培訓(xùn)項(xiàng)目參考

何職稱：金程教育資深何職稱：金程教育資深培訓(xùn)師、通過(guò)CFA三級(jí)、通過(guò)FRM專(zhuān)業(yè)能力：講課幽默風(fēng)趣，最擅長(zhǎng)的是將復(fù)雜問(wèn)題簡(jiǎn)單化，通過(guò)舉大量實(shí)例幫助學(xué)員理解復(fù)雜問(wèn)題。金融理論知識(shí)扎實(shí)，在金融教學(xué)中有自己獨(dú)到的方法。多年對(duì)A、M、RP等考試體系的研究使她全面掌握考100%ContributionBreedsTopicinCFALevel100%ContributionBreedsSSETHICS&PROFESSIONALSSBEHAVIORALSSPRIVATEWEALTHTopicinCFALevel100%ContributionBreedsSSETHICS&PROFESSIONALSSBEHAVIORALSSPRIVATEWEALTHSSPORTFOLIOMANAGEMENTFORINSTITUTIONALSSCAPITALMARKETEXPECTATIONSINPORTFOLIOSSECONOMICCONCEPTSFORASSETVALUATIONINPORTFOLIOSSASSETSSMANAGEMENTOFPASSIVEANDACTIVEFIXED‐INCOMESSPORTFOLIOMANAGEMENTOFGLOBALBONDSANDSSEQUITYPORTFOLIOSSALTERNATIVEINVESTMENTSFORPORTFOLIOSSRISKSSRISKMANAGEMENTAPPLICATIONSOFSSEXECUTIONOFPORTFOLIODECISIONS;MONITORINGANDSSPERFORMANCEEVALUATIONANDSSGLOBALINVESTMENTPERFORMANCEORGANIZINGTHETASK:FRAMEWORKANDORGANIZINGTHETASK:FRAMEWORKANDAFrameworkforDevelopingCapitalMarketChallengesinTOOLSFORFORMULATINGCAPITALMARKETFormalSurveyandPanelBusinessCycleEconomicGrowthInternationalEconomicUsingEconomicInformationinForecastingAssetClass100%ContributionBreedsWhat’sInvestors’expectationconcerningtheriskWhat’sInvestors’expectationconcerningtheriskandreturnofassetWhyweneedInputtoformulatingastrategicasset100%ContributionBreedsCapitalmarketCapitalmarketexpectationscanCapitalmarketCapitalmarketexpectationscanbereferredtomacroexpectations(expectationsregardingclassesofassets)microexpectations(expectationsregardingindividualFormulatingcapitalmarketexpectationsisreferredtoasresearchbecauseitisrelatedtosystematicAlpharesearch,ontheotherhand,isconcernedwithearningexcessreturnsthroughtheuseofspecificstrategieswithinspecificassetgroups.100%ContributionBreedsFormulatecapitalmarketTheanalystshouldFormulatecapitalmarketTheanalystshoulduseaseven‐stepDeterminethecapitalmarketexpectationsthatareneededtheinvestor’sInvestigateassets’historicalperformanceandtheirdeterminants;Identifythevaluationmodelusedanditsrequirements;CollectthebestdataUseexperienceandjudgmenttointerpretcurrentinvestmentFormulatecapitalmarketexpectations;Monitoractualperformanceanduseittorefinethe100%ContributionBreedsChallengesinHigh‐qualityforecastsareconsistent,ChallengesinHigh‐qualityforecastsareconsistent,unbiased,objective,wellandhaveaminimumamountofforecast9problemsencounteredinproducingLimitationstousingeconomicTimeChangeindefinitionorcalculationRe‐based(notsubstantivechange,moreofamathematical100%ContributionBreedsChallengesin9problemsencounteredinChallengesin9problemsencounteredinproducingDatameasurementerrorsandtranscriptionerrors:Theseareerrorsingatheringanddata.Sucherrorsaremostseriousiftheyreflectasurvivorshipbias:ariseswhenadataseriesreflectsonlyentitiesthathavesurvivedtotheendoftheperiod.Withoutcorrection,statisticsderivedfromseriessubjecttosurvivorshipbiascanbemisleadingintheforward‐lookingcontextofexpectationssetting.(Returnisoverestimated)appraisal[smoothed]data:forcertainassetswithoutliquidpublicmarkets,appraisaldataareusedinlieuofmarketpricetransactiondata.Appraisedvaluestendtobelessvolatilethanmarket‐determinedvaluesfortheidenticalassetwouldbe.