MS-為氣候變化敞口定價(jià) Pricing climate change exposure 2024

ZurichOpenRepositoryandArchiveUniversityofZurichUniversityLibraryPricingclimatechangeexposureriskpremiumisinsignificantbutexhibitsaperiodwithapositiveriroftheriskpremiumprimarilyoriginatesfromuncerJournalArticlePricingClimateChangeExposure*ZachariasSautnertApril2022Abstractbymarketparticipantsinearningscallstoa?rm’sclimate-relatedrisksandopportunities.Whenextractedfromrealizedreturns,theunconditionalriskpremiumisinsigni?cantbutthereafter.Forward-lookingexpectedreturnproxiesdeliveranunconditionallypositiveriskpremium,withmaximumvaluesof0.5%to1%p.turnproxyexplicitlyaccountsforthehigheropportunitiesandthelowercrashrisksthatcharacterizehigh-exposurestocks.This?ndingarisesasthepricedprimarilyoriginatesfromuncertaintyaboutclimate-relatedupsideopportunities.Inthetimeseries,theriskpremiumisnegativelyassociatedwithgreeninnovation,BigThreeholdings,andESGfund且ows,andpositivelyassociatedwithclimatechangeadaptKeywords:Climate?nance,climatechangeexposure,climateriskpremium,tailrisk,climate*WearegratefultoColinMayer,ananonymousAssociateEditor,tworeferees,EmirhanIlhan,MarcinKacper-czyk,SlavaFos,andLukaszPomorskiforvaluableinput.WealsothankseminarsparticipantsatACPRResearchInitiativeatBanquedeFrance,BI(Oslo),FrankfurtSchoolofFinance&Management,FulcrumAssetMan-agement,ShanghaiUniversityofFinanceandEconomics,thesecondSustainableFinanceForum,andDukeKushanUniversityforusefulcomments.FundingisprovidedbytheDeutscheForschungsgemeinschaftProjectID403041268-TRR266(VanLentandZhang);theInstituteforNewEconomicThinking(INET)(VanLent);the111Project(B18033)(Zhang);andtheShanghaiPujiangProgram(Zhang).FrankfurtSchoolofFinance&ManagementandECGI;PostalAddress:Adickesallee32-34,60322FrankfurtamMain,Germany;E-mail:z.sautner@fs.de.FrankfurtSchoolofFinance&Management;PostalAddress:Adickesallee32-34,60322FrankfurtamMain,Germany;E-mail:l.vanlent@fs.de.§FrankfurtSchoolofFinance&Management;PostalAddress:Adickesallee32-34,60322FrankfurtamMain,Germany;E-mail:vilkov@.?InstituteofAccountingandFinance,ShanghaiUniversityofFinanceandEconomics;PostalAddress:GuodingRoad777,200433,Shanghai,China;E-mail:zhangruishen@.Electroniccopyavailableat:https://ssrn.co1Introductiontoalow-carboneconomyafects?nancialmarkets.Yet,thisbodyofliteratureisstillinitsandopportunitiesafectstockreturns.Thispaperemploystime-varyingmeasuresofhowmarketparticipantsperceiveinetal.(2022)(SvLVZ),whousequarterlyearnibymarketparticipantsto?rms’climate-relatedrisksandopportunities.1Tomeasurea?rm’sustocomplementrelatedworkexaminingtheassetpricingef1AsrecentlyhighlightedbytheTaskForceonClimate-relatedFinancialDisclosures,?nancialmarketsneedinformationonrisksandopportunitiestoevaluatetheimpactofclimatechange(see/).2WefollowSvLVZinde?ning“exposure”toclimatechangebasedontheshareoftheconversationinanearningscallthatisdevotedtothattopic.Thisde?nitionofexposureisdiferentfromhowriskexposureisde?nedintheasset-pricingliterature.Hence,SvLVZ’smeasuresarenotintendedtocapturethecovariancewithaggregate丑uctuations.Thisterminologyfollowsabroaderliteraturethatusesearningscallstoidentify?rms’variousrisksandopportunities(Hassanetal.2019,2021a,b,Jamilovetal.2021,Hassanetal.2021c).1Electroniccopyavailableat:https://ssrn.co(2021a,b),Ilhanetal.