Risky times: Seasonality and event risk of commodities

Abstract

AbstractThe seasonal risk of wheat, corn, and soybean is modeled by a novel seasonality filter based on a generalized ridge regression. Then, using a component GARCH model, seasonal risk is combined with event risk and a short‐term risk dynamics. The resulting model is robust, generates seasonal patterns related to the crop cycle, and significantly outperforms the standard GARCH(1,1) in terms of out‐of‐sample risk prediction. Results are relevant for risk management and portfolio construction.