Cryptocurrency portfolio optimization using genetic algorithms

Detalhes bibliográficos
Autor(a) principal: Sousa, Maikel Ricardo Pereira de
Data de Publicação: 2023
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/149181
Resumo: Project Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
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spelling Cryptocurrency portfolio optimization using genetic algorithmsBlockchainProject Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceBlockchain most discussed application has been in cryptocurrency, being Bitcoin its first. Unbeknownst to many, Bitcoin not only introduced a new digital means of exchange creating fertile ground for others trying to emulate it. Cryptocurrencies took relevance beyond computer science spheres to reach a place of relevance as a security for several investors, making it relevant to study beyond computer science spheres. Economists, statisticians, and portfolio managers, have taken the subject of cryptocurrencies as case study for open digital finance, opening questions regarding price behaviors and objective investment strategies, creating opportunities of research on fields such as machine learning. Nevertheless, each cryptocurrency has its technicalities, and different value proposals, making the subject relatable, in some sense, to traditional financial instruments, from which some lessons can be of use, for example, how it is difficult to come up with a unique approach or toolset that forecasts prices and optimizes investments, at least in a general sense. Here the objective is to tackle a cryptocurrency portfolio optimization by means of genetic algorithms. Two approaches are suggested, the first Limited Trading approach, consists on using genetic algorithms to find how much of the coins to invest for profit considering to sell at the last day. Second approach is called Open Trading, much like the first, intends to find profit but it allows buying and selling at each timestep. In both cases respecting budgeting limitations and using forecast price values of each coin, but for this, instead of delving into the complexities of thousands of possible coins and algorithms, it was used a combination of machine learning methods to forecast prices of the coins in the portfolio. It was found that Limited trading outperforms its counterpart in fitness (expected portfolio value) and %Return. It was also found a genetic algorithm parametrization successful for both strategies, and highlighting the value of the theoretical proposal for fitness optimization based on matrix operations for Open Trading, which has room for improvement and further development in fields beyond portfolio optimization.Vanneschi, LeonardoRUNSousa, Maikel Ricardo Pereira de2023-02-14T17:58:43Z2023-01-252023-01-25T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/149181TID:203227573enginfo: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:RCAAP2024-03-11T05:30:59Zoai:run.unl.pt:10362/149181Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:53:39.126416Repositório 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 Cryptocurrency portfolio optimization using genetic algorithms
title Cryptocurrency portfolio optimization using genetic algorithms
spellingShingle Cryptocurrency portfolio optimization using genetic algorithms
Sousa, Maikel Ricardo Pereira de
Blockchain
title_short Cryptocurrency portfolio optimization using genetic algorithms
title_full Cryptocurrency portfolio optimization using genetic algorithms
title_fullStr Cryptocurrency portfolio optimization using genetic algorithms
title_full_unstemmed Cryptocurrency portfolio optimization using genetic algorithms
title_sort Cryptocurrency portfolio optimization using genetic algorithms
author Sousa, Maikel Ricardo Pereira de
author_facet Sousa, Maikel Ricardo Pereira de
author_role author
dc.contributor.none.fl_str_mv Vanneschi, Leonardo
RUN
dc.contributor.author.fl_str_mv Sousa, Maikel Ricardo Pereira de
dc.subject.por.fl_str_mv Blockchain
topic Blockchain
description Project Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
publishDate 2023
dc.date.none.fl_str_mv 2023-02-14T17:58:43Z
2023-01-25
2023-01-25T00:00:00Z
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/10362/149181
TID:203227573
url http://hdl.handle.net/10362/149181
identifier_str_mv TID:203227573
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
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