Pump it : twitter sentiment analysis for cryptocurrency price prediction

Detalhes bibliográficos
Autor(a) principal: Koltun, Vladyslav
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.5/27662
Resumo: Mestrado Bolonha em Mathematical Finance
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spelling Pump it : twitter sentiment analysis for cryptocurrency price predictionCryptocurrencyPrice PredictionNHITSSentiment AnalysisMachine LearningMestrado Bolonha em Mathematical FinancePredicting the prices of the cryptocurrencies can be done by only using historical data related to the price,but adding ot her sources of information can be beneficial. In this work, we propose to analyse the market sentiment and add that information to the models.This sentiment was analyzed across 567 thousand tweets about 12 coins to get a daily grasp of the sentiment,polarity and subjectivity of the market.The tokens were separated into classes: established, emerging and ”meme” tokens.We trained various algorithms, such as OLS, LOGIT, LST Mand NHITS.Two periods were analysed:one corresponding to a bear market and one to a bull market. Due to the highi ntra-day volatility of cryptocurrencies, LSTM that takes longer periods into consideration did not seem to perform better than the ones without ”memory”, like OL SandL OGIT. NHITS was the best performing model accuracy wise, but lacked in returns,which we associated with our over-simplistictrading strategy.The information extracted from social media proved to be helpful across the range of models and coins. We successfully showed that ”meme” tokens do not representa viable investing strategy in our study. Thefore casting error does not increase significantly from a bear market to a bullmarket, even though the market changes drasticallyInstituto Superior de Economia e GestãoYamshchikov, IvanRepositório da Universidade de LisboaKoltun, Vladyslav2023-04-26T10:03:26Z2022-102022-10-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.5/27662engKoltun, Vladyslav (2022). “Pump it : twitter sentiment analysis for cryptocurrency price prediction”. Dissertação de Mestrado. Universidade de Lisboa. Instituto Superior de Economia e Gestãoinfo: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:RCAAP2023-04-30T01:30:51Zoai:www.repository.utl.pt:10400.5/27662Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:50:26.332781Repositório 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 Pump it : twitter sentiment analysis for cryptocurrency price prediction
title Pump it : twitter sentiment analysis for cryptocurrency price prediction
spellingShingle Pump it : twitter sentiment analysis for cryptocurrency price prediction
Koltun, Vladyslav
Cryptocurrency
Price Prediction
NHITS
Sentiment Analysis
Machine Learning
title_short Pump it : twitter sentiment analysis for cryptocurrency price prediction
title_full Pump it : twitter sentiment analysis for cryptocurrency price prediction
title_fullStr Pump it : twitter sentiment analysis for cryptocurrency price prediction
title_full_unstemmed Pump it : twitter sentiment analysis for cryptocurrency price prediction
title_sort Pump it : twitter sentiment analysis for cryptocurrency price prediction
author Koltun, Vladyslav
author_facet Koltun, Vladyslav
author_role author
dc.contributor.none.fl_str_mv Yamshchikov, Ivan
Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Koltun, Vladyslav
dc.subject.por.fl_str_mv Cryptocurrency
Price Prediction
NHITS
Sentiment Analysis
Machine Learning
topic Cryptocurrency
Price Prediction
NHITS
Sentiment Analysis
Machine Learning
description Mestrado Bolonha em Mathematical Finance
publishDate 2022
dc.date.none.fl_str_mv 2022-10
2022-10-01T00:00:00Z
2023-04-26T10:03:26Z
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/10400.5/27662
url http://hdl.handle.net/10400.5/27662
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Koltun, Vladyslav (2022). “Pump it : twitter sentiment analysis for cryptocurrency price prediction”. Dissertação de Mestrado. Universidade de Lisboa. Instituto Superior de Economia e Gestão
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.publisher.none.fl_str_mv Instituto Superior de Economia e Gestão
publisher.none.fl_str_mv Instituto Superior de Economia e Gestão
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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