Portfolio choice under local industry and country factors

This article extends the parametric portfolio policy approach to optimizing portfolios with a large numbers of assets (Brandt et al. 2009). The proposed approach incorporates unobserved effects into the portfolio policy function. These effects measure the importance of unobserved heterogeneity for e...

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Tipo de recurso:
Fecha de publicación:
2010
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/24060
Acceso en línea:
https://doi.org/10.1007/s11408-010-0143-9
https://repository.urosario.edu.co/handle/10336/24060
Palabra clave:
Industry and country factors
Multifactor asset pricing models
Portfolio choice
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repository_id_str
spelling 799479176002020-05-26T00:08:09Z2020-05-26T00:08:09Z2010This article extends the parametric portfolio policy approach to optimizing portfolios with a large numbers of assets (Brandt et al. 2009). The proposed approach incorporates unobserved effects into the portfolio policy function. These effects measure the importance of unobserved heterogeneity for exploiting the difference between groups of assets. The source of the heterogeneity is local priced factors, such as industry or country. The statistical model allows testing the importance of such local factors in portfolio optimization. The results suggest that local effects or return heterogeneity associated with economic sectors or geographic factors is not as straightforward to exploit financially or as relevant as suggested by the extensive multivariate factor literature on the subject. Furthermore, trying to exploit industry effects rarely provides a gain over simple benchmarks, neither in-sample nor more importantly, out-of-sample. On the other hand, exploiting country effects does provide gains over the benchmark. However, these gains may be offset by the increasing cost of and risk inherent in such strategies. Finally, exploiting size, momentum, and liquidity anomalies in the cross-section of stocks provides strictly greater returns than the industry and country effects. © 2010 Swiss Society for Financial Market Research.application/pdfhttps://doi.org/10.1007/s11408-010-0143-91555497X15554961https://repository.urosario.edu.co/handle/10336/24060eng393No. 4353Financial Markets and Portfolio ManagementVol. 24Financial Markets and Portfolio Management, ISSN:1555497X, 15554961, Vol.24, No.4 (2010); pp. 353-393https://www.scopus.com/inward/record.uri?eid=2-s2.0-78449253227&doi=10.1007%2fs11408-010-0143-9&partnerID=40&md5=1b604c11d828d8711ecabecb45f3a260Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURIndustry and country factorsMultifactor asset pricing modelsPortfolio choicePortfolio choice under local industry and country factorsarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Castro, Carlos10336/24060oai:repository.urosario.edu.co:10336/240602021-06-10 22:40:49.244https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co
dc.title.spa.fl_str_mv Portfolio choice under local industry and country factors
title Portfolio choice under local industry and country factors
spellingShingle Portfolio choice under local industry and country factors
Industry and country factors
Multifactor asset pricing models
Portfolio choice
title_short Portfolio choice under local industry and country factors
title_full Portfolio choice under local industry and country factors
title_fullStr Portfolio choice under local industry and country factors
title_full_unstemmed Portfolio choice under local industry and country factors
title_sort Portfolio choice under local industry and country factors
dc.subject.keyword.spa.fl_str_mv Industry and country factors
Multifactor asset pricing models
Portfolio choice
topic Industry and country factors
Multifactor asset pricing models
Portfolio choice
description This article extends the parametric portfolio policy approach to optimizing portfolios with a large numbers of assets (Brandt et al. 2009). The proposed approach incorporates unobserved effects into the portfolio policy function. These effects measure the importance of unobserved heterogeneity for exploiting the difference between groups of assets. The source of the heterogeneity is local priced factors, such as industry or country. The statistical model allows testing the importance of such local factors in portfolio optimization. The results suggest that local effects or return heterogeneity associated with economic sectors or geographic factors is not as straightforward to exploit financially or as relevant as suggested by the extensive multivariate factor literature on the subject. Furthermore, trying to exploit industry effects rarely provides a gain over simple benchmarks, neither in-sample nor more importantly, out-of-sample. On the other hand, exploiting country effects does provide gains over the benchmark. However, these gains may be offset by the increasing cost of and risk inherent in such strategies. Finally, exploiting size, momentum, and liquidity anomalies in the cross-section of stocks provides strictly greater returns than the industry and country effects. © 2010 Swiss Society for Financial Market Research.
publishDate 2010
dc.date.created.spa.fl_str_mv 2010
dc.date.accessioned.none.fl_str_mv 2020-05-26T00:08:09Z
dc.date.available.none.fl_str_mv 2020-05-26T00:08:09Z
dc.type.eng.fl_str_mv article
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.spa.spa.fl_str_mv Artículo
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1007/s11408-010-0143-9
dc.identifier.issn.none.fl_str_mv 1555497X
15554961
dc.identifier.uri.none.fl_str_mv https://repository.urosario.edu.co/handle/10336/24060
url https://doi.org/10.1007/s11408-010-0143-9
https://repository.urosario.edu.co/handle/10336/24060
identifier_str_mv 1555497X
15554961
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.citationEndPage.none.fl_str_mv 393
dc.relation.citationIssue.none.fl_str_mv No. 4
dc.relation.citationStartPage.none.fl_str_mv 353
dc.relation.citationTitle.none.fl_str_mv Financial Markets and Portfolio Management
dc.relation.citationVolume.none.fl_str_mv Vol. 24
dc.relation.ispartof.spa.fl_str_mv Financial Markets and Portfolio Management, ISSN:1555497X, 15554961, Vol.24, No.4 (2010); pp. 353-393
dc.relation.uri.spa.fl_str_mv https://www.scopus.com/inward/record.uri?eid=2-s2.0-78449253227&doi=10.1007%2fs11408-010-0143-9&partnerID=40&md5=1b604c11d828d8711ecabecb45f3a260
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.acceso.spa.fl_str_mv Abierto (Texto Completo)
rights_invalid_str_mv Abierto (Texto Completo)
http://purl.org/coar/access_right/c_abf2
dc.format.mimetype.none.fl_str_mv application/pdf
institution Universidad del Rosario
dc.source.instname.spa.fl_str_mv instname:Universidad del Rosario
dc.source.reponame.spa.fl_str_mv reponame:Repositorio Institucional EdocUR
repository.name.fl_str_mv Repositorio institucional EdocUR
repository.mail.fl_str_mv edocur@urosario.edu.co
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