Reconstructing cryptocurrency processes via Markov chains
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.5/27351 |
Resumo: | The growing attention on cryptocurrencies has led to increasing research on digital stock markets. Approaches and tools usually applied to characterize standard stocks have been applied to the digital ones. Among these tools is the identification of processes of market fluctuations. Being interesting stochastic processes, the usual statistical methods are appropriate tools to their reconstruction. There, besides chance, the description of a behavioural component shall be present whenever a determinist pattern is ever found. Markov approaches are at the leading edge of this endeavour. In this paper, Markov chains of orders one to eight are considered as a way to forecast the dynamics of three major cryptocurrencies. It is accomplished using an empirical basis of intra-day returns. Besides forecasting, we investigate the existence of eventual long-memory components in each of those stochastic process. Results show that the average predictions obtained from using the empirical probabilities is better than random choices. |
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Reconstructing cryptocurrency processes via Markov chainsMarkov chainsCriptocurrencyForecastingMarket ProcessesThe growing attention on cryptocurrencies has led to increasing research on digital stock markets. Approaches and tools usually applied to characterize standard stocks have been applied to the digital ones. Among these tools is the identification of processes of market fluctuations. Being interesting stochastic processes, the usual statistical methods are appropriate tools to their reconstruction. There, besides chance, the description of a behavioural component shall be present whenever a determinist pattern is ever found. Markov approaches are at the leading edge of this endeavour. In this paper, Markov chains of orders one to eight are considered as a way to forecast the dynamics of three major cryptocurrencies. It is accomplished using an empirical basis of intra-day returns. Besides forecasting, we investigate the existence of eventual long-memory components in each of those stochastic process. Results show that the average predictions obtained from using the empirical probabilities is better than random choices.ISEG - REM - Research in Economics and MathematicsRepositório da Universidade de LisboaAraújo, TanyaBarbosa, Paulo2023-02-27T10:19:09Z2023-022023-02-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/27351engAraújo, Tanya e Paulo Barbosa (2023). "Reconstructing cryptocurrency processes via Markov chains". REM Working paper series, nº 0262/20232184-108Xinfo: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:RCAAP2023-03-06T14:56:42Zoai:www.repository.utl.pt:10400.5/27351Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:10:50.038003Repositório 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 |
Reconstructing cryptocurrency processes via Markov chains |
title |
Reconstructing cryptocurrency processes via Markov chains |
spellingShingle |
Reconstructing cryptocurrency processes via Markov chains Araújo, Tanya Markov chains Criptocurrency Forecasting Market Processes |
title_short |
Reconstructing cryptocurrency processes via Markov chains |
title_full |
Reconstructing cryptocurrency processes via Markov chains |
title_fullStr |
Reconstructing cryptocurrency processes via Markov chains |
title_full_unstemmed |
Reconstructing cryptocurrency processes via Markov chains |
title_sort |
Reconstructing cryptocurrency processes via Markov chains |
author |
Araújo, Tanya |
author_facet |
Araújo, Tanya Barbosa, Paulo |
author_role |
author |
author2 |
Barbosa, Paulo |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Repositório da Universidade de Lisboa |
dc.contributor.author.fl_str_mv |
Araújo, Tanya Barbosa, Paulo |
dc.subject.por.fl_str_mv |
Markov chains Criptocurrency Forecasting Market Processes |
topic |
Markov chains Criptocurrency Forecasting Market Processes |
description |
The growing attention on cryptocurrencies has led to increasing research on digital stock markets. Approaches and tools usually applied to characterize standard stocks have been applied to the digital ones. Among these tools is the identification of processes of market fluctuations. Being interesting stochastic processes, the usual statistical methods are appropriate tools to their reconstruction. There, besides chance, the description of a behavioural component shall be present whenever a determinist pattern is ever found. Markov approaches are at the leading edge of this endeavour. In this paper, Markov chains of orders one to eight are considered as a way to forecast the dynamics of three major cryptocurrencies. It is accomplished using an empirical basis of intra-day returns. Besides forecasting, we investigate the existence of eventual long-memory components in each of those stochastic process. Results show that the average predictions obtained from using the empirical probabilities is better than random choices. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-02-27T10:19:09Z 2023-02 2023-02-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.5/27351 |
url |
http://hdl.handle.net/10400.5/27351 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Araújo, Tanya e Paulo Barbosa (2023). "Reconstructing cryptocurrency processes via Markov chains". REM Working paper series, nº 0262/2023 2184-108X |
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 |
ISEG - REM - Research in Economics and Mathematics |
publisher.none.fl_str_mv |
ISEG - REM - Research in Economics and Mathematics |
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 |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
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 |
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1799131205877104640 |