This article investigates what determines the price dynamics of the main cereals: barley, maize, rice and wheat. Using an extensive dataset of monthly time series covering the years 1980 - 2019, we extract four different common factors explaining the dynamics of commodity prices, exchange rates, financial and macroeconomic indicators. Next, we examine whether these factors are useful in explaining the movements of cereal prices. We show that models incorporating all four factors outperform significantly the naive random walk model in out-of-sample forecasting competition, especially for longer horizons. However, they have only marginally better performance than a simpler model based on the commodity factor alone.