貨幣政策風險溢價外文翻譯中英文2019

貨幣政策風險溢價中英文2018原文Showmethemoney:ThemonetarypolicyriskpremiumAliOzdagli，MihailVelikovAbstractWecreateaparsimoniousmonetarypolicyexposure(MPE)indexbasedonobservablefirmcharacteristicsthatpreviousstudieslinktohowstocksreacttomonetarypolicy.Ourindexsuccessfullycapturesstocks'responsestobothconventionalandunconventionalmonetarypolicy.Stockswhosepricesreactmorepositivelytoexpansionarymonetarypolicy(high-MPEstocks)earnloweraveragereturns.Thisresultisconsistentwiththenotionthathigh-MPEstocksprovideahedgeagainstbadeconomicshocks,towhichtheFederalReserverespondswithexpansionarymonetarypolicy.Along-shorttradingstrategydesignedtoexploitthiseffectachievesanannualizedSharpeRatioof0.77.Keywords：Monetarypolicy，Assetpricing，RiskfactorsIntroductionAlargebodyofliteratureinmacroeconomicsandfinancestudiestheeffectsofmonetarypolicyonassetprices.Inarecentseminalcontribution,BernankeandKuttner(2005)showthatasurprise25-basis-pointcutinthefederalfundstargetrateisassociatedwithanincreaseofabout1%inbroadstockindexes.Overall,theacademicresearchandpractitionersagreethatmonetarypolicyaffectsstockpricessignificantlyandthatstockpricesoffirmswithdifferentcharacteristicsreactdifferentlytomonetarypolicy.1However,theeffectofmonetarypolicyonthecross-sectionofequityriskpremiumsisnotaswellunderstood.Whileseveralclassesoftheoreticalmodelsimplythatmonetarypolicyisanimportantsourceofriskinthestockmarket,theydifferwidelyintheirpredictionsregardingtherelationbetweenmonetarypolicyexposureandtheriskpremium.Inthispaper,wecreateamonetarypolicyexposure(MPE)indexbasedonobservablefirmcharacteristicsthatpreviousstudieslinktomonetarypolicysensitivityofstockprices.Usingthisindex,wefindthatstockswhosepricesreactmorepositivelytoexpansionarymonetarypolicy(high-MPEstocks)earnloweraveragereturnsthanlow-MPEstocks.Thispremiumiseconomicallysignificantandarobustfeatureofthedata.Along-short(low-minus-highMPE)tradingstrategydesignedtoexploitthiseffectachievesanannualizedvalue-weightedreturnof9.12%from1975to2015.OurresultsareconsistentwiththenotionthatstockswithhighmonetarypolicyexposureearnlowerreturnsbecausetheFederalReserverespondstobadeconomicshockswithexpansionarymonetarypolicyandhencehigh-MPEstocksprovideahedgeagainsttheseshocks.AnimportantchallengeincreatingtheMPEindexinvolvesidentifyingthestocks'reactiontoFederalReservepolicy.BernankeandKuttner(2005)notethatstockpricesareforward-lookingandshouldnotreacttoanticipatedpolicyratechanges.Therefore,weestimatearegressionofstockreturnsonunanticipated(surprise)policyratechanges,wherethepolicysurprisesarederivedfrominterestratefuturesonFederalOpenMarketCommittee(FOMC)meetingdatesasintheirpaper.AsBernankeandKuttner(2005)note,assetpricesmayalsorespondtorevisionsinexpectationsaboutfuturepolicyondateswithoutanFOMCmeeting,whichinturnmaybedrivenbynewsaboutchangingeconomicconditions.WefollowtheirapproachofusingunanticipatedpolicychangesonFOMCmeetingdatesbecause,intheirwords,itallowsusto“discernmoreclearlythestockmarketreactiontomonetarypolicy.”O(jiān)urregressionsusetheinteractionofthepolicysurpriseswithfirmcharacteristicsthatarelinkedtopolicysensitivitybythepreviousliterature(e.g.,Weber,Ozdagli,2018).Thismethodyieldsanindexbasedonthecontributionofeachcharacteristictothemonetarypolicyexposure.ThecharacteristicsunderlyingtheMPEindexcapturetheeffectsofvariousmonetarypolicytransmissionmechanisms,includingcreditchannel,balancesheetliquidity,discountrateeffect,andnominalrigidities.Accordingly,thefirmcharacteristicsincludemeasuresoffinancialconstraints,cashandshort-terminvestments,cashflowdurationandvolatility,andoperatingprofitability.Weshowthatourindexsuccessfullycapturesstocks'responsestomonetarypolicyunderdifferentpolicyregimes,includingpre-1994,1994-008,andpost-2008periods.ForadditionalevidenceofthestabilizerchannelandtheabilityofourMPEindextocapturethepolicyexposure,wenotethatthedualmandateoftheFederalReserve(stablepricesandsustainableemployment)requiresittostabilizetheeconomybytighteningpolicyinresponsetopositivesurprisesintheconsumerpriceindex(CPI)andemployment(Gurkaynaketal.,2005b).Thisleadstotwoimportanttestableimplications.First,thestabilizerchannelpredictsthatthelow-minus-highMPEportfolioshouldperformwellondayswithpositiveCPIandemploymentsurprisesbecausesuchsurprisesleadtoanexpectationoftightermonetarypolicy.Consistentwiththisprediction,wefindthatthereturntothelow-minus-highMPEportfolioincreasesinresponsetopositiveCPIandemploymentsurprisesderivedfromsurveyexpectationsasinGurkaynaketal.(2005b).Second,ifourMPEindexcapturespurelytheexposuretomonetarypolicy,theCPIandemploymentnewsshouldaffectthelow-minus-highMPEportfolioonlythroughtheireffectonmonetarypolicyexpectations.Consistentwiththisimplication,wefindthattheeffectofemploymentandCPIsurprisesonthelow-minus-highMPEportfolioallbutdisappearsoncewecontrolforchangesinpolicyexpectations.Finally,weconductabatteryofteststochecktherobustnessofthereturnpremiumonthelong-shortstrategy.Atradableversionofthelong-shortstrategythatusesonlyhistoricallyavailableinformationfortheconstructionoftheMPEindexgeneratesastatisticallysignificantaveragereturnof71basispointspermonthaftertransactioncosts.Inaddition,wedemonstratethatthepredictabilitywedocumentcannotbeexplainedbythepre-FOMCannouncementdriftdiscussedbyLuccaandMoench(2015)orthebetting-against-beta(BAB)effectdiscussedbyBlack(1972)andFrazziniandPedersen(2014).Moreover,thetradingstrategieswereportsurvivecontrolsfortheunderlyingcharacteristicsusedtoconstructtheMPEindexaswellasthe23anomalysignalsinNovy-MarxandVelikov(2016).Ourpaperisrelatedtoimportantcontributionsintheassetpricingliteraturethatuseindicesbasedonfirmcharacteristicstostudythecross-sectionofstockreturns.PastorandStambaugh(2003)usestock-levelcharacteristicstopredictfirms'exposuretoaggregateliquidityrisk,WhitedandWu(2006)createanindexoffinancialconstraints,Campbelletal.(2008)createafinancialdistressindex,andGuetal.(2018)createanindexofinvestmentirreversibilityandeachpaperstudiesthe? 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Tassetpricingimplicationsofitsrespectiveindex.Ourpaperbuildsabridgebetweentheliteraturethatconnectsfirmcharacteristicstotheirexpectedreturns,asinFamaandFrench(1993),andtheliteraturethatstudiesmacroeconomicaggregatesaspredictorsofassetreturns,asinLettauandLudvigson(2001),ParkerandJulliard(2005),Yogo(2006),andBalietal.(2017).Eventhoughthereisanextensivetheoreticalliteraturethatstudiestheimpactofmonetarypolicyonriskpremiums,theempiricalevidenceisscant.Creatingtheindexofmonetarypolicyexposureallowsustoresolvetheambiguityinthepredictionsoftheoreticalmodelsandshowthatmonetarypolicyexposureisastrongpredictorofreturnsinthecross-sectionofequities.Moreover,thepredictabilitywedocumentisrobusttothestricterthresholdsforstatisticalsignificancesuggestedbyHarveyetal.