公司理财（英文版·第5版）课件 第13章　投资者行为与资本市场效率

CorporateFinanceFifthEditionChapter13InvestorBehaviorandCapitalMarketEfficiencyCopyright©2020,2017,2014PearsonEducation,Inc.

AllRightsReservedChapterOutline(1of2)13.1CompetitionandCapitalMarkets13.2InformationandRationalExpectations13.3TheBehaviorofIndividualInvestors13.4SystematicTradingBiases13.5TheEfficiencyoftheMarketPortfolio13.6Style-BasedTechniquesandtheMarketEfficiencyDebateChapterOutline(2of2)13.7MultifactorModelsofRisk13.8MethodsUsedinPracticeAppendixLearningObjectives(1of4)Computeastock’salpha.Explainhowinvestors’attemptsto“beatthemarket”shouldkeepthemarketportfolioefficient.Describetheeffectofhomogeneousexpectationsonasecurity’salpha.Explainwhyholdingthemarketportfoliodoesnotdependonthequalityofaninvestor’sinformationortradingskills.UnderstandwhattheC

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Mrequiresaboutinvestors’expectations.LearningObjectives(2of4)Evaluateunderwhatconditionsthemarketportfoliowouldbeinefficient.Explaindiversificationbiasandfamiliaritybias.Discusswhyuninformedinvestorstradetoomuch.Assesshowuninformedinvestors’behaviordeviatesfromtheC

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Minsystematicways.Explainthedispositioneffect.LearningObjectives(3of4)Reviewwhyinvestors,onaverage,earnnegativealphaswhentheyinvestinmanagedmutualfunds.Assessthestrategyofaninvestor“holdingthemarket.”Discussthesizeeffect.Describethemomentumtradingstrategy.Explainhowthechoiceofthemarketproxymayleadtonon-zeroalphas.LearningObjectives(4of4)Discusshowsystematicbehavioralbiasesmayaffecttheefficiencyofthemarketportfolio.Assesshowapreferenceforstockswithapositivelyskewedreturndistributionwouldimpactthemarketportfolio’sefficiency.DescribetheArbitragePricingTheory.Discusstheexpectedreturnonaself-financingportfolio.DiscusstheFama-French-Carhartmodel.13.1CompetitionandCapitalMarkets(1of3)IdentifyingaStock’sAlphaToimprovetheperformanceoftheirportfolios,investorswillcomparetheexpectedreturnofasecuritywithitsrequiredreturnfromthesecuritymarketline.13.1CompetitionandCapitalMarkets(2of3)IdentifyingaStock’sAlphaThedifferencebetweenastock’sexpectedreturnanditsrequiredreturnaccordingtothesecuritymarketlineiscalledthestock’salpha.Whenthemarketportfolioisefficient,allstocksareonthesecuritymarketlineandhaveanalphaofzero.Figure13.1AnInefficientMarketPortfolio13.1CompetitionandCapitalMarkets(3of3)ProfitingfromNon-ZeroAlphaStocksInvestorscanimprovetheperformanceoftheirportfoliosbybuyingstockswithpositivealphasandbysellingstockswithnegativealphas.Figure13.2DeviationsfromtheSecurityMarketLine13.2InformationandRationalExpectations(1of5)InformedVersusUninformedInvestorsIntheC

