A machine learning algorithm applied to macroeconomic factor investing

Detalhes bibliográficos
Autor(a) principal: Simões, Ana Bárbara Moura Da Luz Delgado
Data de Publicação: 2021
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/144695
Resumo: This paper examines the extent to which macroeconomic indicators can be used to determine the optimal allocation of an extended Fama French 5-Factor model which includes the risk-free rate. The study is based on Modern Portfolio Theory (MPT) as developed by Markowitz(1952) and Smart Beta Investing. The algorithm combines MPT with two Machine Learning (ML) Algorithms (K-means Clustering and Random Forest) to predict the macroeconomic state and arrive at the according optimal ‘tactical’ portfolio allocation of each security over the investment period. The research contributes to the existing literature of ML Algorithm performance applied to Smart Beta macroeconomic strategies.
id RCAP_3b10cbb524e9c4f898e3522ee76e7737
oai_identifier_str oai:run.unl.pt:10362/144695
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling A machine learning algorithm applied to macroeconomic factor investingCorporate financePrivate equityDomínio/Área Científica::Ciências Sociais::Economia e GestãoThis paper examines the extent to which macroeconomic indicators can be used to determine the optimal allocation of an extended Fama French 5-Factor model which includes the risk-free rate. The study is based on Modern Portfolio Theory (MPT) as developed by Markowitz(1952) and Smart Beta Investing. The algorithm combines MPT with two Machine Learning (ML) Algorithms (K-means Clustering and Random Forest) to predict the macroeconomic state and arrive at the according optimal ‘tactical’ portfolio allocation of each security over the investment period. The research contributes to the existing literature of ML Algorithm performance applied to Smart Beta macroeconomic strategies.Ribeiro, Gonçalo SommerAnjos, FernandoRUNSimões, Ana Bárbara Moura Da Luz Delgado2022-10-14T09:53:43Z2022-04-052021-12-172022-04-05T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/144695TID:203064828enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:24:31Zoai:run.unl.pt:10362/144695Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:51:42.053097Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv A machine learning algorithm applied to macroeconomic factor investing
title A machine learning algorithm applied to macroeconomic factor investing
spellingShingle A machine learning algorithm applied to macroeconomic factor investing
Simões, Ana Bárbara Moura Da Luz Delgado
Corporate finance
Private equity
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
title_short A machine learning algorithm applied to macroeconomic factor investing
title_full A machine learning algorithm applied to macroeconomic factor investing
title_fullStr A machine learning algorithm applied to macroeconomic factor investing
title_full_unstemmed A machine learning algorithm applied to macroeconomic factor investing
title_sort A machine learning algorithm applied to macroeconomic factor investing
author Simões, Ana Bárbara Moura Da Luz Delgado
author_facet Simões, Ana Bárbara Moura Da Luz Delgado
author_role author
dc.contributor.none.fl_str_mv Ribeiro, Gonçalo Sommer
Anjos, Fernando
RUN
dc.contributor.author.fl_str_mv Simões, Ana Bárbara Moura Da Luz Delgado
dc.subject.por.fl_str_mv Corporate finance
Private equity
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
topic Corporate finance
Private equity
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
description This paper examines the extent to which macroeconomic indicators can be used to determine the optimal allocation of an extended Fama French 5-Factor model which includes the risk-free rate. The study is based on Modern Portfolio Theory (MPT) as developed by Markowitz(1952) and Smart Beta Investing. The algorithm combines MPT with two Machine Learning (ML) Algorithms (K-means Clustering and Random Forest) to predict the macroeconomic state and arrive at the according optimal ‘tactical’ portfolio allocation of each security over the investment period. The research contributes to the existing literature of ML Algorithm performance applied to Smart Beta macroeconomic strategies.
publishDate 2021
dc.date.none.fl_str_mv 2021-12-17
2022-10-14T09:53:43Z
2022-04-05
2022-04-05T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/144695
TID:203064828
url http://hdl.handle.net/10362/144695
identifier_str_mv TID:203064828
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
_version_ 1799138109865066496