(2016)andNovy-Marx(2016).OurpaperalsocontributestotheburgeoningliteratureonFOMCcyclesandaggregatestockreturns(Lucca,Moench,2015,Cieslak,Morse,Vissing-Jorgensen,2018,Neuhierl,Weber)butinsteadfocusesonthecross-sectionofreturns.TheoreticalconsiderationsThesignofthemonetarypolicyriskpremiumStandardassetpricingtheorytellsusthattheriskpremiumofmonetarypolicyistheproductofthepriceofmonetarypolicyriskandtheexposuretomonetarypolicy.Inthissection,wesummarizetheimplicationsofdifferenttheoriesforthesetwocomponentsandshowthatthemonetarypolicyriskpremiumcanbepositiveornegativedependingontheunderlyingassumptions.Therefore,weconcludethatthesignandthesizeofthisriskpremiumisanempiricalquestionwhichwestudyinthefollowingsections.BansalandColeman(1996)andChanetal.(1996)aretwoearlyexamplesthatanalyzetheeffectofmonetarypolicyonequitypremiums.Bothofthesemodelsfeaturecash-in-advanceconstraintsfromtheseminalpaperofLucasandStokey(1987)inamodelwhereinvestors'utilitydependsontheconsumptionofcashandcreditgoods.TheinformationinthesepapersislatercrystallizedinBalduzzi(2007)whoshowsthatthepriceofmonetarypolicyrisk,andhencethesignofthepolicyriskpremium,dependsontheelasticityofsubstitutionbetweencashandcreditgoods.Ontheonehand,anincreaseinrealmoneysupplyshiftsconsumptionfromcreditgoodstocashgoodsandthereforeincreasesthemarginalutilityofconsumingcreditgoods,assumingthattheutilityisconcaveincreditgoods.Ontheotherhand,assumingcashandcreditgoodsaresubstitutes,theincreaseintheconsumptionofcashgoodsreducesthemarginalutilityofconsumingcreditgoods.Ifthefirst(second)effectdominates,thenrealmoneysupplycommandsanegative(positive)riskpremium.Morerecently,New-Keynesianmonetarymodelsthatincorporatenominalandrealrigiditieshavereceivedincreasingattentionintheliteraturestudyingtheriskofequities,e.g.,LiandPalomino(2014)andWeber(2015).Inthesemodels,anexpansionarypolicysurpriseincreasesconsumptiongrowth,consistentwiththetime-seriesevidencefrom,forexample,Christianoetal.(2005)andSmetsandWouters(2007).Theincreaseinconsumptiondecreasesthemarginalutilityofconsumption.Thismechanismgeneratesapositiverelationbetweenmonetarycontractionsandthemarginalvalueofwealth,leadingtoapositiveriskpriceofmonetarypolicy.Therefore,stocksthatreactmorepositivelytoanexpansionarypolicysurpriseshouldcommandahigherriskpremium.Anotherrecentstrandofliteraturestudiestheassetpricingimplicationsofmacroeconomicmodelswithfinancialfrictions,suchasthoseinBernankeandBlinder(1988).Thecentralthemeofthisliteratureisthatthemarginalinvestorislikelyafinancialintermediary,sothestochasticdiscountfactorshoulddependonthehealthofthefinancialsector,orfundingliquidity,whichinturndeterminesthemarginalvalueofwealth.Thus,assetsthatpayoffintimesofhighmarginalvalueofwealth,i.e.,timeswithlowfundingliquidity,shouldbelessrisky.5Empirically,Adrianetal.(2014)andHeetal.(2017)findthatfundingliquidityofintermediariesexplainsthereturnsonawiderangeofassetclasses.Drechsleretal.