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Mframework,investorsshouldholdthemarketportfoliocombinedwithrisk-freeinvestments.Thisinvestmentstrategydoesnotdependonthequalityofaninvestor’sinformationortradingskill.TextbookExample13.1(1of2)HowtoAvoidBeingOutsmartedinFinancialMarketsProblemSupposeyouareaninvestorwithoutaccesstoanyinformationregardingstocks.Youknowthatotherinvestorsinthemarketpossessagreatdealofinformationandareactivelyusingthatinformationtoselectanefficientportfolio.Youareconcernedthatbecauseyouarelessinformedthantheaverageinvestor,yourportfoliowillunderperformtheportfoliooftheaverageinvestor.Howcanyoupreventthatoutcomeandguaranteethatyourportfoliowilldoaswellasthatoftheaverageinvestor?TextbookExample13.1(2of2)SolutionEventhoughyouarenotaswellinformed,youcanguaranteeyourselfthesamereturnastheaverageinvestorportfoliosimplybyholdingthemarketportfolio.Becausetheaggregateofallinvestors’portfoliomustequalthemarketportfolio(i.e.,demandmustequalsupply),ifyouholdthemarketportfoliothenyoumustmakethesamereturnastheaverageinvestor.Ontheotherhand,supposeyoudon’tholdthemarketportfolio,butinsteadholdlessofsomestock,suchasGoogle,thanitsmarketweight.Thismustmeanthatinaggregateallotherinvestorshaveover-weightedGooglerelativetothemarket.Butbecauseotherinvestorsaremoreinformedthanyouare,theymustrealizeGoogleisagooddeal,andsoarehappytoprofitatyourexpense.13.2InformationandRationalExpectations(2of5)RationalExpectationsAllinvestorscorrectlyinterpretandusetheirowninformation,aswellasinformationthatcanbeinferredfrommarketpricesorthetradesofothers.13.2InformationandRationalExpectations(3of5)Regardlessofhowmuchinformationaninvestorhasaccessto,hecanguaranteehimselfanalphaofzerobyholdingthemarketportfolio.13.2InformationandRationalExpectations(4of5)Becausetheaverageportfolioofallinvestorsisthemarketportfolio,theaveragealphaofallinvestorsiszero.Ifnoinvestorearnsanegativealpha,thennoinvestorcanearnapositivealpha,andthemarketportfoliomustbeefficient.13.2InformationandRationalExpectations(5of5)ThemarketportfoliocanbeinefficientonlyifasignificantnumberofinvestorseitherMisinterpretinformationandbelievetheyareearningapositivealphawhentheyareactuallyearninganegativealpha,orCareaboutaspectsoftheirportfoliosotherthanexpectedreturnandvolatility,andsoarewillingtoholdinefficientportfoliosofsecurities.13.3TheBehaviorofIndividualInvestors(1of4)UnderdiversificationandPortfolioBiasesThereismuchevidencethatindividualinvestorsfailtodiversifytheirportfoliosadequately.FamiliarityBiasInvestorsfavorinvestmentsincompanieswithwhichtheyarefamiliarRelativeWealthConcernsInvestorscaremoreabouttheperformanceoftheirportfoliosrelativetotheirpeers13.3TheBehaviorofIndividualInvestors(2of4)ExcessiveTradingandOverconfidenceAccordingtotheC

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M,investorsshouldholdrisk-freeassetsincombinationwiththemarketportfolioofallriskysecurities.Inreality,atremendousamountoftradingoccurseachday.13.3TheBehaviorofIndividualInvestors(3of4)ExcessiveTradingandOverconfidenceOverconfidenceBiasInvestorsbelievetheycanpickwinnersandloserswhen,infact,theycannot;thisleadsthemtotradetoomuchSensationSeekingAnindividual’sdesirefornovelandintenserisk-takingexperiencesFigure13.3NYSEAnnualShareTurnover,1970–2015Source:Figure13.4IndividualInvestorReturnsVersusPortfolioTurnoverSource:B.BarberandT.Odean,“TradingIsHazardoustoYourWealth:TheCommonStockInvestmentPerformanceofIndividualInvestors,”JournalofFinance55(2000)773–806.13.3TheBehaviorofIndividualInvestors(4of4)IndividualBehaviorandMarketPricesIfindividualsdepartfromtheC

