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1、CFA：级培训项HTopic in CFA Level IllETHICS & PROFESSIONAL STANDARDS &：2Study Session 3BEHAVIORAL FINANCEStudySession1-2StudySession4CAPITALMARKETEXPECTATIONSStudy Session 5Study Session 6Study Session 78Study Session 910Study Session UStudy Session 12-13Study Session 14Study Session 15Study Session 16ASS
2、ETALLetations1Part1:FrameworkandMacroConsiderationsRllCapitalMarketExpectations.Part4-1152:ForecastingAssetClassReturnsSdBM.EtaCapitalMarketExpectations,Part1:FrameworkandMacroConsiderations11ZiflFramework1.ChallengeswhenformulatingCME2.ThetrendIateofgrowth3.Approachestoeconomicforecasting4.Thebusin
3、esscycle5.Monetarypolicyandfiscreateshort-termexsf，:，makingactiveinvestmentdecis:ns&15.M.3taAFrameworkforDevelopingCME，ThefollowingisJframeworkoradisciplinedapproachtosettingCME.1.Specif,teset:fexpectationsneededInClUdingthEtimehorizon：s:twhichtheyapply.2.Researchrhehistoricalrecord3.Specifythemetho
4、d(s)and/orm父同，$IQbeusedandthenInfsmationrequirements.4.Determinethebe“sourcesforinformationeed.5.Interpretthecurrentinvestmentenvironmentusingtheselecteddataandmethods,applyingexperiefreandjudgment.6.Povdethesetofexpectationsneededdocum?Eingconclusions7.Monitor.providingfeedbacktoimproveTheepectatns
5、-sengprocess.Bd2.M2LChallengesinForecasting1.LimitationstousingeconomicdataTl-timelagTheInternationalMonetaiyFund,forexample,reportsdatawithalagofJSmuchJStwoyears.一revisedasthepubhcaton.Additionally,datadefinitionsandmethodologychangeovertime.Dataindexesdieofterebased,timeIel!basepMKhtheyarecalculat
6、edischanged:.Althoughaebasingi$notasubstantialchangeinthedaaitself,theunawareanalystcouldcalculatechangesnthevalueoftheindexesincorrectlyfshedoesnotmakeanappropriateadjustment.ChallengesinForecasting2.DatameasurementerrorsandbiasesTranscriptionerrorsarethemisreportingorincorrectrecordingofinfomotion
7、andaemostSeiaUSiftheyaebiasedinonedirection.SurvivorshipbiasseriesisdeletedfronIhehistoricalpeormaeecodofmanagersorfirmsCH?etion$areoftentiedtopoorperformanceandbiastleIrstoncalreturnUPWJldAppraisaldatafc，illiquidanainfrequent;p,cedassetsmakesthepathofetunsappea,smoothervitactuallys.Thisbiasesdownwa
8、rdthecalculatedStandaiddeviationandnukesIhereturnsseemlesscorrelatedKlQSetQO)withmoreliquidpricedassetsThis田aparticularproblemfosometypesofalternativeassetssuchasrealestate.Sd5MEgChallengesinForecasting，3.LimitationsofhistoricalestimatesValuesfromhistoricaldatamustoftenbeadjustedgoingforv.ardasecoon
9、icpolitical,recuhtory.3IdtechnologalenvonnentschangeThAispartculaIvtrueforvolatileassetsSUChasequityTliesechangesareknowna.regimechangesj11dresultinnonstationarydata/Fsexample,theglobalfinancialcrisisin20072009?SUlIedinreturnsdatathatweremarkedlydifferentthanthosefromthepreviousfiveyears.11-115/Nons
10、tationarityouldmeandiffaentperiodsinthetimeserieshavedffeentstatisticalpropertiesandcreateproblemswithstandardstatisticaltesngmethods12.wZiQChallengesinForecasting，3.Limitationsofhistoricalestimates(con,t)AIQHgtimePeMQdTpefeablefSee?alreasons：It,vj.bestatisticallyrequiredTQCWLHaIkIlDWJlco,.aance(and
11、correlation),thenumberofdatapointsmustexceedthenunb0ofcovariancetobecalculated/AlargerdatasetTimeperiod)providesmore,erstdata,atrerrhefactodetermineeanv?beforethefactriskandreturnSnbepiOblematic.Theanalyst/.ouldunderestimatetherisksthatequitvresorsfaeanoverestimatetheirpotentialreturnsHQ，ciatasenesd
12、eseven,)ecbs-.,substantiallyoverstatethelikelihoodofSUCheventshappeninginthefuture./As3simpleexampletherevere21tradingdaystnJuly2018.On26July,thepriceQfRKebookstockcloseddown19：.Basedonthissampletheinterpolated)dy5c：VJRsFatsa】alsouncoverpatternsinsecritetrnsthatareunlikelytooccurinthefutureandcanpro