(2021),G¨orgenetal.(2019)orInetal.(2019)examinehowcarbonemissionsarepricedinequityoroptionmarkets,eitherasa?rmcharacterSimilarly,Hongetal.(2019),Addoumetal.(2020)orKruttlietal.(2021)examinetheassettheefectsofclimatechangeonindividualstocksarehighlyuncertain,andBarnettetdemonstratetheoreticallythatthisuncertaintyshouldbepriced.Climatechangeuncertaintytaxbrown)activities.Concerningtechnology,itisalsodi伍culttopredictwhetherinnovatstoragewillsucceedandtowhatextentbatterytechnologywillseebr(Thomas2021),ashasvolcanicactivitytoinvestorsinsolarinstallations.Theseexamplesillustratetheuncertaintiesthatmakeitdi伍cultforinvestorstoevaluatehowindividualstocksBroadersocietaltrendstowardESGandimpactinvestingcanalsoafecttheriskpremium2Electroniccopyavailableat:https://ssrn.cotuallyambiguous.Theyalsosignifythattheriskpremiumislikelytochangeovertime,asitremainsunclearwhattheeventualequilibriumwillresemble.Oneimplicationisthatanyesti-ourunderstandingofhowclimatechangeevolve,bothforrealizedandexpectedreturns?Third,unconditionallyanddynamically,whatclimate-relatedriskquantitiesareassociatproxybyMartinandWagner(2019)(MW)assumesthatvarianceisthesu伍cientriskstatistic3Electroniccopyavailableat:https://ssrn.coofthemarketindexandthestocksintheindex.Somewhatdiferently,Chabi-Yoetal.(2022)(GLB)assumethatinvestorsalsoconsiderextremerisksandopportunities,sotheirapproachexplicitlyaccountsforreturns’higher-ordermomentsintheriskpremiuclimatechangeexposureincreasestheMW-basedriskpremiumby0.09%p.a.(t-statof2.88),andtheGLB-basedriskpremiumby0.18%p.a.(t-statof3.12).Wedemonstratethatthesemodestunconditionalriskpremiumsmasklargepositiveriskulatory,andphysicalshocks,thepositiveunconditionalr 3Wedonot?ndsigni?cantefectsforameasureofclimate-relatedlitigationexposure.OnereasoncouldbethatclimatelitigationisstillarelativelyrecentphenomenonintheU.S.,andsuccessfullawsuitsaretheexception.4Resultsarerobusttoapplyinganexposuremeasurethatre丑ectsthenegativetone(orsentiment)oftheclimatechangediscussionsandtousingperturbedexposuremeasuresthatrandomlydrop5%ofthebigramsusedtoconstructthemeasure.4Electroniccopyavailableat:https://ssrn.coofclimate-relatedconcernspremiumandexhibitsomesubtlediferencesrelativetoeachother.FowiththeMW-basedpremiumgraduallyrisingtoabout0.5%p.a.in2012andtheGLB-based2015,bothpremiumsreverttoalmostzero,buttheMWproxystaysataslightlyhigherlevel.insights,becauseeatheriskpremiumforbothproxies,5Thistime-seriespatternalignswiththemodelinBansaletal.