(Riskis100%ContributionBreedsChallengesin9problemsencounteredinproducingLimitationChallengesin9problemsencounteredinproducingLimitationofhistoricalNonstationarity:meaning,informally,thatdifferentpartsofaseriesreflectdifferentunderlyingstatisticalTheriskthatthedatacovermultipleregimesTimeseriesoftherequiredlengthmaynotbeInordertogetdataseriesoftherequiredlength,temptationistousehigh‐frequencydata(weeklyorevendaily).Dataofhighfrequencyaremoresensitivetoasynchronismacrossvariables.Asaresult,high‐frequencydatatendtoproducelowercorrelationestimates.ExPostriskasabiasedriskmeasureofExAnteLookingbackward,wearelikelytounderestimateexanteriskoverestimateexanteaniticipatedOnlytheexanteriskpremiumisimportantindecision100%ContributionBreedsChallengesin9problemsencounteredinproducingChallengesin9problemsencounteredinproducingBiasesinanalyst’sData‐miningbiasisintroducedbyrepeatedly“drilling”oradatasetuntiltheanalystfindssomestatisticallysignificanttime‐periodbiasrelatestoresultsthataretimeperiodspecific.Researchfindingsareoftenfoundtobesensitivetotheselectionofstartingand/orendingdates.Howtoavoid:checkforeconomicrationalesbetweenthevariables;splitinto2subperiods.Useout‐of‐sampleFailuretoaccountforconditioninginformation:therelationshipsecurityreturnsandeconomicvariablesisnotconstantoverMisinterpretationof100%ContributionBreedsChallengesin9problemsencounteredinproducingChallengesin9problemsencounteredinproducing6Psychologicaltheanchoringthetendencyofthemindtogivedisproportionateweighttothefirstinformationitreceivesonatopic.Initialimpressions,estimates,ordataanchorsubsequentthoughtsandjudgments. thestatusquothetendencyforforecaststoperpetuaterecent—thatis,topredictnochangefromtherecentIfinflationhasbeenrisingatadouble‐digitrateforseveralrecentperiods,itisanaturaltendencytoforecastasimilarincreaseinthenextperiod.Maybeovercomewithrationalanalysisusedwithinamaking100%ContributionBreedsChallengesin9problemsencounteredinChallengesin9problemsencounteredinproducing6Psychological theconfirmingevidencethebiasthatleadsindividualstogivegreaterweightinformationthatsupportsanexistingorpreferredpointofviewthantoevidencethatcontradictsit.Thetendencytoseekoutinformationthatsupportsanexistingpointofviewalsoreflectsthisbias.ExamineallevidenceswithequalInvolveindependent‐mindedHonestto100%ContributionBreedsChallengesin9problemsencounteredinproducingChallengesin9problemsencounteredinproducing6Psychological theoverconfidencethetendencyofindividualstooverestimatetheaccuracytheirforecasts.wouldbereflectedinadmittingtoonarrowarangeofpossibilitiesorscenariosinforecasting.Agoodpracticetopreventthistrapfromunderminingtheforecastingendeavoristowidentherangeofpossibilitiesaroundtheprimarytargetforecast. theprudencethetendencytotemperforecastssothattheydonotextreme,orthetendencytobeoverlycautiousinAvoidance;widentherangeofInaddition,themostsensitiveestimatesaffectingaforecastshouldbecarefullyreviewedinlightofthesupporting100%ContributionBreedsChallengesin9problemsencounteredChallengesin9problemsencounteredinproducing6Psychological