品职教育2017年cfa二级portfolio management知识框架图-何旋版

PortfolioPortfolioCFA二级培训项ReadingArbitrageArbitragepricingtheory(APT)公E(RP)RFP,1(1)P,2(2)...P,k(k （均衡模型 计λ:factorriskpremium(orfactorβp:factorAfactormodeldescribesassetTherearemanyassets,soinvestorscanformwell-diversifiedportfoliosthateliminatespecific特不同的asset，λ1一样，βp,1不一只有well-diversifiedportfolios满足这个公式，no-arbitrageCarhartfour-factormodelanextensionofFamaand 理E(RE(Rp)=RF+βp,1RMRF+βp,2SMB+βp,3HML+βp,4WML;WML=winnersminuslosers,amomentumCAPM:therearesize,value,andmomentumCarhartmodel:size,value,andmomentumrepresentsystematicriskMacroeconomicFactor计算、性Rab b （回归模型 i1 i2 Ri=returnforassetai=E(Ri)=expectedreturnforassetFGDP=surpriseintheGDPSurprise=actualvalue–expectedbi1=GDPsurprisesensitivityofassetεi=firm-specific不同的asset:F一样，b不一Riaibi1FP/Ebi2FSIZEai:Noeconomicinterpretation Standardizedbeta:b(P/E)1- P/F:factorCross-sectional不同的assetF一样，b不一Statisticalfactormodels

结论、性FactorFactorModelsinReturnNN

Activereturn=Rp–Portfoliosensitivity arksensitivityFactorreturn

kk

k Factortilts:over-orunderweightsrelativetotheben arkfactor

Securityselection:reflectsthemanager’sskillinindividualassetselectionFactorFactorModelsinRisktheactivenon-factororriskassumedbytheActivespecificrisk(securitytheactivenon-factororriskassumedbytheActivespecificrisk(securityselectionActivefactorInformationRatioRP s(RR

resultingfromtheportfolio’s exposuresrelativetofactorsspecifiedintheriskmodel.TheTheinvestorwhodependsefromsalaryorself-employmentissensitivebusinesscycleriskandhemightbeverysensitivetoinvestinprocyclicalAninvestorwithindependentwealthandnojob-lossconcernswouldhavecomparativeadvantageinbearingbusinesscycleFactorModelsinPortfolioFactorsensitivityequalto1toonlyoneriskfactorandsensitivitiesof0totheremaining应用：hedgethatriskoffsetitorspeculateonTrackingPortfoliowithfactorsensitivitiesthatmatchbenark-FactorFactorModelsinPortfolioAcceptaboveaverageexposurestorisksthattheyhaveacomparativeadvantageinIndividualtradedequitiesortheliquidityReadingMEASURINGANDMANAGINGMARKETValueValueatRisk:FormalValueatrisk(VaR)istheminimumlossineithercurrencyunitsorasapercentageofportfoliovaluethatwouldbeexpectedtobeincurredacertainpercentageofthetimeoveracertainperiodoftimegivenassumedmarketconditions.X 结论、Theriskfactorsaredistributednormally,whichallowsTheriskfactorsaredistributednormally,whichallowsustoestimatetheriskofthebasedonlyonthemeans,variances,andcovariances(orVaR(X%)decimalbasisE(R)J计assetThemajoradvantageoftheparametricmethodisitssimplicityandThecalculatedVaRisalsoverysensitivetothecovarianceTheparametricmethodapplyundertheassumptionofnormallydistributedreturns.Whentheportfoliocontainsoptions,theparametricmethodhaslimitedusefulness. EstimatingVaRisbasedEstimatingVaRisbasedontheactualperiodicchangesinriskfactorsoveralookbackperiod.Byorderingthechangesinportfoliovaluefrommostpositivetomostnegative,wecanfindthelargest5%oflosses.Thesmallestofthoselossesisourestimateofthe5%VaRTheHistoricalUnderthehistoricalsimulationmethod,noadjustmentsaremadefordifferenttimeThehistoricalsimulationVaRsaremuchBoththeparametricandhistoricalsimulationmethodshavethelimitationthatAdvantageofthehistoricalsimulationDonotneedtheassumptionofCanbeusedtoestimatetheVaRforportfoliosthatincludebasedonwhatactuallyWeaknessofthehistoricalsimulationTherecanbenocertaintythatahistoricaleventwillre-Thehistoricalsimulationmethodisbestusedwhenthedistributionofreturnsduringlookbackperiodareexpectedtoberepresentativeofthe MonteCarlosimulationisMonteCarlosimulationisbasedonanassumedprobabilitydistributionforeachriskComputersoftwareisusedtogeneraterandomvalues.Themorevaluesweuse,thereliableouranswersare,butthemoretime-TheflexibilityoftheMonteCarlomethodtohandlemorecomplexdistributions.TheMonteCarloandhistoricalsimulationmethodsaremuchmorecapableincorporatingtheeffectsofoptionpositions.Withthespeedoftoday’scomputers,itisrelativelyeasyandfasttosimulateextremelycomplexprocessesAdvantages&DisadvantageofNonparametricMethodsComparedToParametric TheconceptofVaRissimpleandeasytoVaRallowstheriskofdifferentportfolios,assetclasses,ortradingoperationstobe

