Analysis of the visibility graphs of the Brazilian soybean, corn and chicken meat market
Keywords:Agricultural market; Complex networks; Horizontal visibility graph.
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.
Ahmadi, N., & Pechenizkiy, M. (2016). Application of horizontal visibility graph as a robust measure of neurophysiological signals synchrony. Proceedings - IEEE Symposium on Computer-Based Medical Systems, 2016-August, 273–278. https://doi.org/10.1109/CBMS.2016.73
Albert, R., & Barabási, A.-L. (2002). Statistical mechanics of complex networks. Reviews of Modern Physics, 74(1), 47–97. https://doi.org/10.1103/RevModPhys.74.47
Bini, D. A., Canever, M. D., De Souza, M. O., & Ely, R. A. (2016). Transmissão De Preços Ao Longo Das Cadeias Produtivas Do Brasil. Revista de Economia, 42(1). https://doi.org/10.5380/re.v42i1.48660
Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., & Hwang, D. U. (2006). Complex networks: Structure and dynamics. Physics Reports, 424(4–5), 175–308. https://doi.org/10.1016/j.physrep.2005.10.009
Braga, A. C., Alves, L. G. A., Costa, L. S., Ribeiro, A. A., De Jesus, M. M. A., Tateishi, A. A., & Ribeiro, H. V. (2016). Characterization of river flow fluctuations via horizontal visibility graphs. Physica A: Statistical Mechanics and Its Applications, 444, 1003–1011. https://doi.org/10.1016/j.physa.2015.10.102
CEPEA/ESALQ/USP. (2020). Consultas ao Banco de Dados do Site - Centro de Estudos Avançados em Economia Aplicada - CEPEA-Esalq/USP. Recuperado de https://www.cepea.esalq.usp.br/br/consultas-ao-banco-de-dados-do-site.aspx
CNA. (2020). Panorama do Agro | Confederação da Agricultura e Pecuária do Brasil (CNA). Recuperado de https://www.cnabrasil.org.br/cna/panorama-do-agro#_ftn2
EMBRAPA. (2020). Desempenho de produção 2019. EMBRAPA - Suínos e Aves. Recuperado de https://www.embrapa.br/suinos-e-aves/cias/estatisticas
FAS/USDA (2020). United States Department of Agriculture Foreign Agricultural Service. Disponível em: https://apps.fas.usda.gov/psdonline/app/index.html#/app/topCountriesByCommodity#chart28. Acessado em 27 de agosto de 2020.
Gao, Z. K., Cai, Q., Yang, Y. X., Dang, W. D., & Zhang, S. S. (2016). Multiscale limited penetrable horizontal visibility graph for analyzing nonlinear time series. Scientific Reports, 6(October), 1–7. https://doi.org/10.1038/srep35622
Gouveia, A. B. V. S., de Paulo, L. M., da Silva, J. M. S., de Sousa, F. E., dos Santos, F. R., Minafra, C. S. (2020). Subprodutos da soja na alimentação de aves: Revisão. Research, Society and Development, 9(7), e471974187. http://dx.doi.org/10.33448/rsd-v9i7.4187
Hochman, G., Rajagopal, D., Timilsina, G., & Zilberman, D. (2014). Quantifying the causes of the global food commodity price crisis. Biomass and Bioenergy, 68, 106–114. https://doi.org/10.1016/j.biombioe.2014.06.012
Ivanic, M., Martin, W., & Zaman, H. (2012). Estimating the Short-Run Poverty Impacts of the 2010–11 Surge in Food Prices. World Development, 40(11), 2302–2317. https://doi.org/10.1016/j.worlddev.2012.03.024
Lacasa, L., Luque, B., Ballesteros, F., Luque, J., & Nuno, J. C. (2008). From time series to complex networks: The visibility graph. Proceedings of the National Academy of Sciences, 105(13), 4972-4975.
Lacasa, L., & Toral, R. (2010). Description of stochastic and chaotic series using visibility graphs. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 82(3), 1–11. https://doi.org/10.1103/PhysRevE.82.036120
Lange, H., Sippel, S., & Rosso, O. A. (2018). Nonlinear dynamics of river runoff elucidated by horizontal visibility graphs. Chaos, 28(7), 075520. https://doi.org/10.1063/1.5026491
Luque, B., Lacasa, L., Ballesteros, F., & Luque, J. (2009). Horizontal visibility graphs: Exact results for random time series. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 80(4), 1–11. https://doi.org/10.1103/PhysRevE.80.046103
Madl, T. (2016). Network analysis of heart beat intervals using horizontal visibility graphs. Computing in Cardiology, 43, 733–736. https://doi.org/10.22489/cinc.2016.213-510
Morettin, P., & Toloi, C. (2006). Análise de Séries Temporais. São Paulo: Egard Blucher.
Oliveira Junior, O. D. P., Wander, A. E., & Figueiredo, R. S. (2014). Relação entre os preços do milho, da soja e da carne de frango no período de 2004 a 2013. In Embrapa Arroz e Feijão-Artigo em anais de congresso (ALICE). In: CONGRESSO DA SOCIEDADE BRASILEIRA DE ECONOMIA, ADMINISTRAÇÃO E SOCIOLOGIA RURAL, 52., 2014, Goiânia. Heterogeneidade e suas implicações no rural brasileiro: anais. Goiânia: Sober, 2014.
Santana, L. I. T. de, da Silva, J. M., Araújo, L. S., Moreira, G. R., & Stosic, T. (2020). Análise de quantificação de recorrência de preços brasileiros do milho, da soja e da carne de frango. Research, Society and Development, 9(10), e9979109461. https://doi.org/10.33448/rsd-v9i10.9461
Sivakumar, B., & Woldemeskel, F. M. (2015). A network-based analysis of spatial rainfall connections. Environmental Modelling and Software, 69, 55–62. https://doi.org/10.1016/j.envsoft.2015.02.020
Stam, C. J., & Reijneveld, J. C. (2007). Graph theoretical analysis of complex networks in the brain. In Nonlinear Biomedical Physics (Vol. 1, Issue 1, pp. 1–19). BioMed Central. https://doi.org/10.1186/1753-4631-1-3
Vamvakaris, M. D., Pantelous, A. A., & Zuev, K. M. (2018). Time series analysis of S&P 500 index: A horizontal visibility graph approach. Physica A: Statistical Mechanics and Its Applications, 497, 41–51. https://doi.org/10.1016/j.physa.2018.01.010
Zhang, J., Sun, J., Luo, X., Zhang, K., Nakamura, T., & Small, M. (2008). Characterizing pseudoperiodic time series through the complex network approach. Physica D: Nonlinear Phenomena, 237(22), 2856–2865. https://doi.org/10.1016/j.physd.2008.05.008
Zhu, G., Li, Y., & Wen, P. P. (2014). Analysis and classification of sleep stages based on difference visibility graphs from a single-channel EEG signal. IEEE Journal of Biomedical and Health Informatics, 18(6), 1813–1821. https://doi.org/10.1109/JBHI.2014.2303991
Zou, Y., Donner, R. V., Marwan, N., Donges, J. F., & Kurths, J. (2019). Complex network approaches to nonlinear time series analysis. Physics Reports, 787, 1–97. https://doi.org/10.1016/j.physrep.2018.10.005
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Copyright (c) 2021 José Edvaldo de Oliveira Nunes; Joelma Mayara da Silva; Lidiane da Silva Araújo ; Guilherme Rocha Moreira; Tatijana Stosic; Borko Stosic
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