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Minrandomways,thenthesedepartureswilltendtocancelout.Individualswillholdthemarketportfolioinaggregate,andtherewillbenoeffectonmarketpricesorreturns.13.4SystematicTradingBiases(1of5)HangingontoLosersandtheDispositionEffectDispositionEffectAninvestorholdsontostocksthathavelosttheirvalueandsellstocksthathaveriseninvaluesincethetimeofpurchase13.4SystematicTradingBiases(2of5)InvestorAttention,Mood,andExperienceStudiesshowthatindividualsaremorelikelytobuystocksthathaverecentlybeeninthenews,engagedinadvertising,experiencedexceptionallyhightradingvolume,orhavehadextremereturns.Sunshinegenerallyhasapositiveeffectonmood,andstudieshavefoundthatstockreturnstendtobehigherwhenitisasunnydayatthelocationofthestockexchange.13.4SystematicTradingBiases(3of5)InvestorAttention,Mood,andExperienceInvestorsappeartoputtoomuchweightontheirownexperienceratherthanconsideringallthehistoricalevidence.Asaresult,peoplewhogrewupandlivedduringatimeofhighstockreturnsaremorelikelytoinvestinstocksthanarepeoplewhoexperiencedtimeswhenstocksperformedpoorly.13.4SystematicTradingBiases(4of5)HerdBehaviorWheninvestorsmakesimilartradingerrorsbecausetheyareactivelytryingtofolloweachother’sbehaviorInformationalCascadeEffectsWheretradersignoretheirowninformationhopingtoprofitfromtheinformationofothers13.4SystematicTradingBiases(5of5)ImplicationsofBehavioralBiasesIfindividualinvestorsareengaginginstrategiesthatearnnegativealphas,itmaybepossibleformoresophisticatedinvestorstotakeadvantageofthisbehaviorandearnpositivealphas.13.5TheEfficiencyoftheMarketPortfolio(1of4)TradingonNewsorRecommendationsTakeoverOffersIfyoucouldpredictwhetherthefirmwouldultimatelybeacquiredornot,youcouldearnprofitstradingonthatinformation.Figure13.5ReturnstoHoldingTargetStocksSubsequenttoTakeoverAnnouncementsSource:AdaptedfromM.Bradley,A.Desai,andE.H.Kim,“TheRationaleBehindInterfirmTenderOffers:InformationorSynergy?”JournalofFinancialEconomics11(1983)183–206.13.5TheEfficiencyoftheMarketPortfolio(2of4)TradingonNewsorRecommendationsStockRecommendationsJimCramermakesnumerousstockrecommendationsonhistelevisionshow,MadMoney.Forstockswithnews,itappearsthatthestockpricecorrectlyreflectsthisinformationthenextday,andstaysflat(relativetothemarket)subsequently.Ontheotherhand,forthestockswithoutnews,thereappearstobeasignificantjumpinthestockpricethenextday,butthestockpricethentendstofallrelativetothemarket,generatinganegativealpha,overthenextseveralweeks.Figure13.6StockPriceReactionstoRecommendationsonMadMoneySource:AdaptedfromJ.Engelberg,C.Sasseville,J.Williams,“MarketMadness?TheCaseofMadMoney,”SSRNworkingpaper,2009.13.5TheEfficiencyoftheMarketPortfolio(3of4)ThePerformanceofFundManagersFundManagerValue-AddedThemedianmutualfundactuallydestroysvalue.Mostfundmanagersappeartotradesomuchthattheirtradingcostsexceedtheprofitsfromanytradingopportunitiestheymayfind.ReturntoInvestorsNumerousstudiesreportthattheactualreturnstoinvestorsoftheaveragemutualfundhaveanegativealpha.Superiorpastperformanceisnotagoodpredictorofafund’sfutureabilitytooutperformthemarket.Figure13.7ManagerValueAddedandInvestorReturnsforU.S.MutualFunds(1977–2011)Figure13.8BeforeandAfterHiringReturnsofInvestmentManagersSources:A.GoyalandS.Wahal,“TheSelectionandTerminationofInvestmentManagementFirmsbyPlanSponsors,”JournalofFinance63(2008):1805–1847andwithJ.Busse,“PerformanceandPersistenceinInstitutionalInvestmentManagement,”JournalofFinance65(2010):765–790.13.5TheEfficiencyoftheMarketPortfolio(4of4)TheWinnersandLosersTheaverageinvestorearnsanalphaofzerobeforeincludingtradingcosts.Beatingthemarketshouldrequirespecialskillsorlowertradingcosts.Becauseindividualinvestorsarelikelytobeatadisadvantageonbothcounts,theC

