dynamic stock selection strategies a structured factor model framework free energy sequential monte carlo

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1、DynamicStockSelectionStrategies:AStructuredFactorModelFramework*UniversityPressScholarshipOnlineOxfordScholarshipOnlineBayesianStatistics9JoséM.Bernardo,M.J.Bayarri,JamesO.Berger,A.P.Dawid,DavidHeckerman,AdrianF.M.Smith,andMikeWestPrintpublicationdate:2011P

2、rintISBN-13:9780199694587PublishedtoOxfordScholarshipOnline:January2012DOI:10.1093/acprof:oso/9780199694587.001.0001DynamicStockSelectionStrategies:AStructuredFactorModelFramework*CarlosM.CarvalhoHedibertF.LopesOmarAguilarDOI:10.1093/acprof:oso/978019969458

3、7.003.0002AbstractandKeywordsWeproposeanovelframeworkforestimatingthetime‐varyingcovariationamongstocks.OurworkisinspiredbyassetpricingtheoryandassociateddevelopmentsinFinancialIndexModels.Weworkwithafamilyofhighlystructureddynamicfactormodelsthatseektheext

4、ractionofthelatentstructureresponsibleforthecross‐sectionalcovariationinalargesetoffinancialsecurities.Ourmodelsincorporatestockspecificinformationintheestimationofcommonalitiesanddelivereconomicallyinterpretablefactorsthatareusedbothasavehicletoestimatethe

5、largetime‐varyingcovariancematrix,andasapotentialtoolforstockselectioninportfolioallocationproblems.Inanempiricallyoriented,high‐dimensionalcasestudy,weshowcasetheuseofourmethodologyandhighlighttheflexibilityandpowerofthedynamicfactormodelframeworkinfinanci

6、aleconometrics.Page1of24DynamicStockSelectionStrategies:AStructuredFactorModelFramework*Keywords:DynamicFactorModels,FinancialIndexmodels,Portfolioselection,Sparsefactormodels,StructuredloadingsSummaryWeproposeanovelframeworkforestimatingthetime‐varyingcova

7、riationamongstocks.OurworkisinspiredbyassetpricingtheoryandassociateddevelopmentsinFinancialIndexModels.Weworkwithafamilyofhighlystructureddynamicfactormodelsthatseektheextractionofthelatentstructureresponsibleforthecross‐sectionalcovariationinalargesetoffi

8、nancialsecurities.Ourmodelsincorporatestockspecificinformationintheestimationofcommonalitiesanddelivereconomicallyinterpretablefactorsthatareusedbothasavehicletoestimatethelargetime‐varyingcovariancema