(2018)provideadynamicassetpricingmodellinkingequityriskpremiumstomonetarypolicythroughthisfundingliquiditychannel.Intheirmodel,loweringthenominalinterestratereducesthecostofleverageforfinancialintermediariesandeffectivelyreducestheirexternalfinancepremium,therebyincreasingrisktakingand,inturn,decreasingriskpremiums.BoththeNew-Keynesianmodelsandthefundingliquiditymodelsoperateundertheviewthatmonetarypolicyisa“driver”ofbusinesscycles.Thatis,monetarypolicyimpactsthemarginalvalueofwealthbyaffectingrealvariables,whichinturntransformsitintoasourceofpricedrisk.Alternatively,monetarypolicycanbeviewedasa“stabilizer”ofbusinesscycles,consistentwiththeroleoftheFederalReserveintheeconomy.Inparticular,monetarypolicyismorelikelytobeexpansionary(contractionary)followingnegative(positive)macroeconomicnews(Gurkaynaketal.,2005b).Sincenegativeeconomicshocksincreasethemarginalvalueofwealth,assetsthataremorelikelytopayoffafteranexpansionarymonetarypolicyarepreciselythosethatprovideinvestorswithadditionalfundsintimesofneedandthereforehavelowerexpectedreturns.6InAppendixA.2,weoutlineasimplemathematicalmodelthatillustratestheassetpricingimplicationsofthedriverandstabilizereffectsofmonetarypolicy.Weshowthatthemonetarypolicyriskpremiumcanbepositiveornegativedependingonwhicheffectdominates.TransmissionchannelsofmonetarypolicyThemainempiricalchallengeinourpaperistheidentificationofthecross-sectionaldifferencesinmonetarypolicyexposureofindividualfirms.Whatisthebestwaytoestimatetheexposure?Adirectapproachwouldbesimplyregressingthereturnsofeachstockseparatelyonmonetarypolicysurprises.However,themajorityofstockshavehighreturnvolatilityorlackalongenoughreturnhistory,whichleadstonoisyexposureestimates(Cochrane,2005,p.436).Instead,wefollowthefootstepsofearlierimportantcontributionstoassetpricingliteraturethatuseindicesbasedonfirmcharacteristicstostudythecross-sectionofstockreturns(e.g.,Campbell,Hilscher,Szilagyi,2008,Gu,Hackbarth,Johnson,2018).Thetraditionofcreatingindicesisalsopopularincorporatefinance(Altman,1968,Kaplan,Zingales,1997,D'Acunto,Weber,Yang).Financialconstraints(Creditchannel):Theeffectoffirms'financialconstraintsonmonetarypolicytransmissionhasbeenattheheartofpolicyandacademicdiscussions(Gertler,Gilchrist,1994,Fisher,1933).Whilethereisanextensiveliteraturefocusingontheimplicationsofthiscreditchannelforrealvariables,theliteraturestudyingitsimplicationsforstockpricesisrelativelyscarce.Perez-QuirosandTimmermann(2000)usesmallerfirmsizeasafinancialconstraintmeasureandfindthatstockpricesofsmallerfirmsaremoreresponsivetomonetarypolicychanges,measuredbymoneysupply.Lamontetal.(2001)recognizethatmonetarypolicyisimplementedbythechoiceofpolicyrates,ratherthanmoneysupply,butdonotfindanysignificantrelationbetweenfinancialconstraintsandpolicysensitivityofstockpriceswhentheyusethechangeinpolicyrate.Ozdagli(2018)usestheunexpectedcomponentofthepolicyratechangeasinBernankeandKuttner(2005)becausestocksshouldnotreacttoexpectedchangesinmonetarypolicy.Usingbothfinancialconstraintindicesandanaturalexperiment,hefindsthatmoreconstrainedfirmscanbelessresponsivetomonetarypolicybecausethesefirmsrelylessonexternalfinance,andhencearelessaffectedbythechangesinthecostofexternalfinance.FollowingOzdagli(2018),weusethefinancialconstraintindexcreatedbyWhitedandWu(2006)asourfinancialconstraintsproxy.Cashandshort-terminvestments(Liquidityeffect):Thesearethemostliquidassetsofthefirmandaredirectlyrelatedtothemonetarybase,broadlydefined.Ontheonehand,firmswithahigheramountofcashcanreactmorenegativelytoapolicyrateincreasebecausetheinterestrateistheopportunitycostofholdingcash(Baumol,1952);ontheotherhand,corporatecashreservescandampentheeffectofmonetarypolicybymakinginvestmentlesssensitivetopolicy(Gaoetal.,2018).Similarly,iffirmsdeposittheircashinashort-termsavingsoranotherinterest-bearingaccount,anincreaseintheinterestratecanactuallyhelpthemobtainadditionalliquidfunds,whichwouldalsodampentheeffectofmonetarypolicy.Cashflowduration(Discountrateeffect):Macaulay(1938)durationhasbeenwidelyemployedbyfixed-incomeanalystsduetoitsclearrelationtotheinterestratesensitivityofbondpricesthroughthediscountrateeffect.Morerecently,theconceptofdurationisstudiedbyDechowetal.