The 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.

中文翻译：

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风险时期：商品的季节性和事件风险

小麦、玉米和大豆的季节性风险通过基于广义岭回归的新型季节性过滤器进行建模。然后，使用组件 GARCH 模型，将季节性风险与事件风险和短期风险动态相结合。所得模型非常稳健，可生成与作物周期相关的季节性模式，并且在样本外风险预测方面显着优于标准 GARCH(1,1)。结果与风险管理和投资组合构建相关。