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Mwisdomthatinvestorsshould“holdthemarket”isprobablythebestadviceformostpeople.13.6Style-BasedTechniquesandtheMarketEfficiencyDebate(1of6)SizeEffectsExcessReturnandMarketCapitalizationsSmallmarketcapitalizationstockshavehistoricallyearnedhigheraveragereturnsthanthemarketportfolio,evenafteraccountingfortheirhigherbetas.ExcessReturnandBook-to-MarketRatioHighbook-to-marketstockshavehistoricallyearnedhigheraveragereturnsthanlowbook-to-marketstocks.Figure13.9ExcessReturnofSizePortfolios,1926-2018Source:DatacourtesyofKennethFrench.Figure13.10ExcessReturnofBook-to-MarketPortfolios,1926–2018Source:DatacourtesyofKennethFrench.13.6Style-BasedTechniquesandtheMarketEfficiencyDebate(2of6)SizeEffectSizeEffectsandEmpiricalEvidenceDataSnoopingBiasGivenenoughcharacteristics,itwillalwaysbepossibletofindsomecharacteristicthatbypurechancehappenstobecorrelatedwiththeestimationerrorofaveragereturns.TextbookExample13.2(1of3)RiskandtheMarketValueofEquityProblemConsidertwofirms,SMIndustriesandBiGCorporation,whichareexpectedtopaydividendsof$1millionperyearinperpetuity.SM’sdividendstreamisriskierthanBiG’s,soitscostofcapitalis14%peryear.BiG’scostofcapitalis10%.Whichfirmhasthehighermarketvalue?Whichfirmhasthehigherexpectedreturn?Nowassumebothstockshavethesameestimatedbeta,eitherbecauseofestimationerror,orbecausethemarketportfolioisnotefficient.Basedonthisbeta,theC

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Mwouldassignanexpectedreturnof12%tobothstocks.Howdothemarketvaluesofthefirmsrelatetotheiralphas?TextbookExample13.2(2of3)SolutionThetimelineofdividendsisthesameforbothfirms:TocalculatethemarketvalueofSM,wecalculatethepresentvalueofitsfutureexpecteddividendsusingtheperpetuityformulaandacostofcapitalof14%:Similarly,themarketvalueofBiGisTextbookExample13.2(3of3)SMhasthelowermarketvalue,andahigherexpectedreturn(14%vs.10%).Italsohasthehigheralpha:Consequently,thefirmwiththelowermarketvaluehasthehigheralpha.AlternativeExample13.2A(1of4)ProblemSupposetwofirms,ABCandXYZ,arebothexpectedtopayadividendstreamof$2.2millionperyearinperpetuity.ABC’scostofcapitalis12%peryear,andXYZ’scostofcapitalis16%.Whichfirmhasthehighermarketvalue?Whichfirmhasthehigherexpectedreturn?

AlternativeExample13.2A(2of4)ProblemNowassumebothstockshavethesameestimatedbeta,eitherbecauseofestimationerrororbecausethemarketportfolioisnotefficient.Basedonthisbeta,theC

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Mwouldassignanexpectedreturnof15%tobothstocks.Whichfirmhasthehigheralpha?

Howdothemarketvaluesofthefirmsrelatetotheiralphas?AlternativeExample13.2A(3of4)SolutionABChasanexpectedreturnof12%.XYZhasanexpectedreturnof16%.AlternativeExample13.2A(4of4)SolutionThefirmwiththelowermarketvaluehasthehigheralpha.13.6Style-BasedTechniquesandtheMarketEfficiencyDebate(3of6)MomentumMomentumStrategyBuyingstocksthathavehadpasthighreturnsand(short)sellingstocksthathavehadpastlowreturns13.6Style-BasedTechniquesandtheMarketEfficiencyDebate(4of6)ImplicationsofPositive-AlphaTradingStrategiesTheonlywaypositive-alphastrategiescanpersistinamarketisifsomebarriertoentryrestrictscompetition.However,theexistenceofthesetradingstrategieshasbeenwidelyknownformorethan15years.Anotherpossibilityisthatthemarketportfolioisnotefficient,andtherefore,astock’sbetawiththemarketisnotanadequatemeasureofitssystematicrisk.13.6Style-BasedTechniquesandtheMarketEfficiencyDebate(5of6)ImplicationsofPositive-AlphaTradingStrategiesProxyErrorThetruemarketportfoliomaybeefficient,buttheproxywehaveusedforitmaybeinaccurateBehavioralBiasesByfallingpreytobehavioralbiases,investorsmayholdinefficientportfolios13.6Style-BasedTechniquesandtheMarketEfficiencyDebate(6of6)ImplicationsofPositive-AlphaTradingStrategiesAlternativeRiskPreferencesandNon-TradableWealthInvestorsmaychooseinefficientportfoliosbecausetheycareaboutriskcharacteristicsotherthanthevolatilityoftheirtradedportfolio.13.7MultifactorModelsofRisk(1of11)

