Using image recognition for trading

Detalhes bibliográficos
Autor(a) principal: Günes, Berkay
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/10362/122788
Resumo: This research aims to gain a deeper understanding of how image recognition can be applied in trading. In recent years, artificial intelligence has influenced various industries, including the financial sector. It can be observed that there are new ways of predicting stock trends. This paper aims to address the question to what extend convolutional neural networks can be used in trading. On the empirical side several convolutional neural networks have been analyzed and were compared with a zero-predictive model. This study’s results do not show reliable results that convolutional neural networks should be used for this sort of task.
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spelling Using image recognition for tradingConvolutional neural networksImage recognitionFinanceTradingDomínio/Área Científica::Ciências Sociais::Economia e GestãoThis research aims to gain a deeper understanding of how image recognition can be applied in trading. In recent years, artificial intelligence has influenced various industries, including the financial sector. It can be observed that there are new ways of predicting stock trends. This paper aims to address the question to what extend convolutional neural networks can be used in trading. On the empirical side several convolutional neural networks have been analyzed and were compared with a zero-predictive model. This study’s results do not show reliable results that convolutional neural networks should be used for this sort of task.Xufre, PatriciaRUNGünes, Berkay2021-08-20T09:32:57Z2021-01-192021-01-042021-01-19T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/122788TID:202741613enginfo: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:RCAAP2024-03-11T05:04:18Zoai:run.unl.pt:10362/122788Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:44:51.207836Repositório 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 Using image recognition for trading
title Using image recognition for trading
spellingShingle Using image recognition for trading
Günes, Berkay
Convolutional neural networks
Image recognition
Finance
Trading
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
title_short Using image recognition for trading
title_full Using image recognition for trading
title_fullStr Using image recognition for trading
title_full_unstemmed Using image recognition for trading
title_sort Using image recognition for trading
author Günes, Berkay
author_facet Günes, Berkay
author_role author
dc.contributor.none.fl_str_mv Xufre, Patricia
RUN
dc.contributor.author.fl_str_mv Günes, Berkay
dc.subject.por.fl_str_mv Convolutional neural networks
Image recognition
Finance
Trading
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
topic Convolutional neural networks
Image recognition
Finance
Trading
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
description This research aims to gain a deeper understanding of how image recognition can be applied in trading. In recent years, artificial intelligence has influenced various industries, including the financial sector. It can be observed that there are new ways of predicting stock trends. This paper aims to address the question to what extend convolutional neural networks can be used in trading. On the empirical side several convolutional neural networks have been analyzed and were compared with a zero-predictive model. This study’s results do not show reliable results that convolutional neural networks should be used for this sort of task.
publishDate 2021
dc.date.none.fl_str_mv 2021-08-20T09:32:57Z
2021-01-19
2021-01-04
2021-01-19T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/122788
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dc.language.iso.fl_str_mv eng
language eng
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eu_rights_str_mv openAccess
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dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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