Modeling Long Range Dependence in Wheat Food Price Returns

Abstract

The present paper focuses on analyzing the volatility dynamics of wheat commodity based on the presence of long memory. The paper utilizes several econometric tests to identify the presence and magnitude of the fractional difference parameter. Fractional GARCH models, namely FIGARCH and FIEGARCH, are employed to examine the long memory property. Twenty years of wheat daily price data were used to study the long-range dependence. The results reveal that fractional integration is found in the daily wheat price return series. Overall, the FIGARCH model seems a better fit, in describing the time-varying volatility of the commodity adequately, compared to the FIEGARCH model. Food price shocks are likely to persist for a long time for wheat, resulting in higher market risk for producers and increased purchasing costs for consumers.