(2021),who?ndthat“good”stockssigni?cantlyoutperform“bad”stocksduringgoodeconomictimesbutunderperformduringbadtimes(assumingthatstockswithhighclimatechangeexposureareperceivedasgoodstocks).6ThisconclusionisconsistentwithBoltonandKacperczyk(2021b),whoseanalysisalsorevealsthedistinctefectsofthecarbonriskpremiumovertimeandacrosscountries.5Electroniccopyavailableat:https://ssrn.corelatedopportunityshocks.Assuchopportunitiesareuncertainverylowpayofs,theycauseinvestorstodemandariskpremium.7Third,且owsintoESGfundsdecreasethreducingtheconditionalriskpremium.9Fourth,theoilpricepositivelyrelatestother7Stockswithhighexposuretoclimate-relatedopportunityshocksmaycommandanunconditionalriskpremiumbecauseofahigherexpectedvariance.Theassociatedriskpremiumdeclineswhenthevariancedecreases,anditmayevenreachzeroifhigherexposurealsomeanshigherupsidepotentialandlowerdownsidecrashrisk.8Adaptationplansalsoprovidenewopportunitiesfor?rms,whichshouldreducetheriskpremium.However,ourresultsuggeststhattheregulationchanneldominatestheopportunitychannelforthisvariable.9Thisefectdisappearsinsomespeci?cationsthatcontrolfortheoilprice,thepriceofcarbonemissionallowances,andBigThreeholdings.6Electroniccopyavailableat:https://ssrn.copremium,probablybecausehighoilpricesgasactivities(Acemogluetal.2020),makingnon-traditionalinvestmentsinriskier.Withourriskpremiumoriginatingmostlyfromclimate-relatedopportunities,highoilFifth,higheraggregateholdingsofthe“BigThree”(Vanguard,Blackrock,andStateStreet)especiallydownsidetailrisk(Ilhanetal.2021),higherexposure-weightedholdingsbytheBigThreereducetheriskpremium.ThisresultisstrongerfortheGLBproxy,corroboratingtheideathatthisriskpremiumchannelgoesthroughtailrisk(inadditiontovolatility).Overall,ourpaperaddresinvestors’attentiontoclimatetopicscanoccurduringthatshortperiod.f(variance)risksfromthoseoftailandhigher-order7Electroniccopyavailableat:https://ssrn.coofissuespotentiallydrivingreturns(e.g.,temperaturechanges,ESGawarenessofinvestors,orlinkedtotheESG-CAPMframeworkofPedersenetal.(2021)anmodelswith“uncertaintyaboutthepathofclimatechange”(Giglioetal.2021),inwhichhigh2DataandVariableMeasurement2.1Firm-LevelClimateChangeExposure2.1.1VariableMeasurementfromtranscriptsofquarterlyearningscalls.Earningscallsallowmarketparticipantstolisten2010).Earningscallsprovariousrisksandopportunities,includingclimatechange.TheSvLVZmeasurescapturethe10AstepinthesamedirectionisprovidedbyK¨olbeletal.(2021),whoshowthata10-K-basedmeasureofclimatechangeexposureafectstheCDStermstructure.8Electroniccopyavailableat:https://ssrn.coTomeasureclimatechangeportunity,regulatory,andphysicalshocks(COpp,CReg,andCPhy,respectively).Basedonthesebigramsets,SvLVZconstructfourmetricsinatranscript,scaledbythelengthofthetranscript:whereb=1,...Bi,tarethebigramsappearinginthetranscriptof?rmiinquartert,where1[·]CPhy).TheoverallmeasureislabeledasCCExposure,andthethreetopic-basedmeasuresasCCExposureOpp,CCExposureReg,andCCExposurePhy,respectively.1211SvLVZ’sdatacanbeaccessedpubliclyonhttps://osf.io/fd6jq/.TheSvLVZdataareavailablefrom01/2002onward,butourtestsincludedatafrom01/2005tomatchthemeasureswithotherdatasourcesandtoallowforaburn-inperiod(thisensuresthatareasonablenumberofstocksobtainnon-zeroexposurevaluesatthestartoftheestimation).OursampleincludesallstocksincludedintheS&P500from2000onward.12SvLVZevaluatehowstronglyCCExposuredependsonindividualbigramsintheinitialbigramlistbyper-formingaperturbationtest.Theysuccessivelyexcludeoneinitialbigramatatime,