therecallabilitythetendencyofforecaststobeoverlyinfluencedbythathaveleftastrongimpressiononaperson’smemory.Often,forecastsareoverlyinfluencedbythememoryofcatastrophicordramaticpastevents.Tominimizethedistortionsoftherecallabilitytrap,analystsshouldgroundtheirconclusionsonobjectivedataandproceduresratherthanonpersonalemotionsandmemories.100%ContributionBreedsChallengesin9problemsencounteredChallengesin9problemsencounteredinproducingModelandinputmodeluncertainty:uncertaintyconcerningwhetheramodelisinputuncertainty:uncertaintyconcerningwhethertheinputsare100%ContributionBreedsORGANIZINGTHETASK:FRAMEWORKANDORGANIZINGTHETASK:FRAMEWORKANDAFrameworkforDevelopingCapitalMarketChallengesinTOOLSFORFORMULATINGCAPITALMARKETFormalSurveyandPanelBusinessCycleEconomicGrowthInternationalEconomicUsingEconomicInformationinForecastingAssetClass100%ContributionBreedsForecastingThetoolsforformulatingcapitalmarketForecastingThetoolsforformulatingcapitalmarketformalstatisticaldiscountedcashflowmodels,theriskpremiumapproach,financialmarketequilibriumSurveyandpanelAnalyst100%ContributionBreedsFormalTools-StatisticalStatistical1.ProjectinghistoricaldataFormalTools-StatisticalStatistical1.Projectinghistoricaldata:historicalmeanreturn,standarddeviation,andcorrelationsforadatasetintothefuture.ThearithmeticmeanisthebestwhenprojectingforaThegeometricmeanisbestforprojectingoverseveralThegeometricmeanisalwayssmallerthanthemeanwhenthevarianceofreturnsisThedifferencebetweenthetwomeasuresincreasesasthevarianceofreturnsincreases100%ContributionBreedsFormalTools‐Statistical2.FormalTools‐Statistical2.Shrinkageestimators:weightedaveragesofhistoricaldatasomeotherestimate,wheretheweightsandotherestimatesaredefinedbytheanalyst.Shrinkageestimatorsreduce(shrink)theinfluenceofhistoricaloutliersthroughtheweightingprocess.Themeanreturnandcovariancearetheparametersmostoftenadjustedwithshrinkageestimators.Thistoolismostusefulwhenthedatasetissosmallthathistoricalvaluesarenotreliableestimatesoffutureparameters.100%ContributionBreedsFormalTools-Statistical3.Time‐SeriesTime‐SeriesEstimatorsinvolveFormalTools-Statistical3.Time‐SeriesTime‐SeriesEstimatorsinvolveforecastingavariableonthebasisoflaggedvaluesofthevariablebeingforecastandoftenlaggedvaluesofotherselectedvariables. (1)22ttt0Volatilityclusteringisthetendencyforlarge(small)swingsinpricestofollowedbylarge(small)swingsofrandomdirection.Volatilitycapturestheideathatsomemarketsrepresentperiodsofnotablyhighorlowvolatility100%ContributionBreedsFormalTools-Statistical4.MultifactorRitwo‐factormultifactorFormalTools-Statistical4.MultifactorRitwo‐factormultifactor)2i 2 Cov(F Cov(i,j)22)Cov(FF Byrelatingthereturnsonallassetstoacommonsetofreturndrivers,multifactormodelsimplifiesthetaskofestimating100%ContributionBreedsFormalTools‐StatisticalFormalTools‐Statistical100%ContributionBreedsFormaltools-DCFDiscountedcashflowcorrectFormaltools-DCFDiscountedcashflowcorrectemphasisonthefuturecashflowsofanassetandtheabilitytobackoutarequiredreturndonotaccountforcurrentmarkerconditionssuchsupplyanddemandsothesemodelsareviewedasbeingmoresuitableforLTvaluationEarninggrowthrate(g)=GDPgrowthrate+excesscorporategrowth(fortheindexcompanies)ThegrowthrateisproxiedbythenominalgrowthinGDP=thesumoftherealgrowthrateinGDP+therateofinflation.Moreadvancedanalysis:Thegrowthratecanbeadjustedforanydifferencesbetweentheeconomy’sgrowthrateandthatoftheequityindex.thisadjustmentisreferredtoastheexcesscorporategrowthrate.100%ContributionBreeds P0 Ri P1Rg