Forecasting stock markets using machine learning : forecasting the PSI-20 index using a machine learning approach

Detalhes bibliográficos
Autor(a) principal: Dinis Oliveira, André
Data de Publicação: 2017
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/21452
Resumo: Project Work presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Risk Analysis and Management
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spelling Forecasting stock markets using machine learning : forecasting the PSI-20 index using a machine learning approachGenetic programmingStock marketsMachine learningGeometric semantic operatorsForecastingProject Work presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Risk Analysis and ManagementPredicting nancial markets is a task of extreme di culty. The factors that in uence stock prices are extremely complex to model. Machine Learning algorithms have been widely used to predict nancial markets with some degree of success. This Master's project aims to study the application of these algorithms to the Portuguese stock market, the PSI-20, with special emphasis on genetic programming and the introduction of the concept of semantics in the process of evolution. Three systems based on genetic programming were studied: STGP, GSGP and GSGP-LS. The construction of the predictive models is based on historical information of the index extracted through a blooberg portal. In order to analyze the quality of the models based on genetic programming, the nal results were compared with other Machine Learning algorithms through the application of signi cance statistical tests. An analysis of the quality of the results of the di erent algorithms is presented and discussed.Castelli, MauroRUNDinis Oliveira, André2017-06-06T13:55:55Z2017-05-302017-05-30T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/21452TID:201702312enginfo: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:RCAAP2024-03-11T04:08:07Zoai:run.unl.pt:10362/21452Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:26:47.779454Repositório 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 Forecasting stock markets using machine learning : forecasting the PSI-20 index using a machine learning approach
title Forecasting stock markets using machine learning : forecasting the PSI-20 index using a machine learning approach
spellingShingle Forecasting stock markets using machine learning : forecasting the PSI-20 index using a machine learning approach
Dinis Oliveira, André
Genetic programming
Stock markets
Machine learning
Geometric semantic operators
Forecasting
title_short Forecasting stock markets using machine learning : forecasting the PSI-20 index using a machine learning approach
title_full Forecasting stock markets using machine learning : forecasting the PSI-20 index using a machine learning approach
title_fullStr Forecasting stock markets using machine learning : forecasting the PSI-20 index using a machine learning approach
title_full_unstemmed Forecasting stock markets using machine learning : forecasting the PSI-20 index using a machine learning approach
title_sort Forecasting stock markets using machine learning : forecasting the PSI-20 index using a machine learning approach
author Dinis Oliveira, André
author_facet Dinis Oliveira, André
author_role author
dc.contributor.none.fl_str_mv Castelli, Mauro
RUN
dc.contributor.author.fl_str_mv Dinis Oliveira, André
dc.subject.por.fl_str_mv Genetic programming
Stock markets
Machine learning
Geometric semantic operators
Forecasting
topic Genetic programming
Stock markets
Machine learning
Geometric semantic operators
Forecasting
description Project Work presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Risk Analysis and Management
publishDate 2017
dc.date.none.fl_str_mv 2017-06-06T13:55:55Z
2017-05-30
2017-05-30T00:00:00Z
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/10362/21452
TID:201702312
url http://hdl.handle.net/10362/21452
identifier_str_mv TID:201702312
dc.language.iso.fl_str_mv eng
language eng
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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
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repository.mail.fl_str_mv
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