VaRcanbeusedforperformanceevaluation(calculationoftheratio etoAfirmsriskmanagerscanlookattheallocationofVaRandoptimizetheallocationofReliabilityofVaRasameasureofriskcanbeverifiedbyVaRestimationrequiresmanychoicesandcanbeverysignificantlyaffectedbytheseTheassumptionofnormalityleadstounderestimatesofdownside(tail)AVaRwillunderstatetheactuallossesincurredwhenliquidatingIncreasingcorrelationsmeanthatVaRmeasuresbasedonnormallevelsofcorrelationoverestimatediversificationbenefitsandunderestimatethemagnitudeofpotentialManyaspectsofriskare fiedorVaRfocusesonlyondownsideriskandextreme 结Extensionsof 概TheCVaRistheexpectedloss,giventhatthelossisequaltoorgreaterthantheIncrementalVaRthechangeinVaRfromachangeintheportfolioallocationtoaMarginalVaRthechangeinVaRfora1%increaseinthesecurity’sMarginalVaRmaybeusedtodeterminethecontributionofeachassettotheoverallmeasurestheVaRofthedifferencebetweenthereturnonaportfolioandthereturnonitsmanagers arkportfolioSensitivityandScenarioMeasures

概念、对SensitivityRiskMeasures:focusesontheeffectonportfoliovaluegivenasmallchangeinoneriskScenarioRiskMeasures:Whilesensitivityysisprovidesanestimateofthechangeinportfoliovalueduetoasmallchangeinasingleriskfactor,scenarioysisprovidesanestimateoftheeffectonportfoliovalueofasetofchangesofsignificantmagnitudeinmultipleriskfactors.Stresstests:ApplyextremenegativestresstoaparticularportfolioScenarios&HistoricalScenariosScenarios&HistoricalScenarios:UseasetofchangesinriskfactorsthathaveactuallyoccurredintheespeciallychangesduringaperiodoffinancialdisruptionandHypotheticalScenarios:Anysetofchangesinriskfactorscanbeused,notjustonethathashappenedinthepast.AhypotheticalscenariocouldhavemoreextremechangesinriskfactorsthanthosethathaveoccurredinthepastTheuseofPartiesthatuseleverage,suchasbanksandhedgefunds:pass/failLong-onlyassetmanagersdonottypicallyuseleverageandarethuslesslikely insolvent,makingapass/failtestforsolvencylessrelevanttoReversestresstesting:Todesignaneffectivehypotheticalscenario,itisnecessarytoidentifytheportfolio’smostsignificantexposures.SensitivityandScenarioRiskMeasures&VaRisaVaRisameasureoflossesandtheprobabilityoflargeSensitivityriskmeasurescapturechangesinthevalueofanassetinresponseachangeinriskfactor;theydo lusanythingabouttheSimilarity:estimatepotentialSimilarity:estimatepotentialTheVaRestimateisvulnerableifcorrelationrelationshipsandmarketarenotrepresentativeoffuture ysisallowstheriskassessmenttobefullyAdvantagesandLimitationsofSensitivityandScenarioRiskSensitivityandscenarioriskmeasurescancomplementVaRinthefollowingTheydonotneedtorelyonScenarioscanbedesigned eanyassumptionofnormalScenarios:allowingliquiditytobetakenintoLimitationsofScenarioRiskHistoricalscenariosareinterestingbutarenotgoingtohappeninexactlythesamewayHypotheticalscenariosmayincorrectlyspecifyhowassetswillco-HypotheticalscenarioscanbeverydifficulttocreateandItisverydifficulttoknowhowtoestablishtheappropriatelimitsona ysisorstress 了机结sensitivitymeasures,scenarioysisandstresstesting,leverageriskmeasures,VaRasset-liabilityHedgeassetfocusonrelativeriskEx-posttrackingerrorisameasureoveralookbackperiod.Ex-posttrackingerrorisusedforperformanceattributionandtoassessmanagerskilloverpriorperiods.pensionfundssurplus-at-InsuranceLifeinsurers:morehighlycorrelatedwiththemarketandbygeographicalRiskBudgeting:firstdeterminestheacceptableRiskBudgeting:firstdeterminestheacceptabletotalrisk,andthenPositionlimits:limitriskbecausetheyensuresomeminimumlevelofScenariolimitsarelimitsonexpectedlossforagivenStop-losslimitsrequirethatariskexposurebereducediflossesexceedaspecifiedamountoveracertainofReadingECONOMICSANDINVESTMENT整章以结论为 CF CF t ts