Formaltools-DCFGrinoldandKronerstepfurtherbyincludingaFormaltools-DCFGrinoldandKronerstepfurtherbyincludingavariablethatforstockrepurchasesandchangesinmarketvaluationsasrepresentedbyP/EratioPRiSig1E=theexpectedrateofreturnonDiv1/P0=theexpecteddividend△S=percentagechangeinsharesoutstanding(positiveornegative)i=expectedinflationrate△P/EtheperperiodpercentchangeintheP/ETheterm△Sisnegativeinthecaseofnetpositivesharerepurchasesisapositiverepurchaseyieldinsuchcases.100%ContributionBreedsFormaltools-DCFGrinoldFormaltools-DCFGrinoldandEquationconsistsofthreeExpectedincomereturn:D/P-If?Sisnegative(shareshavebeenrepurchased),stockholdersareassumedtoreceivecash;thus,thepercentagechangeinthenumberofsharesoutstandingisaddedIf?Sispositive,however,stockholdersareassumedtopaycash.thepercentagechangeinthenumberofsharesoutstandingissubtractedExpectednominalearningsgrowthreturn:i+Expectedrepricingreturn:Theexpectednominalearningsgrowthreturnandtheexpectedrepricingreturnconstitutetheexpectedcapital100%ContributionBreedsExample2007AclientofShopondExample2007AclientofShopondisconsideringadjustingherallocationtotheU.S.marketandhasaskedSteinertoestimatethenominalexpectedreturnforthatmarket.SteinerdecidestousetheGrinold‐KronermodelinsteadoftheGordonGrowthmodeltoforecasttheexpectedreturnonU.S.equities.ToimplementtheGrinold‐Kronermodel,SteinergathersthedatashownExhibit2007Economic100%ContributionBreedsU.S.Example2007B.SupportSteiner’sdecisiontousetheGrinold‐KronermodelwithtwoExample2007B.SupportSteiner’sdecisiontousetheGrinold‐Kronermodelwithtwobasedontheinformationprovided.(4C.CalculatetheexpectedreturnonU.S.equities.usingtheGrniold‐Kronermodel.basedonthedatainExhibit1andExhibit2.Showyourcalculations.(3minutes)100%ContributionBreedsU.S.equitiesintegrationDividendReallong‐termgrowthSharerepurchasePerperiod%changeinP/EilliquidityGlobalSharperatioforglobalinvestmentmarketCorrelationcoefficientGIM,U.S.Example2007PartTheGrinold–KronerExample2007PartTheGrinold–Kroner(GK)modelisanextensionofthegrowthmodelthattakesexplicitaccountofsharerepurchases.ThemodelalsoprovidesameansforanalyststoincorporateexpectationsofvaluationlevelsthroughtheP/Eratio.BasedontheinformationprovidedinExhibit2,Steiner’sdecisiontousetheGKmodelisbasedon:TheU.S.Dataincludesasharerepurchaseyieldof1%.TheGKmodeltakesexplicitaccountofsharerepurchasesandisthereforeanappropriatemodelforSteiner’sanalysis.Exhibit2showsaperperiodchangeinP/Eof0.25%.TheGKmodelallowschangingP/EratiostobeincorporatedandisthereforeappropriateforSteiner’sanalysis.100%ContributionBreedsExample2007PartTheExample2007PartThereturntoU.S.equitiesusingtheGrinold–Kronermodelcalculatedas100%ContributionBreedsFormaltools-RiskpremiumRiskpremiumGeneralFormaltools-RiskpremiumRiskpremiumGeneralE(Ri)=Rf+RP1+RP2+…..