andthenrecomputeeachtimethemodi?edsetofbigramsaswellasthemodi?edexposuremeasure.WhentheycalculatethecorrelationofeachoftheseexposuremeasureswithCCExposure,thecorrelationsareallabove85%.ThismeansthatCCExposuredoesnotdependmuchonthespeci?cinitialseedbigrams.9Electroniccopyavailableat:https://ssrn.cospeci?cordrivenbyinvestorattitudestowardparticularindustries.Tothisend,wecomputeameasureofindustry-levelexposure,CCExposureInd,byaveragingCCExposureacrossalllatethe“pure”stock-speci?ccomponentCCExposureResasCCExposure-CCExposureInd.thenegativetoneorsentimentoftheclimatechangediscussions.CCSentimenTodemonstratethattheSvLVZalgoritpurpose-developinthispaperameasureoflitigationexposure(CCExposureLtg),whichcountsof21litigationkeywords,including“l(fā)itigation,”“l(fā)awsuit,”“sued,”or“classaction.”Electroniccopyavailableat:https://ssrn.co2.1.2VariableTransformation:TimeStructureandMatchingProcedurewiththeexpectedreturnpearningscall,subsequentca?rststep,wematchthemonthofatranscript’sdatewiththeend-of-monthdateintheCRSPMonthlyStockFileandrecordtothatdatetheexposuremeasurefromSvLVZ(weinitiallysetxi,twithitsexponentiallyweightedmovingaverageyi,t:wherethedecayαisrelatedtohalf-lifeτasα=1-exp(-ln(2)/τ).Wenormalizethemeasuresmonth,toobtaintherespectiveriskp13Sometranscriptsmaycontainfewerclimatechangebigrams,notbecauseclimateissuesarenotperceivedasimportantanymore,butbecausetheywereexhaustivelydiscussedinarecentearningscall.Electroniccopyavailableat:https://ssrn.co2.2RealizedandExpectedReturnsreturnorRET,iscomputedasthenext-monthrealizedreturnminustheone-monthTreasurybillrateforthecorrespondingperiod.AconcernwiththisproxyisthatitmaynotworkwellrecentworkbyMartinandWagner(2019)andChabi-Yoetal.(2022).15MartinandWagner(2019)(MW)derivetheirproxyaslowerboundexpectedexcessreturn,thatis,asEt[Rt+1]-Rf,t≥LBt(KadanandTang2020useasimilarrisksandasymmetryinthereturndistribution(beyondtheportionsspannedbytheofindividualstocksandthemarketindex).ofinvestorswhoconside14AsElton(1999)noted:“AlmostallthetestingIamawareofinvolvesusingrealizedreturnsasaproxyforexpectedreturns.[It]reliesonabeliefthat[..]realizedreturnsarethereforeanunbiasedestimateofexpectedreturns.However,Ibelievethatthereisampleevidencethatthisbeliefismisplaced.”15Forrecentapplications,seeCieslaketal.(2019),whousetheequityriskpremiumproxyfromMartin(2017)andAietal.(2022),whotakeanimpliedvariancemeasureasaproxyforastock’sexpectedreturn.Electroniccopyavailableat:https://ssrn.cowherewi,tisthevalueweightofstockiinthemarketindex(S&P500),whereIVt,t+△tistheimpliedvarianceofmarketreturns(S&P500),andwhereIVi,t,t+△tisstocki’simpliedvariance.16ThegeneralizedlowerboundsofChabi-Yoetal.(2022)(GLB)accountfortheentirerisk-neutraldistribution,implicitlyconsideringallhigher-ordermoments,andcavariance).17Formally,itiscalculatedas:whereEdenotestherisk-neutralexpectation,where?θ(x)=xθ+1,andwhereΘi,tisthestock-Yoetal.