lt,s:realdefault-freeinterestinflation-linkedbondissuedby ernmentofadevelopedθt,s:expectedinflationPt

•nominaldefault-frees11lt,st,st,s

ρit,s:compensationofuncertaintyabouttheasset’sfuturecashCreditrisk,liquidityTheDiscountRateonRealDefault-freeBonds

Inter-temporalratem=marginalutilityofconsumptionfuture/marginalutilityofconsumptionWealthincreases→marginalutilityInter-temporalrateofsubstitutionislowerinthegoodstateoftheOne-periodrealrisk-freerateisinverselyrelatedtotheinter-temporalrateofsubstitution.Thatis,thehigherthereturntheinvestorcanearn,themoreimportantcurrentconsumption esrelativetofutureconsumption.Pricingas-PeriodFreePt,s=riskneutralpresentvalue(discountedattherisk-freerate)+covariance(discountforrisk-averseinvestors:Negativecovarianceterm→assetreturn>risk-freePositivecovarianceterm→assetreturn<risk-freeDefault-FreeInteresthighertrendrealeconomicgrowth→higherrealdefault-freeinterestratesGDPgrowthismorevolatile→realinterestratesarehigherTheYieldCurveonNominalDefault-freeBonds

compensatefortheexpectedinflation,θ ycompensationfortakingontheuncertaintyrelatedtofutureinflationtheexpectedinflation,πt,s+θBeinfluencedbytheinflationenvironmentandinflationexpectationsoverBeinfluencedbyrealeconomicactivity,whichisinfluencedbythesavingandinvestmentTheseinterestrateswillalsobeaffectedbythecentralbank’spolicyrate,whichshouldfluctuatetheneutralpolicyBEI=θt,sLong-YieldInvestorExpectations:expectinterestratestodecline→yieldcurvetobedownwardsloorTheTermSpreadandtheBusinessCycle:Termspread=long-termrate–short-termArecessionisoftenprecededbyaflattening,orevenaninversion,intheyieldDuringarecession,shortratesareoftenlowerbecausecentralbankstendtolowertheirpolicyandtheslopeoftheyieldcurvewilltypicallysteependuringaCorrelationbetweenthebondpriceandtheeconomicgrowthisernmentbondriskpremiumsarepositiveandrelatedtotheconsumptionhedgingbenefitsShort-datedbondshavebeenmorereliablehedgesagainstbadeconomicDefault-freerate=lt,s+πt,s+θt,s→interestrateCredit-risky

Creditpremium(creditspread)=γt,s→credit结Expectedloss=probabilityofdefault×(1–recoveryDefaultstendtoclusterarounddownturnsinthebusinesscycle.Defaultrateincreases.RecoveryratestendtobehigherwhentheeconomyexpandingandlowerwhenitisCreditPremiumsandTheBusinessBondspreadsdotendtoriseintheleaduptoandduringarecession,andtodeclineoncetheeconomycomesoutofrecession.Asthebusinesscycleturnsdown,andspreadswiden,thoseissuerswithagoodcreditratingtendtocreditriskybonds(corporateorsovereign)tendperformpoorlyinbadeconomic

IndustrialSectorsandCreditQuality:Duringrecession,thespreadontheconsumercyclicalsectorrosemoredramaticallyCompany-SpecificFactors:Ifthisabilitytomeetitsdebtobligationsdeclines,thenthespreaddemandedontheirdebtwillriseSovereignCreditRisk:importantin emergingEquitiesEquitiesandTheEquityRiskPremiumEquityriskpremium,

