Recurrence quantification analysis of Brazilian prices of corn, soybean and chicken meat
DOI:
https://doi.org/10.33448/rsd-v9i10.9461Keywords:
Food commodities; Inputs; Recurrence plot; Recurrence quantification analysis.Abstract
Corn and soybean meal are the most used inputs in poultry feed production in Brazil. Changes in the prices of these inputs influence the price and consumption of chicken meat. With this in mind, this work aims to analyse the dynamics of chicken, corn and soybean prices individually and jointly, using the Recurrence Plot method, its extension, the Cross Recurrence Plot and the Recurrence Quantification Analysis, which were developed for the analysis of nonlinear dynamics of temporal series. The data are daily prices for chicken meet, corn and soybeans, from 08/02/2004 to 08/31/2020, provided by the Centro de Estudos Avançados em Economia Aplicada/Escola Superior de Agricultura Luiz de Queiroz/Universidade de São Paulo. The results showed that commodity prices evolve in a similar manner, where soybeans and corn prices are more synchronized with each other than with chicken prices. Considering the input/product relationship it was shown that soybean prices have a greater influence (than corn prices) on the temporal variation of chicken meat prices.
References
Afonso, L. C., Rosa, G. H., Pereira, C. R., Weber, S. A., Hook, C., Albuquerque, V. H. C., & Papa, J. P. (2019). A recurrence plot-based approach for Parkinson’s disease identification. Future Generation Computer Systems, 94, 282-292.
Artuzo, F. D., Foguesatto, C. R., Souza, Â. R. L. D., & Silva, L. X. D. (2018). Gestão de custos na produção de milho e soja. Revista Brasileira de Gestão de Negócios, 20(2), 273-294.
Bastos, J. A., & Caiado, J. (2011). Recurrence quantification analysis of global stock markets. Physica A: Statistical Mechanics and its Applications, 390(7), 1315-1325.
Baffes, J. (2013). A framework for analyzing the interplay among food, fuels, and biofuels. Global Food Security, 2(2), 110-116.
Cao, L. (1997). Practical method for determining the minimum embedding dimension of a scalar time series. Physica D: Nonlinear Phenomena, 110(1-2), 43-50.
Centro de Estudos Avançados em Economia Aplicada. (2020). Disponível em: https://www.cepea.esalq.usp.br/br. Acessado em 08 de janeiro de 2020.
de Santana, L. I. T., da Silva, A. S. A., Menezes, R. S. C., & Stosic, T. (2020). Recurrence quantification analysis of monthly rainfall time series in Pernambuco, Brazil. Research, Society and Development, 9(9), e637997737-e637997737.
de Souza, A. E., dos Reis, J. G. M., Abraham, E. R., dos Santos, R. M., & Gobbetti, M. P. (2020). Simulação de operações de grãos em um terminal portuário. Agrarian, 13(47), 114-121.
de Souza, A. E., dos Reis, J. G. M., Raymundo, J. C., & Pinto, R. S. (2018). Estudo da produção do milho no Brasil. South American Development Society Journal, 4(11), 182.
Donner, R. V., Balasis, G., Stolbova, V., Georgiou, M., Wiedermann, M., & Kurths, J. (2019). Recurrence‐Based Quantification of Dynamical Complexity in the Earth's Magnetosphere at Geospace Storm Timescales. Journal of Geophysical Research: Space Physics, 124(1), 90-108.
Eckmann, J. P., Kamphorst, S. O., & Ruelle, D. (1987). Recurrence Plots of Dynamical Systems. Europhysics Letters, 4(9), 973-977.
Goswami, B., Ambika, G., Marwan, N., & Kurths, J. (2012). On interrelations of recurrences and connectivity trends between stock indices. Physica A: Statistical Mechanics and its Applications, 391(18), 4364-4376.
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.
Kantz, H., & Schreiber, T. (2004). Nonlinear time series analysis (Vol. 7). Cambridge university press.
Marwan, N., & Kurths, J. (2002). Nonlinear analysis of bivariate data with cross recurrence plots. Physics Letters A, 302(5-6), 299-307.
Marwan, N., Romano, M. C., Thiel, M., & Kurths, J. (2007). Recurrence plots for the analysis of complex systems. Physics reports, 438(5-6), 237-329.
Marwan, N., Thiel, M., & Nowaczyk, N. R. (2002). Cross recurrence plot based synchronization of time series. arXiv preprint physics/0201062.
Marwan, N., Wessel, N., Meyerfeldt, U., Schirdewan, A., & Kurths, J. (2002). Recurrence-plot-based measures of complexity and their application to heart-rate-variability data. Physical review E, 66(2), 026702.
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..
Pereira, A. F. C., de Melo, A. F., Justo, W. R., & da Silva Melo, S. R. (2016). Cointegration and price transmission in poultry in Pernambuco. Informe GEPEC, 20(1), 129.
R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
Strozzi, F., Zaldívar, J. M., & Zbilut, J. P. (2007). Recurrence quantification analysis and state space divergence reconstruction for financial time series analysis. Physica A: statistical mechanics and its applications, 376, 487-499.
Takens, F. (1981). Detecting strange attractors in turbulence. In Dynamical systems and turbulence, Warwick 1980 (pp. 366-381). Springer, Berlin, Heidelberg.
United States Department of Agriculture Foreign Agricultural Service. (2020). Disponível em: https://apps.fas.usda.gov/psdonline/app/index.html#/app/topCountriesByCommodity#chart28. Acessado em 27 de agosto de 2020.
Webber Jr, C. L., & Zbilut, J. P. (2005). Recurrence quantification analysis of nonlinear dynamical systems. Tutorials in contemporary nonlinear methods for the behavioral sciences, 94(2005), 26-94.
Xu, Z., Wang, H., Wan, H., & Li, H. (2019). Quantitative Assessment of Nonstationarity of Wind Speed Signal Using Recurrence Plot. Journal of Aerospace Engineering, 32(6), 04019094
Yao, C. Z., & Lin, Q. W. (2017). Recurrence plots analysis of the CNY exchange markets based on phase space reconstruction. The North American Journal of Economics and Finance, 42, 584-596.
Zaitouny, A., Small, M., Hill, J., Emelyanova, I., & Clennell, M. B. (2020). Fast automatic detection of geological boundaries from multivariate log data using recurrence. Computers & Geosciences, 135, 104362.
Zbilut, J. P. (2005). Use of recurrence quantification analysis in economic time series. In Economics: Complex Windows (pp. 91-104). Springer, Milano.
Zbilut, J. P., Giuliani, A., & Webber Jr, C. L. (1998). Detecting deterministic signals in exceptionally noisy environments using cross-recurrence quantification. Physics Letters A, 246(1-2), 122-128.
Zbilut, J. P., & Webber Jr, C. L. (1992). Embeddings and delays as derived from quantification of recurrence plots. Physics letters A, 171(3-4), 199-203.
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Copyright (c) 2020 Leika Irabele Tenório de Santana; Joelma Mayara da Silva; Lidiane da Silva Araújo; Guilherme Rocha Moreira; Tatijana Stosic
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