Forecasting Wheat Prices Based on Past Behavior: Comparison of Different Modelling Approaches

Abstract

Being able to accurately forecast the evolution of wheat prices can be a valuable tool. Most of the published works apply classical forecasting models to wheat price time series, and they do not always perform out-of-sample testing. This work compares five modelling approaches for wheat price forecasts, using only past values of the time series. The models performance is assessed considering out-of-sample data only, by considering a sliding and growing time window that will define the data used to determine the models parameters, and the data used for out-of-sample forecasts.