γit,s→Creditrisk

→equitypremiumrelativetocreditriskyEquityRiskPremiumandtheeconomiccycleEquitiesareabadhedgeforbad es,soequityriskpremiumbepositive(pro-Intimesofeconomicweaknessorstress,equityriskpremiumTheP/EtendstoriseduringperiodsofeconomicAnincreaseinexpectationoffuturerealearningsFallingrealinterestrates,possiblyassociatedwithfallingvolatilityinrealGDPAfallininflationAdeclineinuncertaintyaboutfutureAfallintheequityriskInvestmentCyclicalsectorhasgreatersensitivitytobusinessDuringeconomicexpansion,byrotatingintogrowthstocks,orsmall-capstocks,orcyclicalstocks,amanagercan,ifcorrect,outperformabroadequitymarketCommercialCommercialRealEstateBond-like: emightberelativelyEquity-like:valueofThecapitalvaluesarehighlysensitivetotheeconomicArecessionwillgenerallycausethesevaluestoThepro-cyclicalnaturemeansthatinvestorswilldemandahighriskBadhedgeagainstbad ReadingYSISOFACTIVEPORTFOLIOValueValueaddedActivereturn(valueadded):Rp=Rp–Alpha(risk-adjustedcalculationofvalueadded):αP=RP–Rp=Rp–NRAwi ,Δwi=wP,i–wB,i(ThesumoftheactiveweightsisRAwiRAi,RAi=Ri– RARPRBwP,jRP,jwB,jRB, RAwjRB,jwP,jRA,

12012

RA

MM12assetallocation→wjRB,12MMsecurityselection→wP,jRA,ComparingRiskandReturnSharperatioSharperatioisunaffectedbytheadditionofcashorleverage(createdbyborrowingfreecash)inaSameSharpeRatio→combination=portfolio+/-SameSharpeRatio,changevolatilityσC目标volatility)=wpσPwfcashorleverage比例1PSRRPPP

结论、计Ac原portfolio的Ac原portfolio的权重1clong或short σCcσ(σC:目标activeriskσ:原active••TheinformationratioisaffectedbytheadditionofcashortheuseofTheinformationratioisunaffectedbytheaggressivenessofactiveSameInformationRatio→combinationportfolio=activeportfolio+/-ben SameSharpeRatio,changeactiverisk→Closetindexfund:advertisesitselfasactiveClosetindexfund:advertisesitselfasactivebutisactuallyclosetobeinganindexMarket-neutrallong–shortequityfund:offsettinglongandshortpositions s(RR SR2=

+IR2→TheexpectedinformationratioisthesinglebestOptimal

22B BOptimalamountofactiverisk izingactiveriskor“aggressiveness”)→ASRBTheFundamentalLawofActiveManagementIRTCTheFundamentalLawofActiveManagementKeyThecorrelationReturnsμi Active Realized△ ICCORRAi,i ihigherIC,orabilitytoforecastreturns→addmorePortfolioconstruction:transfercoefficientTCCORi,w ii degreetowhichtheinvestor’sforecastsaretranslatedintoactiveBRthenumberofindependentdecisionsmadeperIR ERA BRIRTCIC ERATCICBROptimalOptimalamountofactiverisk→ATCIR*BBConstrainedportfolio’ssquaredsharperatio→SR2=SR2+BApplicationofTheFundamental 结GlobalEquityUnconstrainedportfolio:IRisinvarianttothelevelofactiveConstrainedportfolio:IRgenerallydecreaseswiththeaggressivenessofthestrategy,inaccordancewithanincreasinglylowertransfercoefficient.e():Time-series(择时):比如每个季度判断一次市PracticalLimitationsofTheFundamental 结InvestorstendtooverestimatetheirInvestorstendtooverestimatetheirownskillsForecastingabilitydiffersamongdifferentassetsegmentsandvariesover BR

N1N1Allthestocksinagivenindustryorallthecountriesinagivenregionthatarerespondingtosimilarcannotbecountedas yindependentdecisions,sobreadthislowerthanthenumberofBreadthcanincreasewellbeyondthenumberofsecuritieswithhedgingstrategiesusingderivativesorotherformsofarbitrage.Increasingtherebalancingfrequencymayincreasetherealizedinformationratio,butonlytotheextentsequentialactivereturnforecastsareindependentfromperiodtoReadingALGORITHMICTRADINGANDHIGH-FREQUENCYTheBasicsofAlgorithmicTrading

概念、对AlgorithmicAlgorithmictrading:atradingstrategythathasbeenautomatedthroughtheuseofacomputer.ComputerstradingalgorithmsmakedecisionsandexecutetradesthousandsoftimesfasterthanahumanExecutionHigh-frequencyTradingslicealargeorderintosmallera