Volatility forecasting of crude oil futures market: Which structural change-based HAR models have better performance?

Abstract

The paper focuses on the smooth and sharp structural changes in crude oil futures volatility and singles out the flexible Fourier form (FFF) and the modified ICSS algorithm to detect them, respectively, so as to explore whether different structural change-based HAR models exhibit significantly better performance for crude oil return volatility forecasting than traditional HAR-type models. The empirical results indicate that, on the one hand, crude oil market displays a strong evidence of breaks, and the incorporation of trigonometric terms can account for the structural changes in crude oil return volatility. On the other hand, the flexible Fourier form (FFF) based HAR-type models and the Structural Breakpoints (SB) based HAR-type models yield superior forecasting performance than traditional HAR-type models. Meanwhile, the forecasting results and economic performance of the former usually outperform the latter, particularly for the short- and medium-term forecasts.