现代资产组合理论和资本资产定价模型分析PPT推荐.ppt
- 文档编号:15416757
- 上传时间:2022-10-30
- 格式:PPT
- 页数:54
- 大小:155KB
现代资产组合理论和资本资产定价模型分析PPT推荐.ppt
《现代资产组合理论和资本资产定价模型分析PPT推荐.ppt》由会员分享,可在线阅读,更多相关《现代资产组合理论和资本资产定价模型分析PPT推荐.ppt(54页珍藏版)》请在冰豆网上搜索。
ModernPortfolioTheoryTheFactorModelsandTheArbitragePricingTheoryChapter8ByDingzhaoyongReturn-generatingProcessandFactorModelsReturn-generatingprocessIsastatisticalmodelthatdescribehowreturnonasecurityisproduced.ThetaskofidentifyingtheMarkowitzefficientsetcanbegreatlysimplifiedbyintroducingthisprocess.Themarketmodelisakindofthisprocess,andtherearemanyothers.Return-generatingProcessandFactorModelsFactormodelsThesemodelsassumethatthereturnonasecurityissensitivetothemove-mentsofvariousfactorsorindices.Inattemptingtoaccuratelyestimateexpectedreturns,variances,andcovariancesforsecurities,multiple-factormodelsarepotentiallymoreusefulthanthemarketmodel.Return-generatingProcessandFactorModelsImplicitintheconstructionofafactormodelistheassumptionthatthereturnsontwosecuritieswillbecorrelatedonlythroughcommonreactionstooneormoreofthespecifiedinthemodel.Anyaspectofasecuritysreturnunexplainedbythefactormodelisuncorrelatedwiththeuniqueelementsofreturnsonothersecurities.Return-generatingProcessandFactorModelsAfactormodelisapowerfultoolforportfoliomanagement.Itcansupplytheinformationneededtocalculateexpectedreturns,variances,andcovariancesforeverysecurity,whicharethenecessaryconditionsfordeterminingthecurvedMarkowitzefficientset.Itcanalsobeusedtocharacterizeaportfoliossensitivitytomovementinthefactors.Return-generatingProcessandFactorModelsFactormodelssupplythenecessarylevelofabstractionincalculatingcovariances.Theproblemofcalculatingcovariancesamongsecuritiesrisesexponentiallyasthenumberofsecuritiesanalyzedincrease.Practically,abstractionisanessentialstepinidentifyingtheMarkowitzset.Return-generatingProcessandFactorModelsFactormodelsprovideinvestmentmanagerswithaframeworktoidentifyimportantfactorsintheeconomyandthemarketplaceandtoassesstheextenttowhichdifferentsecuritiesandportfolioswillrespondtochangesinthesefactors.Aprimarygoalofsecurityanalysisistodeterminethesefactorsandthesensitivitiesofsecurityreturntomovementsinthesefactors.One-FactorModelsTheone-factormodelsrefertothereturn-generatingprocessforsecuritiesinvolvesasinglefactor.Thesefactorsmaybeoneofthefollowings:
@#@ThepredictedgrowthrateinGDPTheexpectedreturnonmarketindexThegrowthrateofindustrialproduc-tion,etc.One-FactorModelsAnexamplePage295:
@#@Figure11.1One-FactorModelsGeneralizingtheexampleAssumptionsTherandomerrortermandthefactorareuncorrelated.(Why?
@#@)Therandomerrortermsofanytwosecuritiesareuncorrelated.(Why?
@#@)One-FactorModelsExpectedreturnVarianceCovarianceOne-FactorModelsTwoimportantfeaturesofone-factormodelThetangencyportfolioiseasytoget.Thereturnsonallsecuritiesrespondtoasinglecommonfactorgreatersimplifiesthetaskofidentifyingthetangencyportfolio.Thecommonresponsivenessofsecuritiestothefactoreliminatestheneedtoestimatedirectlythecovariancesbetweenthesecurities.Thenumberofestimates:
@#@3N+2One-FactorModelsThefeatureofdiversificationistrueofanyone-factormodel.Factorrisk:
@#@Nonfactorrisk:
@#@DiversificationleadstoanaveragingoffactorriskDiversificationreducesnonfactorriskOne-FactorModelsMultiple-FactorModelsThehealthoftheeconomyeffectsmostfirms,buttheeconomyisnotasimple,monolithicentity.SeveralcommoninfluenceswithpervasiveeffectsmightbeidentifiedThegrowthrateofGDPThelevelofinterestrateTheinflationrateThelevelofoilpriceMultiple-FactorModelsTwo-FactorModelsAssumethatthereturn-generatingprocesscontainstwofactors.Multiple-FactorModelsThesecondequationprovidesatwo-factormodelofacompanysstock,whosereturnsareaffectedbyexpectationsconcerningboththegrowthrateinGDPandtherateofinflation.Page301:
@#@Figure11.2Tothisscatterofpointsisfitatwo-dimensionalplanebyusingthestatisticaltechniqueofmultiple-regressionanalysis.Multiple-FactorModelsFourparametersneedtobeestimatedforeachsecuritywiththetwo-factormodel:
@#@ai,bi1,bi2,andthestandarddeviationoftherandomerrorterm.Foreachofthefactors,twoparametersneedtobeestimated.Theseparametersaretheexpectedvalueofeachfactorandthevarianceofeachfactor.Finally,thecovariancebetweenfactors.Multiple-FactorModelsExpectedreturnVarianceCovarianceMultiple-FactorModelsThetangencyportfolioTheinvestorcanproceedtouseanoptimizertoderivethecurveefficientset.DiversificationDiversificationleadstoanaveragingoffactorrisk.Diversificationcansubstantiallyreducenonfactorrisk.Forawell-diversifiedportfolio,nonfactorriskwillbeinsignificant.Multiple-FactorModelsMultiple-FactorModelsSector-FactorModelsSector-factormodelsarebasedontheacknowledgethatthepricesofsecuritiesinthesamei
- 配套讲稿:
如PPT文件的首页显示word图标,表示该PPT已包含配套word讲稿。双击word图标可打开word文档。
- 特殊限制:
部分文档作品中含有的国旗、国徽等图片,仅作为作品整体效果示例展示,禁止商用。设计者仅对作品中独创性部分享有著作权。
- 关 键 词:
- 现代 资产 组合 理论 资本 定价 模型 分析