+FixedincomeE(R)=realriskfreeinterestrate+inflationpremium+defaultpremium+illiquiditypremium+maturitypremium+taxEquityriskE(R)=YTMonalong‐termgovernmentbond+equityriskFormaltools-FinancialMarketEquilibriumFormaltools-FinancialMarketEquilibriumFinancialMarketEquilibriumgivestheexpectedreturnonanyassetasthesumthe(domestic)risk‐freeariskpremiumbasedontheasset’ssensitivitytotheworldmarketportfolioexpectedreturnontheworldmarketportfolioinexcessofrisk‐free100%ContributionBreedsFormaltools-FinancialMarketEquilibriumE(Ri)=RF+βi[E(RM)–E(Ri)==theFormaltools-FinancialMarketEquilibriumE(Ri)=RF+βi[E(RM)–E(Ri)==theexpectedreturnonassetigivenitsRF=therisk‐freerateofE(RM)=theexpectedreturnontheworldmarketβi=theasset’ssensitivitytoreturnsontheworldmarketportfolio,toCov(Ri,i,Mi assetclassriskpremium,RPiequaltoE(Ri)‐RF,isasimplefunctionofworldmarketriskpremium,,RPM,equaltoE(RM)–RP ((RP))iiM imM100%ContributionBreedsFormaltools‐FinancialMarketEquilibriumFormaltools‐FinancialMarketEquilibriumTheSingerandTerhaaranalysisadjuststheICAPMforimperfections,suchasilliquidityandmarketThemoreilliquidanassetis,thegreatertheliquidityriskpremiumshouldbe.Toestimatethesizeoftheliquidityriskpremium,onecouldestimatethemulti‐periodSharperatio(MPSR)fortheinvestmentoverthetimeuntilitisliquidandcompareittotheestimatedmulti‐periodSharperatioforthemarket(givenitsTheSharperatiofortheilliquidassetmustbeatleastashighasthatforthemarket.SupposethatanalternativeinvestmenthasalockupperiodofeightyearsanditsICAPMgivenrequiredrateofreturnis12%butitsMPSRisbelowthatoftheSharperatioofmarketataneight‐yearhorizon.Ifincreasingitsexpectedreturnto20%makesthealternativeinvestment'sMSPRequaltheSharperatioofmarketattheeight‐yearhorizon,thentheestimateoftheilliquiditypremiumis20%‐12%=8%100%ContributionBreedsFormaltools‐FinancialMarketEquilibriumFormaltools‐FinancialMarketEquilibriumTheSingerandTerhaaranalysisadjuststheICAPMforimperfections,suchasilliquidityandmarketInreality,mostmarketsarenotfullysegmentedorDevelopedworldequitymarketshavebeenestimatedas80%integrated,whereasemergingmarketequitieshavebeenestimatedas65%integrated.Intheexampletofollow,wewilladjustforpartialmarketsegmentationbyestimatingariskpremiumassumingfullintegrationandariskpremiumassumingfullsegmentation,andthentakingaweightedaverageofthetworiskpremiums.100%ContributionBreedsFormaltools‐FinancialMarketEquilibriumExample:Formaltools‐FinancialMarketEquilibriumExample:Usingmarketriskpremiumstocalculateexpectedreturns,betas,Supposeananalystisvaluingtwomarkets.MarketAisadevelopedmarket,andMarketBisanemergingmarket.theinvestor’stimehorizonisfiveyears.theotherpertinentfactsare:SharperatiooftheglobalStandarddeviationoftheglobalinvestableportfolioRisk-freerateDegreeofmarketintegrationformarketADegreeofmarketintegrationformarketBStandarddeviationofMarketAStandarddeviationofMarketBCorrelationofMarketAwithglobalportCorrelationofMarketBwithglobalportEstimatedilliquiditypremiumforAEstimatedilliquiditypremiumforBCalculatetheassets’expectedreturns,betas,and100%ContributionBreedsFormaltools‐FinancialMarketEquilibriumFirst,Formaltools‐FinancialMarketEquilibriumFirst,wecalculatetheequityriskpremiumforbothmarketsassumingintegration.Notethatfortheemergingmarket,theilliquidityriskpremiumisNext,wecalculatetheequityriskpremiumforbothmarketsassuming100%ContributionBreedsFormaltools‐FinancialMarketEquilibriumWeFormaltools‐FinancialMarketEquilibriumWethenweighttheintegratedandsegmentedriskpremiumsbythedegreeintegrationandsegmentationineachmarkettoarriveattheweightedaverageequityriskpremium:Theexpectedreturnineachmarketfiguresintherisk‐free100%ContributionBreedsFormaltools‐FinancialMarketEquilibriumTheFormaltools‐FinancialMarketEquilibriumThebetasineachmarket,whichwillbeneededforthecovariance,calculatedLastly,wecalculatethe100%ContributionBreedsORGANIZINGTHETASK:FRAMEWORKANDORGANIZINGTHETASK:FRAMEWORKANDAFrameworkforDevelopingCapitalMarketChallengesinTOOLSFORFORMULATINGCAPITALMARKETFormalSurveyandPanelBusinessCycleEconomicGrowthInternationalEconomicUsingEconomicInformationinForecastingAssetClass100%ContributionBreedsTheUseofSurveysandJudgmentforTheUseofSurveysandJudgmentforCapital