13、ducebiasesinthedata.3Datamining:Justbyalomhace.somevariableswilloppeartohave3relationshipwithSeCLrftyreturns,when,infacttheserelationshipsareunlikelytopersist.14-115Timeperiodbiaselatestoresultsthataretimeperiodspecific.Researchfindingsareoftenfoundtobesensitivetotheselectionofstartingardorendingdat
14、es.12.WZiQChallengesinForecasting5.BiasesinAnalystsMethodsHwtoavoidthesebiasesFirstananalyst$lK)uldfirstWSkHTV-an.ecn*:：?as$thevariablesfoundtoberelatedc-stockerurrs/SecondheShQUldscrutinizethemrgprocesstosustbMtobias.Third,theanalystshouldtestUYd2：SmIm:;la*ms*.*叶:-it-of-sampedatatcdeemineifH*r.W5Ns
15、$ruldbeonebyrtintlr,p-e,.:,htjvjtior$rn；:UlJMdFKbeusedira：.(i.eJT/MNitinvestigatingtheunderlyinglinkagesAlthoughapparentlysqfartnscanbespurious,itisalsoTrueThatackofastrongConWJtioncantemisleading/AnegligiblemeasuredrelatonmayeflectastrongbutnonlinearrelationshipAnalystsshouldexplorethispossibilityf
16、theyhaveasolidrea$onforbelieving3relationshipexists.口rChallengesinForecasting，8.PsychologicalbiasesAnchoringbias:Iwfust111.fat,eedscewegltedStatusquobias:”改hcm”sarehighl,l用Iu-JdhJrErcertpas.Confirmationbias:onlyinformationredelackofBmmTntSfromothersistaker*asagreement,andtheaccuracyofforecastsisover
17、estimated.Prudencebias:forecastsareovelycnsevat.etoavoidtheregretfrommakingextremeforecaststhatcouldendupbeingincorrect.Availabilitybias:.at$easiesttoremmb!OrtRnarextremea、misoverweighted.ChallengesinForecasting9.ModeluncertaintyModeluncertainty:referstoselectingtheColaTtmatmParameteruncertainty:ete
18、s1aAnalysisofEconomicGrowthrr:llong-term，；F-f三FEr.r-:rrrU：-；-,_一Businesscyclesa,*djst?门:Zdngrecs.3T:-oulremeexampleistheU.S.bankingCsisofthe1930$,.whenasevereslowdowninbanklendingparalyzedtheeconomy.ExogenousShockstoGrowthaExogenousShOCkSareunanticipatedeventsthatoccurousdethenormals:JnKUorlBenomy1w
19、hichwouldbeconsideredendogenous,arebuhintomarketprices.1statisticalregimechanges.ExogenousShockstoGrowthExogenousShoCkScanbecausedbyseveralfactorsChangesingovernmentpoliciesGovernnientpoliciesthatSnencowagelong-termgrowthincludesoundscalpolicyminima!governmentinterferencewithfreemarkets,facilitating
20、competitionintheprivatesector,developmentofinfrstructureandhumancapital,andsoundtaxpolicies.Politicalevents22-ll/Geopoliticaltensionsdialdvetesouestolesspodutveu$e$mayleadtodecreasesingrovh.Conversely,CUtSindefensespendingduetohigherlevelsofworldpeacemayleadtoincease$incpovh.Sd5.wWgExogenousShocksto
21、GrowthTechnologicalprogressThecreationofnevandinnovativemarkets,products,andtechnologieshasthepotentialtoimprovegrowth.Naturaldisasters/NJtuiaIdisasterslikelyreduceshot4emgrov/th.Ixitmaarguably；encouragelong-termgrowthIfmoreefficientcapaityreplaou,rrdjchcorR-、.“可：Storecoverexistingresourcesannarcg,j
22、.thFinancialcrises/ShOCkStothfinancialSySteMiIladtoJofconficlramongmarketparticipants.Finaniaijlmarkerexpetatons.SomeofthekeyconsiderationsQfecono11ngoMhtrendanalysisareasfollows:ForecastingetunseitDCFmodelsincorporaterhetrendrateOfgrowth.Highertendg,vtr7tesna,adtohigherstockretrnsassumingthegrowth4
23、notalreadyreflectedinstockpricesWhenwespeakofhighetef0v.1h13【eswemeantheeconomycangrowatafasterpacebeforeinflationbecomesamajorconcern.ThisconsiderationinfluencesmonwyPOliCyandtelevelofbondyields.HlTg!dUl15；yields.DecompositionofGDPGrowth“ThetrendgrowthinGDPisthesumofthefollowing:GlaVthfromlaborinpu
24、tsgrowthinpotentiallaborforcesize/growthinactuallaborforceparticipationGlgwthfromlaborproductivity/growthfromcapitalinputs：M1:/totalfactorproductivity(TFP)growth(i.e.growthfromincreaseintheproductivityinusingcapitalinputs)、2轩HBEconomicGrowthTrends，ForecastingGDPTrendGrowthIfwehavethef?lowinassumptio
