Análise espaço temporal no setor energético, metais preciosos e agropecuário

• Ano de defesa: 2025
• Autor(a) principal: Santana, Thiago Pires
• Orientador(a): Zebende, Gilney Figueira
• Banca de defesa: Rodrigues, Carlos Alberto, Guedes, Everaldo Freitas, Jale, Jader da Silva, Pesente, Ronaldo
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual de Feira de Santana
• Programa de Pós-Graduação: Programa de Pós-Graduação em Modelagem em Ciências da Terra e do Ambiente
• Departamento: DEPARTAMENTO DE CIÊNCIAS EXATAS
• País: Brasil
• Palavras-chave em Português: Séries temporais; Interdependência; Efeito de Contágio; Commodities; αDF A; ρDCCA
• Palavras-chave em Inglês: Time series; Interdependence; Contagion Effect; Commodities; αDF A; ρDCCA
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA
• Link de acesso: http://tede2.uefs.br:8080/handle/tede/2015

The technologies have made the world increasingly interconnected, enabling the simultaneous exchange of information between geographically distant spaces. Currently, socioeconomic and environmental structures are studied in an integrated manner, taking into account their interaction, adaptation, and evolution, a methodological approach grounded in the analysis of complex systems. The economic sector, for instance, exhibits an interactive relationship among various other agents, being capable of generating positive and/or negative interferences in their dynamics, as occurs in the energy, agricultural, and precious metals sectors. In this context, the main objective of this research is to map the interactive and temporal dynamics of financial index series in the energy, precious metals, and agricultural sectors. To achieve this goal, we initially investigate the scientific landscape related to the research topic through a bibliometric analysis. Subsequently, we performed the characterization of the time series regarding the presence of long-range dependence, interdependence, and contagion effects, based on the exponent αDF A and the coefficients ρDCCA and ∆ρDCCA metrics widely employed in the field of Econophysics for the analysis of dependence and correlation among non-stationary series. We worked with the indices of oil, gold, silver, corn, live cattle, soybeans, and companies in the clean energy sector in order to understand the dynamics of the series and their respective markets. The results are presented in Chapter 3 in the form of a scientific article. Through bibliometric studies, we recognize that Econophysics has grown as a scientific field, and that the analysis of interdependence and contagion in agricultural commodities has been approached from the perspective of sustainability and energy transition. We observed that the COVID-19 pandemic affected the price dynamics of oil and precious metals, with greater intensity among oil indices. Furthermore, positive contagion was identified across the analyzed commodities, especially between metals and oil. In the agricultural sector, we observed persistence in most indices, with emphasis on the commodity of live cattle, while the commodity of corn exhibited this pattern only at small temporal scales. Our findings indicated that most companies in the clean energy segment exhibit interdependent relationships, characterized by the formation of groups with higher connectivity and elements that exert greater interaction within these groups. Based on the results, we conclude that science has become increasingly interdisciplinary, with a growing focus on sustainable balance. The current process of globalization recognizes that local events exert influence on global dynamics and enables the diversification and mitigation of systemic crises, allowing large, medium, and small producers or institutions to alleviate difficulties. Thus, it becomes possible to understand economic interactions and how they affect each sector.