Correlações cruzadas entre os mercados brasileiros de energia e alimentos

Abstract

As human beings developed agriculture, human civilization was modified. Innovations in the world’s agriculture have turned this activity into a major energy drain. In this way, the agricultural sector become heavily dependent on energy prices through the cost of transport, fertilizers, pesticides and food processing. Energy prices also affect the food market by inducing policies that divert food crops to the production of biofuels. The relationship between oil prices and agricultural commodity (feedstock) prices has attracted a considerable attention in the last years, resulting in an extensive scientific literature. The most important link between the energy and food markets is the production of biofuels (ethanol and biodiesel). The increased production of biofuels and its competition with food production raises the need for a deeper understanding of the relationship between the two markets. The interaction between biofuel and food markets in the US and Europe has been extensively studied in the last years. On the other hand, the Brazilian market for sugar cane and ethanol has received much less attention. In the present study, the interaction between the Brazilian energy and food markets was investigated from the point of view of Econophysics. The weekly series of prices of oil, ethanol and sugar for the period 07/07/2000 to 03/24/2016 were analyzed using the methods Detrended Cross Correlation Analysis (DCCA) and its recently proposed modification Detrended Partial Cross Correlation Analysis (DPCCA) which was developed to quantify the intrinsic cross-correlations between two non-stationary time series. The results show the existence of long-range cross-correlations in time series of volatility of oil, ethanol and sugar indicated by the value of DCCA exponent which was greater than 0.5. The intrinsic cross-correlations revealed by the DPCCA are positive for ethanol-sugar and oil-sugar volatility series, and negative for oil-ethanol volatility series, suggesting that the interactions between energy commodity markets and agricultural commodity market are different from the interactions within the energy commodities market.