Please use this identifier to cite or link to this item: https://rd.uffs.edu.br/handle/prefix/9397
Type: Monografia
Title: Análise da relação entre order blocks e medidas de centralidade de ativos financeiros
Author: Barcaroli, Eduardo Rostirola
First advisor: Braga , Andrei de Almeida Sampaio
Resume: O mercado financeiro apresenta elevada complexidade e forte interconectividade entre ativos, sendo influenciado significativamente pela atuação do capital institucional, responsável por gerar impactos na dinâmica dos preços e nos fluxos de mercado. Nesse contexto, este trabalho investiga a relação entre aspectos macroestruturais e microestruturais do mercado financeiro, analisando se ativos que ocupam posições semelhantes em redes de correlação também apresentam comportamentos semelhantes relacionados à formação de order blocks. A metodologia empregada consistiu na coleta e processamento de dados históricos de diferentes ativos financeiros, construção de uma matriz de correlação e geração de uma rede ponderada representando as relações entre os ativos analisados. Posteriormente, foram aplicadas medidas de centralidade, incluindo grau, strength e autovetor, com o objetivo de identificar os ativos mais relevantes dentro da estru tura da rede. Em seguida, foram identificados e caracterizados padrões de order blocks, permitindo a comparação com características estruturais dos ativos. Os resultados indicaram que ativos com maior proximidade estrutural na rede de correlação apresentaram maior recorrência de padrões semelhantes relacionados aos order blocks, sugerindo a existência de associação entre a posição estrutural dos ativos e determinados comportamentos observados em sua microestrutura. Além disso, observou-se que ativos pertencentes a setores semelhantes ou que apresentavam elevada correlação demons traram padrões mais próximos quando comparados a ativos menos conectados. Conclui-se que a integração entre análise de redes financeiras e análise microestrutural representa uma abordagem complementar para compreender a dinâmica dos mercados financeiros, contribuindo para a interpretação da influência do capital institucional sobre a formação dos preços e ampliando as possibilidades de desenvolvimento de novas metodologias de análise.
Abstract: The financial market presents high complexity and strong interconnectivity among assets, being significantly influenced by institutional capital, which plays an important role in price dynamics and market flows. In this context, this study investigates the relationship between macrostructural and microstructural aspects of financial markets by analyzing whether assets occupying similar positions in correlation networks also exhibit similar behaviors related to the formation of order blocks. The adopted methodology consisted of collecting and processing historical data from different financial assets, constructing a correlation matrix, and generating a weighted network representing the relationships among the analyzed assets. Subsequently, centrality measures, including degree, strength, and eigenvector, were applied in order to identify the most relevant assets within the network structure. Afterwards, order block patterns were identified and characterized, allowing comparisons with structural characteristics of the assets. The results indicated that assets with greater structural proximity in the correlation network presented a higher recurrence of similar order block patterns, suggesting the existence of an association between an asset’s structural position and certain behaviors observed in its market microstructure. Furthermore, assets belonging to similar sectors or presenting high levels of correlation exhibited more similar patterns when compared to less connected assets. It is concluded that integrating financial network analysis with market microstructure analysis represents a complementary approach for understanding financial market dynamics, contributing to the interpretation of institutional capital influence on price formation and expanding possibilities for the development of new analytical methodologies.
The financial market presents high complexity and strong interconnectivity among assets, being significantly influenced by institutional capital, which plays an important role in price dynamics and market flows. In this context, this study investigates the relationship between macrostructural and microstructural aspects of financial markets by analyzing whether assets occupying similar positions in correlation networks also exhibit similar behaviors related to the formation of order blocks. The adopted methodology consisted of collecting and processing historical data from different financial assets, constructing a correlation matrix, and generating a weighted network representing the relationships among the analyzed assets. Subsequently, centrality measures, including degree, strength, and eigenvector, were applied in order to identify the most relevant assets within the network structure. Afterwards, order block patterns were identified and characterized, allowing comparisons with structural characteristics of the assets. The results indicated that assets with greater structural proximity in the correlation network presented a higher recurrence of similar order block patterns, suggesting the existence of an association between an asset’s structural position and certain behaviors observed in its market microstructure. Furthermore, assets belonging to similar sectors or presenting high levels of correlation exhibited more similar patterns when compared to less connected assets. It is concluded that integrating financial network analysis with market microstructure analysis represents a complementary approach for understanding financial market dynamics, contributing to the interpretation of institutional capital influence on price formation and expanding possibilities for the development of new analytical methodologies.
Keywords: Mercado financeiro
Ativos intangíveis
Processamento de dados
Language: por
Country: Brasil
Publisher: Universidade Federal da Fronteira Sul
Acronym of the institution: UFFS
College, Institute or Department: Campus Chapecó
Type of Access: Acesso Aberto
URI: https://rd.uffs.edu.br/handle/prefix/9397
Issue Date: 2026
Appears in Collections:Ciência da Computação

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