighttoblockthosecontractsitdeemedinappropriate.

In2023,theCFTCbarredsomecontractsatKalshithatwerebasedontheoutcomeofelectionsforCongress.TheCFTCconsideredthemtobeelectiongamblingthatwasinviolationofstatelaws.KalshisuedtheCFTCandwonthecaseinU.S.DistrictCourtintheDistrictofColumbiainSeptember2024.

Followingthatrulingandachangeinadministration,theCFTChaslargelypermittedtheDCMstoself-certifycontractsfreely.36ThisallowedtheDCMstointroducesportscontracts.Thesecontractscompetewithsportsbetting,whichisregulatedatthestate,ratherthanfederal,level.Infact,theCFTChassuedstatesthathavetriedtousetheirwageringlawstoregulatepredictionmarkets.37Inthe

U.S.as

ofJuly2026,39statesandWashington,D.C.havelegalizedsportsbetting,with30ofthemandD.C.allowingbettingonmobiledevicesorwebsites.

Predictionmarketsandsportsbettingmarketsnowlargelyoverlapastheresultofthesedevelopments.Estimatessuggestthatsportscontractswere80percentofKalshi’svolumeandabout40percentofPolymarket’svolumefromJuly2024toApril2026.38

Accuracy.Oneofthemainattractionsofpredictionmarketsisthattheyaremoreaccuratethanotherpopularsourcesofinformation,includingpollsandtheopinionsofsingleexperts.Exhibit2showsthecontractpriceonthehorizontalaxisandthewinrateontheverticalaxisformorethan72milliontradesonKalshi.39

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