Abstract
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.
Highlights
Permutation entropy (PE) is a method introduced by Bandt and Pompe [31] as Shannon entropy of ordinal patterns of words of a given size d, obtained by taking into account the local ordering of consecutive values observed within each word
The data used in this work are daily prices of Brazilian agricultural commodities obtained from the Center for Advanced Studies in Applied Economics/Luiz de Queiroz College of Agriculture/University of São Paulo — CEPEA/ESALQ / USP [53]
2007–2009, which makes market participants such as producers, consumers, and investors to be seriously concerned about the movements of agricultural commodities as well as their co-movements on both single market level and among different markets
Summary
Agricultural commodity markets have been drawing increased attention over the last decades, both in the scope of mainstream agricultural economics [1,2,3,4] and related fields such as econophysics [5,6,7,8,9,10,11]. Serious consequences of price spikes on food security, especially in developing countries where millions of people were pushed into hunger and poverty [13], often followed by social unrest, political instability, and socio-political conflicts [14], are the major concerns of governments and international organizations [15]. In this sense, every new empirical evidence about agricultural commodities behavior on global and/or local scale provides valuable contribution to worldwide efforts in establishing reliable scientific base to serve as an aid for developing and testing new prediction models that will include different aspects of this extremely complex phenomenon. We present the methodology, we present data and analysis together with accompanying discussion and, we draw the conclusions
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