New model predicts agricultural commodity price swings with unprecedented accuracy.
Realized GARCH model using high frequency data can better predict price volatility for agricultural commodity futures than traditional models. The model considers skewness and fat-tail in prices, outperforming daily price data-based models like GARCH and EGARCH. Different realized measures show similar performance in forecasting volatility.