Analysis of the Tick Rule and Bulk Volume Classification Algorithms in the Brazilian Stock Market

Detalhes bibliográficos
Autor(a) principal: Siqueira, Leonardo
Data de Publicação: 2022
Outros Autores: Correia, Laíse, Amaral, Hudson
Tipo de documento: Artigo
Idioma: eng
por
Título da fonte: BBR. Brazilian Business Review (English edition. Online)
Texto Completo: http://www.bbronline.com.br/index.php/bbr/article/view/733
Resumo: This study aimed to compare the performance of Tick Rule (TR) and Bulk Volume Classification (BVC) models in classifying assets traded on the Brazilian stock exchange (B3) and indicate which one performs better as an investment decision tool. The assets were split into three groups based on their volume, and actual data was used to assess the accuracy of both algorithms. Data from 2018 was used to estimate the parameters that best fit BVC, and transactions from 2019 were used to test the algorithm’s efficiency. Afterward, the Volume-Synchronized Probability of Informed Trading (VPIN) was calculated for each asset using TR and BVC, and the values obtained were compared against VPIN calculated using real data. In conclusion, the TR algorithm shows betters performance than BVC for all three groups of assets. Analysis of the properties of both methods reveals that the base upon which the TR is built holds up in the Brazilian market, whereas BVC mechanics does not reflect the observed reality
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spelling Analysis of the Tick Rule and Bulk Volume Classification Algorithms in the Brazilian Stock MarketAnálise dos Algoritmos Tick Rule e Bulk Volume Classification no Mercado Acionário BrasileiroTick RuleBulk Volume ClassificationVPINMarket microstructureTick RuleBulk Volume ClassificationVPINMicroestrutura de mercadoThis study aimed to compare the performance of Tick Rule (TR) and Bulk Volume Classification (BVC) models in classifying assets traded on the Brazilian stock exchange (B3) and indicate which one performs better as an investment decision tool. The assets were split into three groups based on their volume, and actual data was used to assess the accuracy of both algorithms. Data from 2018 was used to estimate the parameters that best fit BVC, and transactions from 2019 were used to test the algorithm’s efficiency. Afterward, the Volume-Synchronized Probability of Informed Trading (VPIN) was calculated for each asset using TR and BVC, and the values obtained were compared against VPIN calculated using real data. In conclusion, the TR algorithm shows betters performance than BVC for all three groups of assets. Analysis of the properties of both methods reveals that the base upon which the TR is built holds up in the Brazilian market, whereas BVC mechanics does not reflect the observed realityO objetivo deste artigo foi comparar o desempenho dos algoritmos Tick Rule (TR) e Bulk Volume Classification (BVC) na classificação de transações de ações negociadas na B3 e, assim, indicar o melhor método como ferramenta de auxílio às decisões de investimento. Os ativos foram separados em três grupos conforme o volume transacionado. Os dados reais foram utilizados para verificar a acurácia dos algoritmos, sendo as informações de 2018 utilizadas para estimar os melhores parâmetros do BVC, e as de 2019, para testar a sua eficiência. Posteriormente, foi calculado o Volume-Synchronized Probability of Informed Trading (VPIN) para cada ação utilizando o TR e o BVC. Esses valores foram comparados com o VPIN apurado com os dados reais. Observou-se que o TR apresenta melhor performance em relação ao BVC para todos os três grupos de ações. As análises das propriedades dos métodos revelaram que a base na qual o TR está calcado se sustenta no mercado brasileiro, enquanto a mecânica do BVC não reflete a realidade.FUCAPE Business Shool2022-11-18info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer-reviewed ArticleArtigo revisado pelos paresapplication/pdfapplication/pdfhttp://www.bbronline.com.br/index.php/bbr/article/view/73310.15728/bbr.2023.20.1.6.enBrazilian Business Review; Vol. 20 No. 1 (2023): January to February 2023; 99-116Brazilian Business Review; v. 20 n. 1 (2023): Janeiro a Fevereiro de 2023; 99-1161808-23861807-734Xreponame:BBR. Brazilian Business Review (English edition. Online)instname:Fucape Business School (FBS)instacron:FBSengporhttp://www.bbronline.com.br/index.php/bbr/article/view/733/1103http://www.bbronline.com.br/index.php/bbr/article/view/733/1104Copyright (c) 2022 Brazilian Business Reviewhttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSiqueira, LeonardoCorreia, LaíseAmaral, Hudson2023-01-01T11:34:22Zoai:ojs.pkp.sfu.ca:article/733Revistahttps://www.bbronline.com.br/index.php/bbr/indexONGhttp://www.bbronline.com.br/index.php/bbr/oai|| bbronline@bbronline.com.br1808-23861808-2386opendoar:2023-01-01T11:34:22BBR. Brazilian Business Review (English edition. Online) - Fucape Business School (FBS)false
