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Permutation Entropy and Statistical Complexity Analysis of Brazilian Agricultural Commodities

Departamento de Estatística e Informática, Universidade Federal Rural de Pernambuco, Rua Dom Manoel de Medeiros s/n, Dois Irmãos, Recife, PE 52171-900, Brazil
Instituto de Física, Universidade Federal de Alagoas (UFAL). Avenida Lourival Melo Mota s/n, Tabuleiro do Martins, Maceió, AL CEP 57072-900, Brazil
Instituto de Medicina Traslacional e Ingeniería Biomedica, Hospital Italiano de Buenos Aires & CONICET. Tte. Gral. Juan Domingo Perón 4190, Ciudad Autónoma de Buenos Aires C1199ABB, Argentina
Author to whom correspondence should be addressed.
Entropy 2019, 21(12), 1220;
Received: 27 October 2019 / Revised: 4 December 2019 / Accepted: 10 December 2019 / Published: 14 December 2019
(This article belongs to the Special Issue Information Theoretic Measures and Their Applications)
Agricultural commodities are considered perhaps the most important commodities, as any abrupt increase in food prices has serious consequences on food security and welfare, especially in developing countries. In this work, we analyze predictability of Brazilian agricultural commodity prices during the period after 2007/2008 food crisis. We use information theory based method Complexity/Entropy causality plane (CECP) that was shown to be successful in the analysis of market efficiency and predictability. By estimating information quantifiers permutation entropy and statistical complexity, we associate to each commodity the position in CECP and compare their efficiency (lack of predictability) using the deviation from a random process. Coffee market shows highest efficiency (lowest predictability) while pork market shows lowest efficiency (highest predictability). By analyzing temporal evolution of commodities in the complexity–entropy causality plane, we observe that during the analyzed period (after 2007/2008 crisis) the efficiency of cotton, rice, and cattle markets increases, the soybeans market shows the decrease in efficiency until 2012, followed by the lower predictability and the increase of efficiency, while most commodities (8 out of total 12) exhibit relatively stable efficiency, indicating increased market integration in post-crisis period. View Full-Text
Keywords: permutation entropy; statistical complexity; agricultural commodities; food crisis permutation entropy; statistical complexity; agricultural commodities; food crisis
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MDPI and ACS Style

de Araujo, F.H.A.; Bejan, L.; Rosso, O.A.; Stosic, T. Permutation Entropy and Statistical Complexity Analysis of Brazilian Agricultural Commodities. Entropy 2019, 21, 1220.

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