Forecasting volatility in Chinese crude oil futures: insights from volatility-of-volatility and Markov regime-switching approaches
研究通过引入波动率之波动率及其跳跃成分，并结合马尔可夫区制转换特征，改进了中国原油期货市场已实现波动率的预测模型，发现该方法能显著提升预测能力。
This study aims to improve the prediction ability of realized volatility in the Chinese crude oil futures market by characterizing the volatility of volatility (VOV) and its jump components, as well as the Markov regime-switching feature. We extend the HAR-DJI-GARCH model to include the continuous and jump volatility of volatility while incorporating the Markov regime-switching feature through the MS-GARCH framework, thus offering a novel approach for capturing the intricate, nonlinear behaviour of crude oil futures volatility. Model parameters are estimated by improving the maximum likelihood approach, and the performance of the proposed model is compared to that of other models via out-of-sample R2, the CW test, the MCS test and various robustness checks. The empirical findings suggest that the incorporation of VOV, particularly jump information, alongside Markov regime switching significantly enhances the predictive power for the volatility of the Chinese crude oil futures market.