dc.title.none.fl_str_mv Analysis of the Tick Rule and Bulk Volume Classification Algorithms in the Brazilian Stock Market
Análise dos Algoritmos Tick Rule e Bulk Volume Classification no Mercado Acionário Brasileiro
title Analysis of the Tick Rule and Bulk Volume Classification Algorithms in the Brazilian Stock Market
spellingShingle Analysis of the Tick Rule and Bulk Volume Classification Algorithms in the Brazilian Stock Market
Siqueira, Leonardo
Tick Rule
Bulk Volume Classification
VPIN
Market microstructure
Tick Rule
Bulk Volume Classification
VPIN
Microestrutura de mercado
title_short Analysis of the Tick Rule and Bulk Volume Classification Algorithms in the Brazilian Stock Market
title_full Analysis of the Tick Rule and Bulk Volume Classification Algorithms in the Brazilian Stock Market
title_fullStr Analysis of the Tick Rule and Bulk Volume Classification Algorithms in the Brazilian Stock Market
title_full_unstemmed Analysis of the Tick Rule and Bulk Volume Classification Algorithms in the Brazilian Stock Market
title_sort Analysis of the Tick Rule and Bulk Volume Classification Algorithms in the Brazilian Stock Market
author Siqueira, Leonardo
author_facet Siqueira, Leonardo
Correia, Laíse
Amaral, Hudson
author_role author
author2 Correia, Laíse
Amaral, Hudson
author2_role author
author
dc.contributor.author.fl_str_mv Siqueira, Leonardo
Correia, Laíse
Amaral, Hudson
dc.subject.por.fl_str_mv Tick Rule
Bulk Volume Classification
VPIN
Market microstructure
Tick Rule
Bulk Volume Classification
VPIN
Microestrutura de mercado
topic Tick Rule
Bulk Volume Classification
VPIN
Market microstructure
Tick Rule
Bulk Volume Classification
VPIN
Microestrutura de mercado
description This study aimed to compare the performance of Tick Rule (TR) and Bulk Volume Classification (BVC) models in classifying assets traded on the Brazilian stock exchange (B3) and indicate which one performs better as an investment decision tool. The assets were split into three groups based on their volume, and actual data was used to assess the accuracy of both algorithms. Data from 2018 was used to estimate the parameters that best fit BVC, and transactions from 2019 were used to test the algorithm’s efficiency. Afterward, the Volume-Synchronized Probability of Informed Trading (VPIN) was calculated for each asset using TR and BVC, and the values obtained were compared against VPIN calculated using real data. In conclusion, the TR algorithm shows betters performance than BVC for all three groups of assets. Analysis of the properties of both methods reveals that the base upon which the TR is built holds up in the Brazilian market, whereas BVC mechanics does not reflect the observed reality
publishDate 2022
dc.date.none.fl_str_mv 2022-11-18
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Artigo revisado pelos pares
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.bbronline.com.br/index.php/bbr/article/view/733
10.15728/bbr.2023.20.1.6.en
url http://www.bbronline.com.br/index.php/bbr/article/view/733
identifier_str_mv 10.15728/bbr.2023.20.1.6.en
dc.language.iso.fl_str_mv eng
por
language eng
por
dc.relation.none.fl_str_mv http://www.bbronline.com.br/index.php/bbr/article/view/733/1103
http://www.bbronline.com.br/index.php/bbr/article/view/733/1104
dc.rights.driver.fl_str_mv Copyright (c) 2022 Brazilian Business Review
http://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2022 Brazilian Business Review
http://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv FUCAPE Business Shool
publisher.none.fl_str_mv FUCAPE Business Shool
dc.source.none.fl_str_mv Brazilian Business Review; Vol. 20 No. 1 (2023): January to February 2023; 99-116
Brazilian Business Review; v. 20 n. 1 (2023): Janeiro a Fevereiro de 2023; 99-116
1808-2386
1807-734X
reponame:BBR. Brazilian Business Review (English edition. Online)
instname:Fucape Business School (FBS)
instacron:FBS
instname_str Fucape Business School (FBS)
instacron_str FBS
institution FBS
reponame_str BBR. Brazilian Business Review (English edition. Online)
collection BBR. Brazilian Business Review (English edition. Online)
repository.name.fl_str_mv BBR. Brazilian Business Review (English edition. Online) - Fucape Business School (FBS)
repository.mail.fl_str_mv || bbronline@bbronline.com.br
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