TheexpectedreturnofanymarketablesecurityisWhenthemarketportfolioisnotefficient,wehavetofindamethodtoidentifyanefficientportfoliobeforewecanusetheaboveequation.However,itisnotactuallynecessarytoidentifytheefficientportfolioitself.Allthatisrequiredistoidentifyacollectionofportfoliosfromwhichtheefficientportfoliocanbeconstructed.13.7MultifactorModelsofRisk(2of11)UsingFactorPortfolios

GivenNfactorportfolioswithreturnstheexpectedreturnofassetsisdefinedasfollows:arethefactorbetas13.7MultifactorModelsofRisk(3of11)UsingFactorPortfoliosSingle-FactorModelAmodelthatusesoneportfolioMulti-FactorModelAmodelthatusesmorethanoneportfoliointhemodelTheC

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Misanexampleofasingle-factormodelwhiletheArbitragePricingTheory(A

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T)isanexampleofamultifactormodel.13.7MultifactorModelsofRisk(4of11)UsingFactorPortfoliosAself-financingportfoliocanbeconstructedbygoinglonginsomestocksandgoingshortinotherstockswithequalmarketvalue.Ingeneral,aself-financingportfolioisanyportfoliowithportfolioweightsthatsumtozeroratherthanone.13.7MultifactorModelsofRisk(5of11)UsingFactorPortfoliosIfallfactorportfoliosareself-financing,then13.7MultifactorModelsofRisk(6of11)SelectingthePortfoliosMarketCapitalizationStrategyAtradingstrategythateachyearbuysaportfolioofsmallstocksandfinancesthispositionbyshortsellingaportfolioofbigstockshashistoricallyproducedpositiverisk-adjustedreturns.Thisself-financingportfolioiswidelyknownasthesmall-minus-big(S

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B)portfolio.13.7MultifactorModelsofRisk(7of11)SelectingthePortfoliosBook-to-MarketRatioStrategyAtradingstrategythateachyearbuysanequallyweightedportfolioofstockswithabook-to-marketratiolessthanthe30thpercentileofN

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Efirmsandfinancesthispositionbyshortsellinganequallyweightedportfolioofstockswithabook-to-marketratiogreaterthanthe70thpercentileofN

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Estockshashistoricallyproducedpositiverisk-adjustedreturns.Thisself-financingportfolioiswidelyknownasthehigh-minus-low(H

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L)portfolio.13.7MultifactorModelsofRisk(8of11)SelectingthePortfoliosPastReturnsStrategyEachyear,afterrankingstocksbytheirreturnoverthelastoneyear,atradingstrategythatbuysthetop30%ofstocksandfinancesthispositionbyshortsellingbottom30%ofstockshashistoricallyproducedpositiverisk-adjustedreturns.Thisself-financingportfolioiswidelyknownasthepriorone-yearmomentum(PR

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R)portfolio.

Thistradingstrategyrequiresholdingtheportfolioforayear,andtheprocessisrepeatedannually.13.7MultifactorModelsofRisk(9of11)SelectingthePortfoliosFama-French-Carhart(FFC)FactorSpecificationsTable13.1FFCPortfolioAverageMonthlyReturns,1927–2018FactorPortfolioAverageMonthlyReturn(%)95%ConfidenceBand(%)MKtminusrsubf0.66plusorminus0.32S

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B0.26plusorminus0.19H

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L0.38plusorminus0.21P

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R0.66plusorminus0.28Source:DatacourtesyofKennethFrench/pages/faculty/ken.french/data_library.htmlTextbookExample13.3(1of3)UsingtheF

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CFactorSpecificationtoCalculatetheCostofCapitalProblemYouareconsideringmakinganinvestmentinaprojectinthefastfoodindustry.Youdeterminethattheprojecthasthesamelevelofnon-diversifiableriskasinvestinginMcDonald’sstock.DeterminethecostofcapitalbyusingtheF

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Cfactorspecification.TextbookExample13.3(2of3)SolutionYoudecidetousedataoverthepasttenyearstoestimatethefactorbetasofMcDonald’sstock(ticker:M

