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How to explain the cross-section of equity returns through common principal components

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dc.affiliation.dptoUC3M. Departamento de Estadísticaes
dc.contributor.authorCueto, José Manuel
dc.contributor.authorGrané Chávez, Aurea
dc.contributor.authorCascos Fernández, Ignacio
dc.contributor.funderComunidad de Madrides
dc.date.accessioned2022-02-25T08:26:00Z
dc.date.available2022-02-25T08:26:00Z
dc.date.issued2021-05-01
dc.description.abstractIn this paper, we propose a procedure to obtain and test multifactor models based on statistical and financial factors. A major issue in the factor literature is to select the factors included in the model, as well as the construction of the portfolios. We deal with this matter using a dimensionality reduction technique designed to work with several groups of data called Common Principal Components. A block-bootstrap methodology is developed to assess the validity of the model and the significance of the parameters involved. Data come from Reuters, correspond to nearly 1250 EU companies, and span from October 2009 to October 2019. We also compare our bootstrap-based inferential results with those obtained via classical testing proposals. Methods under assessment are time-series regression and cross-sectional regression. The main findings indicate that the multifactor model proposed improves the Capital Asset Pricing Model with regard to the adjusted-R2 in the time-series regressions. Cross-section regression results reveal that Market and a factor related to Momentum and mean of stocks’ returns have positive risk premia for the analyzed period. Finally, we also observe that tests based on block-bootstrap statistics are more conservative with the null than classical procedures.en
dc.description.sponsorshipThis research was partially funded by the V Regional Plan for Scientific Research and Technological Innovation 2016–2020 of the Community of Madrid, an agreement with Universidad Carlos III de Madrid in the action of “Excellence for University Professors”.en
dc.format.extent22
dc.identifier.bibliographicCitationCueto, J. M., Grané, A., & Cascos, I. (2021). How to Explain the Cross-Section of Equity Returns through Common Principal Components. Mathematics, 9(9), 1011.en
dc.identifier.doihttps://doi.org/10.3390/math9091011
dc.identifier.issn2227-7390
dc.identifier.publicationfirstpage1
dc.identifier.publicationissue9
dc.identifier.publicationlastpage22
dc.identifier.publicationtitleMathematicsen
dc.identifier.publicationvolume9
dc.identifier.urihttps://hdl.handle.net/10016/34240
dc.identifier.uxxiAR/0000028643
dc.language.isoeng
dc.publisherMDPIen
dc.relation.projectIDComunidad de Madrid. V PRICIT
dc.rightsc 2021 by the authors.en
dc.rightsAtribución 3.0 España*
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subject.ecienciaEstadísticaes
dc.subject.ecienciaMatemáticasen
dc.subject.otherAsset pricingen
dc.subject.otherBootstrapen
dc.subject.otherCommon principal component analysisen
dc.subject.otherCross-sectional regressionen
dc.subject.otherFactor modelsen
dc.subject.otherTime seriesen
dc.titleHow to explain the cross-section of equity returns through common principal componentsen
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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