Structural breaks and volatility forecasting in the copper futures market

This paper examines whether structural breaks contain incremental information for forecasting the volatility of copper futures. Considering structural breaks in volatility, we develop four heterogeneous autoregressive (HAR) models based on classical or latest HAR-type models. Subsequently, we apply these models to forecast volatility in the copper futures market. The empirical results reveal that our models exhibit better in-sample and out-of-sample performances than classical or latest HAR-type models. This suggests that structural breaks contain incremental prediction information for the volatility of copper futures. More importantly, we argue that considering structural breaks can improve the performances of most of existing HAR-type models.