25、ns/TleSiZTQftheCanadiarllaborforceKillgcaat1percentPEyearbasedCnpopulationqiectiosLaborforcepartipatiowillgrowJt0.25percentperyear.Growthfomcapitalinputswillbe1.5percentperyea./Totalfactorproductivitygrowthwillbe0.758.Forecastthetrendgrov/thinCanadianGDRCorrectAnswer:26-115ThetrendgrowthinGDP=growth
26、inpotentiallaborforcesize+growthinactualIaboiforceparticipation*growthfromcapitalinputs*totalfactorproductivitygrowth=1%+0.25%+L5%+O75%=35%.11二IQ2.AnchoringAssetReturnstoTrendGrowthThetrendgrowthratealsoprovidesananchorforlong-runequityappreciation.7rofthreefactors:thelevelofnominalGDPtheshareofprof
27、itstheeconomy,S(eaningsGDP;anc；Ih=PEiatKTPE：17=GDPfXSfXPEt3Asjresultinthelongrun,thegtovhYaOftI记tocaIaiUJofequityinaneconomyislinked10thegvvthIamfGDPOverfinitehorizons,thewayinwhichtheshareofcapitalandtheP/EmultipleareexpectedtoCharqewillalsoJ讦metrheforecastOfthetotalvalueOfequity,JSwell3$tscorespon
28、dinggroMliateoverthatperiod.Example”Long*RunEquityReturnsandEconomicGrowthInJanuary2000.AlenaornsdottirCFA,wasupdatingherfirmsprojectionsforUSequityreturns.Thefirmhadalwaysusedthehistoricalaveragereturnwithlittleadjustment.Bjornsdottirwasawarethathistoricalaveragesaresubjecttolargesamplingerrorsandw
29、asespeciallyconcernedaboutthisfactbecauseofthesequenceofveryhighreturnsinthelate1990$.ShedecidedtoexaminewhetherUSequityreturnssinceWorldWar11hadbeenconsistentwitheconomicgrowtl.Fortheperiod1946-1999,thecontinuouslycompounded(i.e.,logarithmic)returnwas12.18%perannm1whicheflectedthefollowingcomponent
30、s:RealGDPGrowthInflationEPS/GDP(Chg)PZE(Chg)DividendYield3.14%4.12%0.00%0.95%3.97%ExampleQUeStiOnS1.WhatconclusionwasBjomsdottirlikelyhavedrawnfromthisanalysis?，CorrectAnswers:Bjomsdottirislikelyhaveconcludedthatthepost-warstockreturnexceededwhatwouldhavebeenconsistentwithgrowthoftheeconomy.29山5Inpa
31、11kular.therisingP/Eadded95%ofextrareturnperyearfor54years,adding51.3%(=540.95%)tothecumulative,continuouslycompoundedreturnandleavingthemarket67%(e冷=1.67)abovefairvalue：11二IQExampleQuestions2.IfShebelievedthatinthelongrunthattheUSIaboiinputwouldgrowby0.9%percnumandlaborproductivityby1.5%thatinflati
32、onwouldbe2.1%thatthedividendyieldwouldbe2.25%,andthattherewouldbenofurthergrowthinP/E,whatislikelytohavebeenherbaselineprojectionforcontinuouslycompoundedIong-IHTnUSequityreturns?CorrectAnswer:HerbaselineprojectionisIlkelytohavebeen6.75c?=0.9：+1.5:,：+2IGc+2.25%.Example”Questions3.Inlightofheranalysi
33、s,howmightshehaveadjustedherbaselineprOjection?CorrectAnswer:Bl-U5SheislikelytohaveadjustedheprojectiondownwardtosomedegreetoreflectthelikelihoodthattheeffectoftheP/Ewoulddeclinetowardzeroovertime.Assuming,forexample,thatthiswouldoccurove30yearswouldimplyreducingthebaselineprojectionby171%=(51.3%3O)
34、peryear.jf2.wEta3.ApproachestoEconomicForecastingThreeapproachestoeconomicforecastingareeconometricmodeling,useofeconomicindicators,andachecklistapproach.1.EconometricanalysisusesstatisticalmethodstoexplaineconomicIelJtionshipsandformulateforecastingmodels.Stiuctuialmodelsarebasedoneconomictheorywhi
35、lereduced-formmodelsarecompactversionsofstructuralapproaches.Structuralmodelsspecifyfunctionalrelationshipsamongvariablesbasedoneconomictheory.Thefunctionalformandparametersofthesemodelsarederivedfromtheunderlyingtheory.32山5VReduced-formmodelsIiaveJlooserconnectiontotheory.11二IQApproachestoEconomicF
36、orecastingAdvantagesofEconometricAnalysis3Modelingcanincorporatemanyvariables.OnCethemodelisspecified,itcanbereused.OutputisquantifiedandbasedonaconsistentsetofrelationshipsDisadvantagesofEconometricAnalysisModelsarecomplexandtime-consumingtoconstructThedatamaybedifficulttoforecastandtherelationshipscanchange.Outputmayrequireinterpretationorbeunrealistic.ITdoesnotworkwelltofore:astturningpointsApproachestoEconomicForecasting2.Economicindicatorsaeavailablefromgovernments,internationalorganizations,andprivateorganizations.Tl-mostusefulindicator
