The study looked at how to predict the volatility of agricultural commodity futures using data from Chinese markets. They found that volatility shows both long-term patterns and changes in behavior over time. By combining these two aspects into a model, they were able to make more accurate predictions about future volatility. The model performed better than other methods in forecasting volatility.