Analysis of new approaches used in portfolio optimization: a systematic literature review
Autor(a) principal: | |
---|---|
Data de Publicação: | 2020 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Production |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132020000100404 |
Resumo: | Abstract Paper aims To do a comprehensive review of the exact and heuristic methods, software/programming languages, constraints, and types of analysis (technical and fundamental) used to solve the portfolio optimization problem. Originality The paper presents a useful discussion on aspects of portfolio optimization, both for researchers and investors and for finance professionals. Research method A systematic literature review was performed, and the articles were compiled according to pre-established criteria/filters. Main findings A point of attention should be given to the input data of optimization models. Depending on the degree of the estimation error of these input parameters, the optimization results may be lower than the results of the 1/N trading strategy. Implications for theory and practice Robust optimization, Fuzzy logic, and prediction are examples of techniques used to reduce estimation errors. At the end of the article are pointed out trends and some gaps for future work. |
id |
ABEPRO-1_e93a2f70d9b1915a4e08e2a0bcda44db |
---|---|
oai_identifier_str |
oai:scielo:S0103-65132020000100404 |
network_acronym_str |
ABEPRO-1 |
network_name_str |
Production |
repository_id_str |
|
spelling |
Analysis of new approaches used in portfolio optimization: a systematic literature reviewPortfolio selectionHeuristicsConstraintsStock marketAbstract Paper aims To do a comprehensive review of the exact and heuristic methods, software/programming languages, constraints, and types of analysis (technical and fundamental) used to solve the portfolio optimization problem. Originality The paper presents a useful discussion on aspects of portfolio optimization, both for researchers and investors and for finance professionals. Research method A systematic literature review was performed, and the articles were compiled according to pre-established criteria/filters. Main findings A point of attention should be given to the input data of optimization models. Depending on the degree of the estimation error of these input parameters, the optimization results may be lower than the results of the 1/N trading strategy. Implications for theory and practice Robust optimization, Fuzzy logic, and prediction are examples of techniques used to reduce estimation errors. At the end of the article are pointed out trends and some gaps for future work.Associação Brasileira de Engenharia de Produção2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132020000100404Production v.30 2020reponame:Productioninstname:Associação Brasileira de Engenharia de Produção (ABEPRO)instacron:ABEPRO10.1590/0103-6513.20190144info:eu-repo/semantics/openAccessMilhomem,Danilo AlcantaraDantas,Maria José Pereiraeng2020-07-30T00:00:00Zoai:scielo:S0103-65132020000100404Revistahttps://www.scielo.br/j/prod/https://old.scielo.br/oai/scielo-oai.php||production@editoracubo.com.br1980-54110103-6513opendoar:2020-07-30T00:00Production - Associação Brasileira de Engenharia de Produção (ABEPRO)false |
dc.title.none.fl_str_mv |
Analysis of new approaches used in portfolio optimization: a systematic literature review |
title |
Analysis of new approaches used in portfolio optimization: a systematic literature review |
spellingShingle |
Analysis of new approaches used in portfolio optimization: a systematic literature review Milhomem,Danilo Alcantara Portfolio selection Heuristics Constraints Stock market |
title_short |
Analysis of new approaches used in portfolio optimization: a systematic literature review |
title_full |
Analysis of new approaches used in portfolio optimization: a systematic literature review |
title_fullStr |
Analysis of new approaches used in portfolio optimization: a systematic literature review |
title_full_unstemmed |
Analysis of new approaches used in portfolio optimization: a systematic literature review |
title_sort |
Analysis of new approaches used in portfolio optimization: a systematic literature review |
author |
Milhomem,Danilo Alcantara |
author_facet |
Milhomem,Danilo Alcantara Dantas,Maria José Pereira |
author_role |
author |
author2 |
Dantas,Maria José Pereira |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Milhomem,Danilo Alcantara Dantas,Maria José Pereira |
dc.subject.por.fl_str_mv |
Portfolio selection Heuristics Constraints Stock market |
topic |
Portfolio selection Heuristics Constraints Stock market |
description |
Abstract Paper aims To do a comprehensive review of the exact and heuristic methods, software/programming languages, constraints, and types of analysis (technical and fundamental) used to solve the portfolio optimization problem. Originality The paper presents a useful discussion on aspects of portfolio optimization, both for researchers and investors and for finance professionals. Research method A systematic literature review was performed, and the articles were compiled according to pre-established criteria/filters. Main findings A point of attention should be given to the input data of optimization models. Depending on the degree of the estimation error of these input parameters, the optimization results may be lower than the results of the 1/N trading strategy. Implications for theory and practice Robust optimization, Fuzzy logic, and prediction are examples of techniques used to reduce estimation errors. At the end of the article are pointed out trends and some gaps for future work. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132020000100404 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132020000100404 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0103-6513.20190144 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Associação Brasileira de Engenharia de Produção |
publisher.none.fl_str_mv |
Associação Brasileira de Engenharia de Produção |
dc.source.none.fl_str_mv |
Production v.30 2020 reponame:Production instname:Associação Brasileira de Engenharia de Produção (ABEPRO) instacron:ABEPRO |
instname_str |
Associação Brasileira de Engenharia de Produção (ABEPRO) |
instacron_str |
ABEPRO |
institution |
ABEPRO |
reponame_str |
Production |
collection |
Production |
repository.name.fl_str_mv |
Production - Associação Brasileira de Engenharia de Produção (ABEPRO) |
repository.mail.fl_str_mv |
||production@editoracubo.com.br |
_version_ |
1754213154547564544 |