SurveyandpanelThesurveymethodofexpectationssettinginvolvesaskinggroupofexpertsfortheirexpectationsandusingtheresponsesincapitalmarketformulation.Ifthegrouppolledisfairlyconstantovertime,thismethodisreferredtoasapanelmethodTheexpectations‐settingprocessneverthelesscangivewidescopetoapplyingjudgment—inparticular,economicandpsychologicalinsight—toimproveforecasts.100%ContributionBreedsORGANIZINGTHETASK:FRAMEWORKANDORGANIZINGTHETASK:FRAMEWORKANDAFrameworkforDevelopingCapitalMarketChallengesinTOOLSFORFORMULATINGCAPITALMARKETFormalSurveyandPanelBusinessCycleEconomicGrowthInternationalEconomicUsingEconomicInformationinForecastingAssetClass100%ContributionBreedsBusinessCycleEconomicoutputhascyclical(moreshort‐term)andgrowthtrendBusinessCycleEconomicoutputhascyclical(moreshort‐term)andgrowthtrend(morerelevantfordetermininglong‐termreturncyclicalfluctuationofinventory,2‐4years)andthebusinesscyclefluctuationsinGDPinrelationtolong‐termtrendgrowth,9‐11Changesineconomicactivitydelineatecyclicalactivity.themeasuresofeconomicactivityareGDP,theoutputgap,andarecession.Atypicalbusinesscyclehasfiveinitiallateupswing,100%ContributionBreedsFivePhasesoftheBusiness100%ContributionBreedsFiscalandCapitalFivePhasesoftheBusiness100%ContributionBreedsFiscalandCapitalstartstostockpricesstronglyHealthyeconomicremainslowShortratesmovingup;bondyieldsstabletoupslightly;stockpricestrendingupwardpicksupShortratesrising;bondyieldsrising;stockstoppingout,oftenvolatiletoaccelerate;Short‐terminterestratespeaking;bondyieldstoppingoutandstarting declinestocksdecliningShortratesdeclining;bondyieldsdropping;stocksbottomingandthenstartingtoBusinessCycleInventoryAcyclemeasuredinBusinessCycleInventoryAcyclemeasuredintermsoffluctuationsinDuetotheexpectedfutureBemeasuredusinginventorytosalesratioIntheupphaseConfidentwithfutureIncreaseinproductionandresultsineconomyWhendisappointedwithfutureDecreaseinWhentheinventory/salesratiohasmoveddown,theeconomylikelytobestronginthenextfewquartersasbusinessestrytorebuildinventory.Conversely,whentheratiohasmovedsharplyup,aperiodofeconomicweaknesscanbeexpected.Improvedtechniquessuchas"justintime"inventory100%ContributionBreedsBusinessCycleAggregateinflationismeasuredBusinessCycleAggregateinflationismeasuredmostfrequentlybyconsumerpriceInflationrisesinthelatterstagesofeconomicexpansionandfallsduringarecessionandtheinitialrecovery.Whenforecasting,theanalystshouldadjusttheinflationfigureforchangesinDeflation,orperiodsofdecreasingprices,reducestheabilityofthebanktostimulatetheDeflationresultsininterestratesnearzero,sothecentralbankcannotlowerratesanyfurthertostimulatetheeconomy.Forthisreason,centralbankspreferalowlevelofinflationtotheprospectofdeflation.100%ContributionBreedsInflation/deflationeffectsonasset100%ContributionBreedsRealAssetsatorInflation/deflationeffectsonasset100%ContributionBreedsRealAssetsatorsteadyorYieldlevelsmarketinBullishwhilemarketinequilibriumstate.CashflowSteadytoRisingslightly.ReturnsEquatetolong-termAverage.MarketingeneralBiastowardhigheryieldsduetoahigherinflationHighinflationanegativeforfinancialassets.Lessnegativeforcompanies/industriesabletopassoninflatedcosts.Assetvaluesandhigherexpectedreturns.