(2022).18WeexplorediferencesbetweentheMWandGLBproxiestoobtaininsightsintoclimate-relatedhigher-orderrisksandhowmark2.3RiskQuantitiesofmarketparticipantsforthefuturereturndistributionuptoagivenoptionmaturity.19Tomeasuretheimpliedvariance(IVi,t)ofstockiattimet,weusetheMartin(2017)varianceswaprateIVt,t+△tformaturityt+△t,constructedfromthepricesofout-of-the-money(OTM)calls16Theweightsarerescaledtoadduptooneforallstockswithnon-missingimpliedvariance.17Backetal.(2022)?ndthat,inconditionalsettings,boundsbasedonsecond-ordermomentsarenotnecessarilytight;thatis,theyprovideawell-performingbutbiasedproxyforconditionalexpectedreturns.Chabi-Yoetal.(2022)showthattheGLBmeasureisaconditionallyvalidandtightproxyofexpectedexcessreturns.18Thedataareavailableon/10.17605/OSF.IO/Z2486(seeVilkov2020).19Thebene?tofthesevariables,comparedtoequivalentsunderthephysicalmeasure,istheirforward-lookingcharacter.Forexample,theimpliedvarianceisapredictorofthefuturerealizedvariance(PoonandGranger2003),theimpliedskewnessallowsforthequanti?cationoftheasymmetryoftherisk-neutraldistribution,andtheimpliedvolatilitysloperepresentsaheuristicproxyfortherelativepriceofprotectionagainsttailrisk(Kellyetal.2016).Thecostincludesapotentialbiasstemmingfromtheriskpremiumefect(seeVanden2008,Changetal.2012,Cremersetal.2015,DeMigueletal.2013).Electroniccopyavailableat:https://ssrn.coC(t,t+△,K)andputsP(t,t+△,K)withstrikepricesK(weomitthesubscriptiforbrevity):IVt,t+△t=whereStandFt,t+△tarethespotandforwardpricesoftheunderlyingstock,andRf,tisthegrossrisk-freerate.Weuseasimilarapproachfortheimpliedskewness(ISkewi,t)andfortheimpliedkurtosis(IKurti,t),applyingtheformulasforthelogreturnsinBakshietal.(2003).20(SlopeUi,t)fromtheat-the-money(ATM)point.AsinKellyetal.(2016),themeasuresaretheslopesoffunctionsrelatiSlopeDi,tbyregressingtheimpliedvolatilitiesofputswithdeltasbetween-0.1and-0.5ontheirdeltas(andaconstant).ForSlopeUi,t,weregressimpliedvolatilitiesofcallswithdeltasarelativelyhighercostofprotectionagainsttailrisks(SlopeDi,t)orrelativelymoreexpensivegrowthopportunities(SlopeUi,t).Themeasuresarepositivearetypicallymorecostly(intermsofimpliedvolatilities)thanATMoptions.2.4InstitutionalandMarketFactorsOurtime-seriesregressionsincllevelofmontht.GreenInnovationtisamonthlymeasureofthetotalnumberofgreenpatents 20WeapproximateeachintegralinEquation(6)forIVi,tusinga?nitesumof500optionprices(wedolikewiseforsimilarintegralsintheformulasforISkewi,tandIKurti,t).WeselectOTMoptionswithabsolutedeltasstrictlysmallerthan0.5forputsandweaklysmallerforcalls,forthematurityof30days.Weinterpolatetheimpliedvolatilitiesasafunctionofmoneyness(strikeoverspotprice)fortherangebetweenavailablemoneynesspoints,andthenextrapolateby?llinginthemissingextremedatabytheimpliedvolatilityvaluesfromtheleftandrightboundariesto?llinthemoneynessrangeof[1/3,3]withatotalof1,001points.Fortheinterpolations,weuseapiecewisecubicHermiteinterpolatingpolynomial.21Theregressioncoe伍cientapproximatesanaveragederivativeofthevolatilitysmile.BecausedeltasoffarOTMputsarelessnegativethanATMdeltas,withmoreexpensiveOTMputs,wegetalargerpositiveregressioncoe伍cient;forcalls,thedeltasdecreasewithanoptiongettingmoreOTM,andwithmoreexpensiveOTMcalls,theregressioncoe伍cientismorenegative.Electroniccopyavailableat:https://ssrn.cotostate-ledclimatechavaryintheirscopesandstrategies,theyallsperisks.22WeconstructtheaggregatemonthlytimeseriesofAdaptationtas:where1AdaptedStatei,tisoneafter(oron)datetifa?rm’sheadquartersarelocatedinastateadoptinganadaptationplan.Thus,AdaptationtmeasurestheproportionofclimatechangefundsfromMorningstar’s2021SustainableFundsU.S.LandscapeReport(Pastoretal.2021a)andmatchthesefundswiththeCRSPSurvivor-Bias-FreeU.S.MutualFundstocalculatethejduringmonthtas:ESGFundFlowsj,t=TNAj,t-(1+Rj,t)×TNAj,t,(8)whereTNAj,tisthechangeintotalnetassetsandwhereRj,tisfundj’sreportedreturn(tore且ectappreciation).Aggregatingthismeasureacrossallfundsjinmontht,wegetESGFundFlowst.BigThreeIOtistheaggregateCCExposure-weightedownershipbyVanguard,BlackRock,andStateStreet(“BigThree”).ThevariableiscomputedeachmonthastheCCExposure-weightedholdingsbytheBigThreeacrossS&P500stocks(detailsintheDataAppendix):22Asof2020,17statesandtheDistrictofColumbiahave?nalizedclimatechangeadaptationplans.Electroniccopyavailableat:https://ssrn.cowhereBigThreei,tarethepercentageholdingsbytheBigThreeinstockiattimet.Intuitively,BigThreeIOtre且ectstheclimatechangeexposureoftheBigThreerelativetotheexposureheldinthemarket.Thisvariableisavailablefrom01/2005to12/2017.23OilPricetistheWTISpotpriceandCO2PricetisthemonthlyfuturespriceofCO2emissionallowances(availablesince08/2005fromtheEUEmissionTradingSystem).2.5SummaryStatisticsTable1reportssummarystatisticsofthemeasuresthatvaryatthestock-monthlevel.CCExposurestocks.CCExposureIndisonaveragesimilartothegeneralmeasurebutlessvolatile.Bycon-struction,CCExposureResisonaveragezero.Thetopic-basedexwhichcomparesto7.0%and9.3%fortheexpectedreturnproxiesbyMWandGLB.Realizedexcessreturns(RET)arenoisier(standarddeviationof112.6%)thantheMWandGLBprox-ies(standarddeviationsof9.0%and10.1%,respectively).OATable1providesunconditional3UnconditionalRiskPremiumforClimateChangeExposure3.1RiskPremiumforClimateChangeExposure:PredictedEfectsCCExposure.Oneviewholdsthathigh-exposurestocksshouldberiskierandearnapositive23BigThreeIOtishighlycorrelatedwithAdaptationtandESGFundFlowst.Tomitigatemulticollinearityconcerns,weregressBigThreeIOtonthetwoothervariables(andaconstant)toobtainaregressionresidualthatweuseintheestimationbelow.Electroniccopyavailableat:https://ssrn.coVariableSTDPanelA:ClimateChangCCExposurei,tCCExposure,dCCExposure,sCCExposure,pCCExposure,gCCExposure,yCCExposure,gCCSentimentegPanelB:ExpectedExcessReturnProxiesRETi,t(p.a.)MWi,t(p.a.)GLBi,t(p.a.)Marketi,tSize(SMB)i,tValue(HML)i,tMomentum(WML)i,tProfitability(RMW)i,tInvestment(CMA)i,tPanelD:RiskQuantitiesIVi,tISkewi,tIKurti,tSlopeUi,tSlopeDi,tPanelE:FundamentalsandMarketCharacteristicsLog(MarketCap)i,tLog(Assets)i,tDebt/Assetsi,tCash/Assetsi,tPP&E/Assetsi,tEBIT/Assetsi,tCapex/Assetsi,tR&D/Assetsi,tVolatilityi,tMomentum12i,tPanelF:CO2andOilExposureMeasuresLog(CarbonEmissions)i,tOilBetai,tTable1:SummaryStatistics.Thistablereportssummarystatisticsatthestock-monthlevel.Theclimatechangeexposuremeasuresarescaledupby106.Thevariablesinthetablearenotyetnormalized.Thesamplecoverstheperiodfrom01/2005to12/2020andincludesS&P500stocks.Electroniccopyavailableat:https://ssrn.coovertime,implyingthattheriskpremiumitselfalsovaries.Forexample,thequantityofriskAnotherviewholdsthattheriskpremiumforCCExposurere且ectsthetrendtowardESGreasons(Pastoretal.2021b,Pedersenetal.2021,orZerbib2020).Investorsmightthentoleratehigher(tail)riskswhenafectstockpricesandcouldleadtoariskpremiumforCCExposurethatiszerooreven.TheseviewsillustratethattheriskpremiumforCCExposureisconceptuallyambiguousandeventimevarying.Thus,anyestimatedpricingefectsofCthelong-termequilibrium,butratherthepathtowardit.3.2RiskPremiumforOverallClimateChangeExposure:EstimationWetestwhetherCCExposureisrelatedtoexcessreturnsicharacteristicsthatareknownreturnpredictorsorpossiblycorrelatedwithCCExposure.These24ThefactorsareMarket,Size(SMB),Value(HML),Momentum(WML),Pro?tability(RMW),andInvestment(CMA).Electroniccopyavailableat:https://ssrn.costockcharacteristicsinclude(i)?rmfundamentals:Log(MarketCap),Log(Assets),Debt/Assets,Cash/Assets,PP&E/Assets,EBIT/AssetsCapex/Assets,R&D/Assets;(ii)marketvariables:Momentum12,Volatility,and(iii)CO2andoilexposuremeasures:Log(CarbonEmissions)andOilBeta.Toensurethatthe?rmfundamentalsusepubliclyavailabledata,wyear-enddataarepubliclyavailable(FamaandFrench1992).OilBetaiscomputedjointly3.3RiskPremiumforClimateChangeExposure:BaselineEstimatesTable2reportsunconditionalriskpremiumestimatesforCCExposureaswellasforitsindus-try(CCExposureInd)andresidual(CCExposureRes)components.26Columns1and2reportestimatesfortherealizedexcessreturn(RET).InColumn1,theunconditionalestimateforRETdeliversapositivebutinsigni?cantriskpremiumforCCExposure.InColumn2,we?ndaninsigni?cantpremiumforCCExposureIndandapositivepremiumforCCExposureRespremiumsformostcColumns3and4considertheriskpremiumestimatesfortheMWpositiveandstatisticallysigni?cantriskpremiumsforCCExposure.InColumn3fortheMWproxy,stockswithhighervaluesofCCExposureareexpectedtodeliverhigherexcessreturns(t-statof2.88).InColumn5,themagnitudeoftheCCExposurepremiumalmost25SvLVZdocumentthatCCExposureandcarbonemissions,whilecorrelated,donotoverlapgreatly.26Followinga“ruleofthumb”fromGreene(2002)andBaumetal.(2007),weuseNeweyandWest(1987)standarderrorswiththreelags.Electroniccopyavailableat:https://ssrn.coExpectedExcessReturnRETi,tMWi,tGLBi,t(1)(2)(3)(4)(5)(6)Marketi,tSize(SMB)i,tValue(HML)i,tMomentum(WML)i,tProfitability(RMW)i,tInvestment(CMA)i,tCCExposurei,tCCExposure,dCCExposure,s(-0.998)(-0.986)(3.354)(3.386)(8.754)(8.683)(1.551)(1.503)(10.204)(10.048)(4.491)(4.452)(-0.674)(-0.725)(1.809)(1.804)(3.273)(3.265)(0.318)(0.432)(-3.048)(-3.024)(-2.325)(-2.296)(1.585)(1.558)(-4.654)(-4.716)(-1.883)(-1.957)(-0.730)(-0.756)(-2.026)(-2.048)(-2.156)(-2.119) (0.994) (2.882) (3.121) (-0.096) (1.216) (2.147) (1.897) (3.172) (3.463)ControlsYesYesYesYesYesYesSamplePeriodObs.R2Table2:RiskPremiumforClimateChangeExposure:UnconditionalEvidence.ThistablereportstheresultsofFama-MacBethregressionsatthestock-monthlevel.Wereporttheriskpremiumestimatesfor?rm-levelclimatechangeexposure(CCExposure).We