(2004)andWeber(2018)inthecontextofequitymarketsandtheconnectionofequitydurationtointerestratesensitivityofstocksisrecognizedbyinvestors(e.g.,DeutscheBank,2010).Ozdagli(2018)findsthatstocksoffirmsthatexpecttohavecashflowsfartherinthefuture,andthereforehavegreaterequityduration,aremoreaffectedbymonetarypolicy,consistentwiththenotionthatthepresentvalueoflatercashflowsaremoreaffectedbythechangesindiscountrate.Cashflowvolatility:Cashflowvolatilitymaycapturethemonetarypolicysensitivityofafirm'sstockpriceinmultipleways,asexplainedinOzdagli(2018).Forexample,volatilitycanberelatedtocashflowdurationandcancaptureaspectsthereofnotperfectlycapturedbystandardcashflowdurationmeasures.Ontheonehand,firmswithlowervolatilitymayhavelowerdefaultlikelihoodandthereforelongerlivesandhigherdurationofcashflows.Ontheotherhand,alowervolatilitymayalsoimplyalowervalueoftheoptiontodelayinvestmentandthereforefirmswithlowervolatilitymayincreasecashflowdurationbyincreasinginvestmenttodayinexchangeforcashflowsinthefuture.Asanotherexamplefortheimportanceofvolatility,highercashflowvolatilitymayimplythatthefirmneedstorelyonexternalfinancingmoreoften,whichincreasestheimportanceofthecostofexternalfinancingwhichinturnisdirectlyaffectedbymonetarypolicy.Operatingprofitability(Nominalrigidities):NominalrigiditiesintheformofstickypricesandwagesareanimportantingredientinNew-Keynesianmacroeconomicmodels.7Whilefirm-leveldataonnominalrigiditiesarenotavailablefortheuniverseofstocks,operatingprofitabilitycanstillprovideawindowintotheeffectsofnominalrigidities.Inparticular,ifinputprices,e.g.,wages,aresticky,anexpansionarymonetarypolicywillhavealargeeffectonthefirms'revenueswithoutchangingthetotalcostofinputsasmuch,drivingstockpricesup.Theresultingpercentageincreaseinstockpricewillbestrongerforfirmswhoserevenuesareclosertotheirinputcosts,i.e.,thosethathavelowprofitability,becauseoftheoperatingleverageeffectcreatedbyrelativelyfixedinputcosts.Morerecently,Gomesetal.(2016)provideamechanismwhereexpansionarymonetarypolicyreducestherealdebtburdenoffirmsduetotheirnominalobligationstolenders.This“stickyleverage”mechanismworksinawaysimilartothestickywagechanneldescribedaboveinthatstickywagesreducetherealburdenofnominalobligationstoemployeesofafirmafteranexpansionarypolicy.Therefore,weexpectstickyleveragetoincreasethepolicysensitivityofstockpricesoflessprofitablefirms,aneffectalsodiscussedinOzdagliandWeber(2017).Followingananalogousintuition,iffirms'outputpricesaremorestickythantheirinputprices,anexpansionarymonetarypolicywillleadtoagreaterincreaseininputcoststhanthefirms'revenues,eatingawaytheirprofits,andthusreducingtheirstockprices.However,thisreductionwouldbesmallerinpercentagetermsforfirmswithhigherprofitability.AssetpricingimplicationsofmonetarypolicyexposureInthissectionweanalyzethestockreturnsofdifferentportfolioscreatedbysortingstocksbasedonourMPEindex.WefirstshowthatportfoliosoffirmswithhigherMPEearn,onaverage,lowerreturnsthanportfoliosoffirmswithlowerMPE,evenaftercontrollingforotherwell-knownassetpricingfactors.ThisresultsuggeststhatthestabilizerchanneldiscussedinSection2.1isthemaindrivingforcebehindtheriskinessofdifferentMPEportfolios.WeprovidefurtherevidenceonthestabilizerchannelandthatourMPEindexcapturespurelymonetarypolicyexposure,bystudyinghowMPEportfoliosrespondtothemacroeconomicnewsthatislikelytotriggerachangeinmonetarypolicy.Moreover,wereportthatanimplementableversionofourMPEtradingstrategy,basedonlyonhistoricallyavailableinformation,generatessignificantaveragereturnsevenafteraccountingfortransactioncostsandstandardassetpricingfactors.Finally,wecompareourapproachwithanalternativeapproachwherewecalculatethepolicysensitivityofeachstockbyregressingeachstock'sreturnsseparatelyonmonetarypolicysurpriseswithoutinteractingthesesurpriseswithanyfirm-levelcharacteristic.Wefindthat,whileatradingstrategybasedonthisalternativeapproachalsogeneratespositivereturns,itisdominatedbyourMPE-index-basedstrategy.Additionalevidenceonthestabilizerchannel:theresponseoftheMPE-sortedportfoliotoinflationandemploymentnewsTheFederalReserveActestablishesstablepricesandmaximumsustainableemploymentasthedualmandateoftheFederalReserveandtheFederalReservepaysparticularattentiontonewsabouttheconsumerpriceindex(CPI)andemployment.Thisleadstotwoimportanttestableimplicationsforourlow-minus-highMPEportfolio.First,thelong/short(low-minus-highMPE)portfolioshouldreactmorepositivelytonewsaboutemploymentandconsumerpriceindexthatleadstoanexpectationoftightermonetarypolicy.Accordingtothestabilizerchannel,positiveCPIandemploymentsurprisesleadtoanexpectationofatightermonetarypolicyastheFederalReservetriestostabilizetheeconomy(Gurkaynaketal.,2005b).Therefore,thelow-minus-highMPEportfolioshouldincreaseinresponsetopositiveCPIandemploymentsurprises.Second,iftheMPEindexcapturespurelythemonetarypolicyexposure,theresponseofthelow-minus-highMPEportfoliotoemploymentandCPInewsshouldlargelydisappearoncewecontrolfortheexpectedchangesinfuturepolicyratesduetothenewsbecausetheresponseofthelow-minus-highMPEportfoliotothisnewsstemsfromitsexposuretomonetarypolicy.Inordertotestthesetwohypotheses,wecreateadailyseriesofemploymentandpriceindexsurprises,followingGurkaynaketal.(2005b).Foremployment,weusenon-farmpayrollstatisticsannouncedmonthly.10ForthepriceindexweusethecoreCPInumbersthattheBureauofLaborStatistics(BLS)announcesinthemiddleofeverymonth.TheCPIandnon-farmpayrollsurpriseseriesarecomputedasthereleasedvaluesminusthemarketexpectation,wherethemarketexpectationismeasuredusingthemedianmarketforecastaspublishedbyMoneyMarketServices(nowknownasInformaGlobalMarkets)theFridaybeforeeachrelease.FollowingGurkaynaketal.(2005b),wereplacemissingobservationsforthesurpriseswithzeros.Forthechangesinpolicyexpectations,weusethechangesintheone-quarter-aheadEurodollarfutures(ED1)rate.Weusethismeasureinsteadofthecurrent-monthfederalfundsfuturesbecausemanymonthsdonotincludeanFOMCmeetingfollowingthedateofanemploymentorCPIannouncement.BecausethepolicyratewouldnotadjustaftertheemploymentorCPIannouncementsinthosemonths,thepriceofthecurrent-monthFedFundsfutureswouldnotmoveandhencenotcapturethechangeinnear-termexpectationsaboutmonetarypolicyduetoemploymentorCPIannouncements.Therefore,wecapturethechangesinnear-termexpectationsusingED1,whichalsoallowsustostudyboththeconventionalandunconventional(zero-lower-bound)monetarypolicyperiodsasdiscussedinSection3.3.ED1hastheadditionaladvantageofbeingpotentiallymoreliquidthanfederalfundsfuturesoutsidetheFOMCdatesduetoitsgreatervolume.Thechangesinpolicyexpectationsequalthenegativeofthedailychangeintheone-quarter-aheadEurodollarfuturesratesothatapositivevalueisexpansionary,inaccordancewithSection3.OurdataperiodstartsinApril1986duetotheavailabilityoftheEurodollarfuturestradingdata.BecauseweareinterestedinchangesinpolicyexpectationsduetochangesinemploymentandpriceindexnewsweomitthedatesoftheFOMCannouncements.Table4reportstheestimatesfromregressingthedailyportfolioreturnsofthelong/short(low-minus-highMPE)portfolioonchangesinpolicyexpectationsandtheemploymentandpriceindexsurprises.Column1showsthatthechangesinpolicyexpectationsonnon-FOMCdatesmovethelong/shortportfoliosinthesamedirectionasthepolicysurprisesonFOMCdatesinSection3.Inparticular,aonestandarddeviationexpansionarysurprisechangeinthepolicyexpectationleadstoastatisticallysignificant9basispointsdecreaseinthelong/shortportfolio.Thisresultisconsistentwithourintuition.TheMPEstrategyislong(short)stocksthatperformpoorly(well)whenthereisanexpansionarypolicysurprise.Thus,anexpansionarychangeinpolicyexpectationsleadstolowerreturnstothelong/shortstrategy.Finally,ifourMPEindexpurelycapturesthemonetarypolicyexposure,changesinexpectedfuturepolicyratesshouldlargelyabsorbtheeffectofemploymentandCPInewsbecausetheresponseofthelong/shortportfoliotothisnewsstemsfromtheportfolio'sexposuretomonetarypolicy.Columns4,5,and6provideevidenceforthispredictionbyusingthechangesinpolicyexpectationsandnewsaboutCPIandemploymentsimultaneously.Aswecanobserve,controllingforthechangeinpolicyexpectationsresultsininsignificantloadingsontheemploymentandCPIsurpriseswhereastheloadingonthechangesinpolicyexpectationsremainsverysimilartotheoneinColumn1.Asweseeinthefifthrow,thedropinthecoefficientsofinflationandemploymentsurprisesisstatisticallysignificantaswell.Thisresultsuggeststhatthelong/shortMPEportfolioreactstoinflationandemploymentnewsmainlybecausethenewsmovestheinvestors'expectationsaboutfuturemonetarypolicy.Therefore,weconcludethatourMPEindextrulycapturestheexposuretomonetarypolicyratherthanadirectexposuretothenews.譯文把錢拿出來：貨幣政策風險溢價摘要我們根據(jù)樣本公司的特征創(chuàng)建了簡約的貨幣政策敞口（MPE）指數(shù)，以前的研究將其與股票對貨幣政策的反應(yīng)相關(guān)聯(lián)。我們的指數(shù)成功地記錄了股票對常規(guī)和非常規(guī)貨幣政策的反應(yīng)。價格對擴張性貨幣政策反應(yīng)更為積極的股票（高MPE股票）的平均回報率較低。這一結(jié)果與以下觀點相一致：高MPE的股票可以對沖不利的經(jīng)濟沖擊，美聯(lián)儲對此采取了擴張性的貨幣政策。利用這種效應(yīng)設(shè)計的多空交易策略可實現(xiàn)0.77的年夏普比率。關(guān)鍵詞：貨幣政策；資產(chǎn)定價；風險因素引言宏觀經(jīng)濟學和金融學中的大量文獻研究了貨幣政策對資產(chǎn)價格的影響。Bernanke和Kuttner（2005）在最近的一項開創(chuàng)性貢獻中指出，聯(lián)邦基金目標利率意外下調(diào)25個基點與廣泛股指上漲約1％有關(guān)?？傮w而言，學術(shù)研究和從業(yè)人員都認為貨幣政策對股票價格的影響很大，而且具有不同特征的公司的股票價格對貨幣政策的反應(yīng)也不同。但是，貨幣政策對股票風險溢價橫截面的影響并不大。完全了解。盡管幾類理論模型暗示貨幣政策是股票市場中重要的風險來源，但它們在貨幣政策敞口和風險溢價之間的關(guān)系預測上卻大相徑庭。在本文中，我們基于可觀察的公司特征創(chuàng)建了貨幣政策敞口（MPE）指數(shù)，以前的研究將其與股票價格的貨幣政策敏感性相關(guān)聯(lián)。使用該指數(shù)，我們發(fā)現(xiàn)，價格對擴張性貨幣政策反應(yīng)更為積極的股票（高MPE股票）的平均收益要低于低MPE股票。此溢價在經(jīng)濟上具有重要意義，并且是數(shù)據(jù)的強大功能。旨在利用這種效應(yīng)的多空（低負高MPE）交易策略在1975年至2015年期間實現(xiàn)了9.12%的年化價值加權(quán)收益。我們的結(jié)果與以下觀點一致：貨幣政策敞口較高的股票收益較低之所以會獲得回報，是因為美聯(lián)儲（Fed）通過擴張性的貨幣政策來應(yīng)對惡劣的經(jīng)濟沖擊，因此高MPE股票可以對沖這些沖擊。建立MPE指數(shù)