The Hurst Exponent as an Indicator to Anticipate Agricultural Commodity Prices

Anticipating and understanding fluctuations in the agri-food market is very important in order to implement policies that can assure fair prices and food availability. In this paper, we contribute to the understanding of this market by exploring its efficiency and whether the local Hurst exponent can help to anticipate its trend or not. We have analyzed the time series of the price for different agri-commodities and classified each day into persistent, anti-persistent, or white-noise. Next, we have studied the probability and speed to mean reversion for several rolling windows. We found that in general mean reversion is more probable and occurs faster during anti-persistent periods. In contrast, for most of the rolling windows we could not find a significant effect of persistence in mean reversion. Hence, we conclude that the Hurst exponent can help to anticipate the future trend and range of the expected prices in this market.

Automated summary

In this study, we contribute to the understanding of the agri-food market by exploring its efficiency and the role of the local Hurst exponent in predicting its trend. The analysis of the time series data for different agri-commodities reveals that mean reversion is more probable and occurs faster during anti-persistent periods. Therefore, we conclude that the Hurst exponent can help anticipate the future trend and range of expected prices in this market.