Abstract
Using the Heterogeneous Autoregressive Realized Volatility (HAR-RV) model as a modeling platform, we study whether climate-risk factors help to predict the realized volatility of movements of agricultural commodity prices. Our main finding is that climate-risk factors improve the predictive performance of the HAR-RV model mainly at longer prediction horizons (month or beyond). Our main finding is robust to estimating the HAR-RV model by the ordinary least squares technique, and to using various shrinkage estimators. We discuss the implications of our results for policymakers and investors.
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