Analysis of the visibility graphs of the Brazilian soybean, corn and chicken meat market

• Autor(a) principal: Nunes, José Edvaldo de Oliveira
• Data de Publicação: 2021
• Outros Autores: Silva, Joelma Mayara da, Araújo , Lidiane da Silva, Moreira, Guilherme Rocha, Stosic, Tatijana, Stosic, Borko
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/11478
• topic: Agricultural market; Complex networks; Horizontal visibility graph.; Mercado agrícola; Redes complejas; Grafo de visibilidad horizontal.; Mercado Agrícola; Redes complexas; Grafo de visibilidade horizontal.

The production, export and consumption of chicken meat in Brazil are constantly growing, presenting price variations for this product that compromise the population's budget. The price of this commodity depends mainly on the cost of the feed, which includes corn and soy as a source of energy and protein, respectively. The study of the price dynamics of this product, therefore, requires an investigation also on the prices of corn and soybean inputs. In order to contribute to the development and validation of theoretical and computational models for the projection of prices for soybeans, corn and chicken, were analyzed their daily prices (in BRL), registered between 03/01/2011 and 12/04/2019, obtained of CEPEA/ESALQ/USP. From the time series of the original data of prices, were also created the series of return and volatility. The Horizontal Visibility Graph (HVG) method, implemented in C language, was used to map the time series in complex networks and, thereafter, calculate the topological indexes of interest. The results showed that the soybean and corn price networks are less integrated than that of chicken meat. In addition, the original series of soybean and corn prices, as well as the series of return of chicken prices and the volatility of corn prices, are generated by correlated stochastic processes; the return series of soybean prices presents behaviour that tends to the one of uncorrelated processes; and the others series are generated by chaotic processes.