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D).Therefore,youregressthemonthlyexcessreturn(therealizedreturnincashmonthminustherisk-freerate)ofMcDonald’sstockonthereturnofeachportfolio.Thecoefficientestimatesarethefactorbetas.Herearetheestimatesofthefourfactorbetasandtheir95%confidenceintervalbasedondatafrom2007–2017:FactorBetaEstimateLower95%Upper95%Mkt0.590.440.75SMBminus0.53minus0.81minus0.25HMLminus0.02minus0.270.24PR1YR0.13minus0.010.27Usingtheseestimatesandarisk-freemonthlyrateof2.4%/12=0.20%,youcancalculatethemonthlyexpectedreturnforinvestinginMcDonalds’sstock:TextbookExample13.3(3of3)ExpressedasanA

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R,theexpectedreturnisThus,theannualcostofcapitaloftheinvestmentopportunityisabout6.6%.(Note,however,thesubstantialuncertaintybothinthefactorbetasandtheirexpectedreturns.)Asacomparison,astandardC

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Mregressionoverthesametimeperiodleadstoanestimatedmarketbetaof0.45forMcDonalds’s—themarketbetadiffersfromtheestimateof0.59abovebecauseweareusingonlyasinglefactorintheC

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Mregression.Usingthehistoricalexcessreturnonthemarketimpliesanexpectedreturnonthemarketimpliesanexpectedreturnofpermonth,orabout6.0%peryear.AlternativeExample13.3A(1of3)ProblemYouareconsideringmakinganinvestmentinaprojectinthesemiconductorindustry.Theprojecthasthesamelevelofnon-diversifiableriskasinvestinginIntelstock.AlternativeExample13.3A(2of3)ProblemAssumeyouhavecalculatedthefollowingfactorbetasforIntelstock:DeterminethecostofcapitalbyusingtheF

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Cfactorspecificationifthemonthlyrisk-freerateis0.5%.AlternativeExample13.3A(3of3)SolutionTheannualcostofcapitalisAlternativeExample13.3B(1of3)ProblemYouareconsideringmakinganinvestmentinaprojectinthefinancialservicesindustry.Theprojecthasthesamelevelofnon-diversifiableriskasinvestinginBankofAmericastock.AlternativeExample13.3B(2of3)ProblemAssumeyouhavecalculatedthefollowingfactorbetasforBankofAmericastock:DeterminethecostofcapitalbyusingtheF

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Cfactorspecificationifthemonthlyrisk-freerateis0.1%.AlternativeExample13.3B(3of3)SolutionTheannualcostofcapitalis13.7MultifactorModelsofRisk(10of11)TheCostofCapitalwithFama-French-CarhartFactorSpecificationAlthoughitiswidelyusedinresearchtomeasurerisk,thereismuchdebateaboutwhethertheF

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CfactorspecificationisreallyasignificantimprovementovertheC

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M13.7MultifactorModelsofRisk(11of11)TheCostofCapitalwithFama-French-CarhartFactorSpecificationOneareawhereresearchershavefoundthattheF

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CfactorspecificationdoesappeartodobetterthantheC

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Mismeasuringtheriskofactivelymanagedmutualfunds.ResearchershavefoundthatfundswithhighreturnsinthepasthavepositivealphasundertheC

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M.WhenthesametestswererepeatedusingtheF

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Cfactorspecificationtocomputealphas,noevidencewasfoundthatmutualfundswithhighpastreturnshadfuturepositivealphas.13.8MethodsUsedinPractice(1of2)FinancialManagersAsurveyofCFOsfoundthat73.5%ofthefirmsusedtheC

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Mtocalculatethecostofcapital40%usedhistoricalaveragereturns16%usedthedividenddiscountmodelLargerfirmsweremorelikelytousetheC

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MthanweresmallerfirmsFigure13.11HowFirmsCalculatetheCostofCapitalSource:J.R.GrahamandC.R.Harvey,“TheTheoryandPracticeofCorporateFinance:EvidencefromtheField,”JournalofFinancialEconomics60(2001):187–243.13.8MethodsUsedinPractice(2of2)InvestorsInarecentstudyofthedifferentriskmodelsexamined,investorbehaviorwasfoundtobemostconsistentwiththeC

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M.ChapterQuiz(1of3)Ifinvestorsbuyastockwithapositivealpha,whatisthelikelyeffectonitspriceandexpectedreturn?Howcananuninformedinvestorguaranteethemselvesanon-negativ