[Positive]termPurchasingpowerincreasing.Biastowardsteadytolowerrates(maybeoffsetbyincreasedriskofpotentialdefaultsduetofallingassetprices).slowsdemand.Especiallyaffectsasset-intensive,commodity-producing(asopposedhighlyleveredcompanies.[Negative]Cashflowssteadytofalling.AssetpricesfaceDownwardBusinessCycleAnalysis‐ConsumerSpending,Business MonetaryPolicy,andFiscalBusinessCycleAnalysis‐ConsumerSpending,Business MonetaryPolicy,andFiscal ConsumerAsapercentageofGDP,consumerspendingismuchlargerthanbusinessspending.Consumerspendingisusuallygaugedthroughtheuseofstoresalesdata,retailsales,andconsumerconsumptiondata.Thedatahasaseasonalpattern,withsalesincreasingnearholidays.Savingsdataarealsoimportantforpredictingconsumerspending.Savingratesareinfluencedbyconsumerconfidence.BusinessSpendingbybusinessesoninventoryandinvestmentsisquitevolatileThepeakofinventoryspendingisoftenabearishsignalfortheeconomy.Itmayindicatethatbusinesseshaveoverspentrelativetotheamounttheyareselling.Aparticularlyusefuldataisthepurchasingmanagersindex(PMI),includingproductionplans,inventories,pricespaid,pricesreceived,andhiringplans.50shouldbethebreakevenpointformanufactur‐inggrowth.100%ContributionBreedsBusinessCycleAnalysis‐ConsumerSpending,Business MonetaryPolicy,andFiscal MonetaryBusinessCycleAnalysis‐ConsumerSpending,Business MonetaryPolicy,andFiscal MonetaryThelatterstagesofaneconomicexpansionareoftencharacterizedbyincreasedinflation.Asaresult,centralbanksusuallyresorttorestrictivepoliciestowardsthelatterpartofanexpansion.Tospurgrowth,acentralbankwillcutshort‐terminterestrates.TheTaylorruleFiscalIfthegovernmentwantstostimulatetheeconomy,itcandecreaseand/orincreasespending,therebyincreasingthebudgetAnanalystshouldfocusonthechangesinthegovernmentbudgetarydeficit,notitslevel.Itisonlychangesinthedeficitduetodeliberatechangesingovernmentfiscalpolicythatmatter.Theyield100%ContributionBreedsTheTaylorTheTaylorrulegivestheoptimalshort‐terminterestrateastheneutralrateplusanamountthatispositivelyrelatedtotheexcessoftheGDPandinflationgrowthratesabovetheirrespectivetrendandtarget0.5TheTaylorTheTaylorrulegivestheoptimalshort‐terminterestrateastheneutralrateplusanamountthatispositivelyrelatedtotheexcessoftheGDPandinflationgrowthratesabovetheirrespectivetrendandtarget0.50.5irtarget/targrtarget=theshort‐terminterestrater=theneutralshort‐terminterest=theexpectedGDPgrowthtrend=thelong‐termtrendintheGDPgrowthiexpected=theexpectedinflationi=thetargetinflation100%ContributionBreedsExampleforTheTaylorExampleforTheTaylorTheneutralvalueoftheshortterminterestrateisTheinflationtargetisTheGDPtrendrateofgrowthisIftheinflationforecastis4percentandtheforecastforGDPgrowthis1%,whatistheoptimalshortterminterestrate?Solution：AccordingtotheTaylorRule,TheGDPgrowthforecastbyitselfimpliesthattheshort‐terminterestshouldloweredby1percentagepoint,becauseGDPgrowthisundertrend.Partiallyoffsettingtheeffectofbelow‐trendGDPgrowthistheinterestrateincreaseimpliedbyabove‐targetinflation.Net,theTaylorruleimpliesthatthecentralbankshouldlowershort‐termratesby25bpsto3.25%.100%ContributionBreedsTheYieldTheYieldmaturityofthedebtsecurityandissensitivetoactionsofthefederalgovernmentaswellascurrentandexpectedeconomicconditions.Whenbothfiscalandmonetarypoliciesareexpansive,theyieldcurvesharplyupwardslopingandtheeconomyislikelytoexpandintheWhenfiscalandmonetarypoliciesarerestrictive,theyieldcurveisdownwardslopingandtheeconomyislikelytocontractinthefuture.whenfiscalandmonetarypoliciesareindisagreement,theshapeoftheyieldcurveislessdefinitive.Monetarypolicycontrolsprimarilyshort‐terminterestrates.100%ContributionBreedsPolicymixandtheyield100%ContributionBreedsPolicymixandtheyield100%ContributionBreedsFiscalYieldcurveYieldcurvemoderatelyYieldcurveYieldcurveEconomicGrowthTheeconomicgrowthtrendEconomicGrowthTheeconomicgrowthtrendisthelong‐termgrowthpathofEconomictrendsexistindependentlyofthecyclebutarerelatedtoit.Businesscyclestaketheeconomythroughanalternatingsequenceofslowandfastgrowth,oftenincludingrecessionsandeconomicbooms.thetrendgrowthinGDPisthesumofthegrowthfromlaborinputs,growthinpotentiallaborforcesizegrowthinactuallaborforceparticipation,growthfromlaborproductivity,growthfromcapitalinputsTotalfactorproductivity(TFP)growth(i.e.,growthfromincreaseintheproductivityinusingcapitalinputs)100%ContributionBreedsEconomicGrowthTrends‐Example:ForecastingEconomicGrowthTrends‐Example:Forecastingthelong‐termeconomicgrowthAssumethatthepopulationisexpectedtogrowby2%andthatforceparticipationisexpectedtogrowby0.25%.Ifspendingonnewcapitalinputsisprojectedtogrowat2.5%andtotalfactorproductivitywillgrowby0.5%,whatisthelong‐termprojectedgrowthrate?Thesumofthecomponentsequals2%+0.25%+2.5%+0.5%=5.25%,theeconomyisprojectedtogrowbythis100%ContributionBreedsEconomicGrowthConsumerspendingisthelargestEconomicGrowthConsumerspendingisthelargestcomponentofGDPandisfairlyoverthebusinessThereasonisthatindividualstendtoconsumeanamountthatisconstantovertimeandrelatedtotheirexpectedlong‐runAsappliedtotheformulationofcapitalmarketexpectations,itmeansthateconomicslowdownswillnotaffectconsumerconsumptionmuch.Inarecession,individualswillsavelessanddecreaseconsumptionbyonlyasmallInanexpansion,individualsconsumemore,butlessthantheirincomeincreases.Insum,wheneventsoccurthatconsumersperceiveastemporary,theirconsumptionandaggregateconsumerspendingwillnotchangeagreatdeal.100%ContributionBreedsEconomicGrowthGovernmentalstructuralpolicies:theEconomicGrowthGovernmentalstructuralpolicies:thetypesofpoliciesthatenhanceFirst,althoughthegovernmentshouldprovidetheinfrastructureneededforgrowth,thegovernmentshouldinterferewiththeeconomyaslittleaspossible.Second,agovernmentshouldhavearesponsiblefiscalBudgetdeficitsarealsooftenaccompaniedbytradedeficits,whichmayresultinaneventualdevaluationofthehomePublicborrowingmaycrowdoutmoreproductiveprivateThird,agovernmentshouldhavetaxpoliciesthataretransparent,consistentlyapplied,pulledfromawidebase,andnotoverlyLastly,thegovernmentshouldpromotecompetitioninthemarketplace,therebyincreasingtheefficiencyoftheeconomy.100%Contribut