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K-means clustering approach for stock risk assessment and portfolio construction: a case study based on the EU-EV risk model

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Resumo:The purpose of this work is to explore the approach of K-means clustering for stock risk classification and efficient portfolio construction through a case study, using data from the PSI index from January 2019 to December 2022. The classification of stock risks will be based on the expected utility, entropy and variance (EU-EV) risk model. The methodology consists in ap-plying K-means clustering with EU-EV risk related attributes to the stocks of the Portuguese PSI index in order to obtain two classes of stocks categorized with low and with high risk. Equally weighted cluster based portfolios are built for each risk class. The performance of these portfolios will be com-pared with the performance of portfolios constructed by selection of the best EU-EV risk ranked stocks.
Autores principais:Brito, Irene
Outros Autores:Machado, Gaspar J.
Assunto:K-means Clustering Risk Classification EU-EV risk Stock Selection Portfolio Construction
Ano:2024
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
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author Brito, Irene
author2 Machado, Gaspar J.
author2_role author
author_facet Brito, Irene
Machado, Gaspar J.
author_role author
contributor_name_str_mv Universidade do Minho
country_str PT
creators_json_txt [{\"Person.name\":\"Brito, Irene\"},{\"Person.name\":\"Machado, Gaspar J.\"}]
datacite.contributors.contributor.contributorName.fl_str_mv Universidade do Minho
datacite.creators.creator.creatorName.fl_str_mv Brito, Irene
Machado, Gaspar J.
datacite.date.Accepted.fl_str_mv 2024-01-01T00:00:00Z
datacite.date.available.fl_str_mv 2024-10-29T16:59:05Z
datacite.date.embargoed.fl_str_mv 2024-10-29T16:59:05Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv K-means Clustering
Risk Classification
EU-EV risk
Stock Selection
Portfolio Construction
datacite.titles.title.fl_str_mv K-means clustering approach for stock risk assessment and portfolio construction: a case study based on the EU-EV risk model
dc.contributor.none.fl_str_mv Universidade do Minho
dc.creator.none.fl_str_mv Brito, Irene
Machado, Gaspar J.
dc.date.Accepted.fl_str_mv 2024-01-01T00:00:00Z
dc.date.available.fl_str_mv 2024-10-29T16:59:05Z
dc.date.embargoed.fl_str_mv 2024-10-29T16:59:05Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv https://hdl.handle.net/1822/93540
dc.language.none.fl_str_mv eng
dc.publisher.none.fl_str_mv Springer, Cham
dc.rights.cclincense.fl_str_mv http://creativecommons.org/licenses/by/4.0/
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.rights.copyright.fl_str_mv openAccess
dc.subject.none.fl_str_mv K-means Clustering
Risk Classification
EU-EV risk
Stock Selection
Portfolio Construction
dc.title.fl_str_mv K-means clustering approach for stock risk assessment and portfolio construction: a case study based on the EU-EV risk model
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_5794
description The purpose of this work is to explore the approach of K-means clustering for stock risk classification and efficient portfolio construction through a case study, using data from the PSI index from January 2019 to December 2022. The classification of stock risks will be based on the expected utility, entropy and variance (EU-EV) risk model. The methodology consists in ap-plying K-means clustering with EU-EV risk related attributes to the stocks of the Portuguese PSI index in order to obtain two classes of stocks categorized with low and with high risk. Equally weighted cluster based portfolios are built for each risk class. The performance of these portfolios will be com-pared with the performance of portfolios constructed by selection of the best EU-EV risk ranked stocks.
dirty 0
eu_rights_str_mv openAccess
format conferencePaper
fulltext.url.fl_str_mv https://prod-dspace.uminho.pt/bitstreams/02a4d051-d768-4685-9275-9608ca8466aa/download
id rum_571981c8e2c6ef91dba2861a6ccb2db2
identifier.url.fl_str_mv https://hdl.handle.net/1822/93540
instacron_str repositorium
institution Universidade do Minho
instname_str Universidade do Minho
language eng
network_acronym_str rum
network_name_str RepositóriUM - Universidade do Minho
oai_identifier_str oai:repositorium.uminho.pt:1822/93540
organization_str_mv urn:organizationAcronym:repositorium
person_str_mv Brito, Irene
Machado, Gaspar J.
publishDate 2024
publisher.none.fl_str_mv Springer, Cham
reponame_str RepositóriUM - Universidade do Minho
repository_id_str urn:repositoryAcronym:rum
service_str_mv urn:repositoryAcronym:rum
spelling engSpringer, ChamporThe purpose of this work is to explore the approach of K-means clustering for stock risk classification and efficient portfolio construction through a case study, using data from the PSI index from January 2019 to December 2022. The classification of stock risks will be based on the expected utility, entropy and variance (EU-EV) risk model. The methodology consists in ap-plying K-means clustering with EU-EV risk related attributes to the stocks of the Portuguese PSI index in order to obtain two classes of stocks categorized with low and with high risk. Equally weighted cluster based portfolios are built for each risk class. The performance of these portfolios will be com-pared with the performance of portfolios constructed by selection of the best EU-EV risk ranked stocks.application/pdfporK-means clustering approach for stock risk assessment and portfolio construction: a case study based on the EU-EV risk modelBrito, IreneMachado, Gaspar J.HostingInstitutionOrganizationalUniversidade do Minhoe-mailmailto:repositorium@usdb.uminho.ptrepositorium@usdb.uminho.ptISBNIsPartOf978-3-031-60270-2ISSNIsPartOf2366-2557DOIIsPartOf10.1007/978-3-031-60271-9_162024-10-29T16:59:05Z20242024-01-01T00:00:00ZHandlehttps://hdl.handle.net/1822/93540http://purl.org/coar/access_right/c_abf2open accessK-means ClusteringRisk ClassificationEU-EV riskStock SelectionPortfolio Construction454193 bytesother research producthttp://purl.org/coar/resource_type/c_5794conference paper2024http://creativecommons.org/licenses/by/4.0/openAccesshttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://prod-dspace.uminho.pt/bitstreams/02a4d051-d768-4685-9275-9608ca8466aa/download
spellingShingle K-means clustering approach for stock risk assessment and portfolio construction: a case study based on the EU-EV risk model
Brito, Irene
K-means Clustering
Risk Classification
EU-EV risk
Stock Selection
Portfolio Construction
status SINGLETON
subject.fl_str_mv K-means Clustering
Risk Classification
EU-EV risk
Stock Selection
Portfolio Construction
title K-means clustering approach for stock risk assessment and portfolio construction: a case study based on the EU-EV risk model
title_full K-means clustering approach for stock risk assessment and portfolio construction: a case study based on the EU-EV risk model
title_fullStr K-means clustering approach for stock risk assessment and portfolio construction: a case study based on the EU-EV risk model
title_full_unstemmed K-means clustering approach for stock risk assessment and portfolio construction: a case study based on the EU-EV risk model
title_short K-means clustering approach for stock risk assessment and portfolio construction: a case study based on the EU-EV risk model
title_sort K-means clustering approach for stock risk assessment and portfolio construction: a case study based on the EU-EV risk model
topic K-means Clustering
Risk Classification
EU-EV risk
Stock Selection
Portfolio Construction
topic_facet K-means Clustering
Risk Classification
EU-EV risk
Stock Selection
Portfolio Construction
url https://hdl.handle.net/1822/93540
visible 1