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dc.contributor.authorCooper, Ilan
dc.contributor.authorMaio, Paulo
dc.date.accessioned2019-08-09T10:57:05Z
dc.date.available2019-08-09T10:57:05Z
dc.date.created2018-10-22T11:14:06Z
dc.date.issued2018
dc.identifier.citationJournal of Financial and Quantitative Analysisnb_NO
dc.identifier.issn0022-1090
dc.identifier.urihttp://hdl.handle.net/11250/2607759
dc.description.abstractWe estimate conditional multifactor models over a large cross section of stock returns matching 25 CAPM anomalies. Using conditioning information associated with different instruments improves the performance of the Hou, Xue, and Zhang (HXZ) (2015) and Fama and French (FF) (2015), (2016) models. The largest increase in performance holds for momentum, investment, and intangibles-based anomalies. Yet, there are significant differences in the performance of scaled models: HXZ clearly dominates FF in explaining momentum and profitability anomalies, while the converse holds for value–growth anomalies. Thus, the asset pricing implications of alternative investment and profitability factors (in a conditional setting) differ in a nontrivial way.nb_NO
dc.language.isoengnb_NO
dc.publisherCambridge University Pressnb_NO
dc.titleNew Evidence on Conditional Factor Modelsnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionsubmittedVersionnb_NO
dc.description.versionacceptedVersionnb_NO
dc.rights.holderThe publisher, Cambridge University Press, allows the author to deposit the version of the article that has been accepted for publication, in an institutional repository.nb_NO
dc.source.journalJournal of Financial and Quantitative Analysisnb_NO
dc.identifier.doi10.1017/S0022109018001606
dc.identifier.cristin1622162
cristin.unitcode158,1,0,0
cristin.unitnameInstitutt for finans
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.fulltextpostprint
cristin.qualitycode2


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