Effects of structural changes on the prediction of downside volatility in futures markets
提出一个考虑结构变化的异质自回归下行波动率模型，用于预测标普500指数、原油、黄金、铜和大豆期货的下行波动率，发现结构变化能提升预测效果，对风险管理有参考价值。
Abstract We develop a heterogeneous autoregressive model of downside volatility (HAR‐DV) model with structural changes (HAR‐DV‐SC) model to investigate the effects of structural changes on predicting downside volatility. Then we employ HAR‐DV and HAR‐DV‐SC models to forecast downside volatilities in S&P 500 index, crude oil, gold, copper, and soybean futures markets. The in‐sample analysis shows that structural changes contain in‐sample information for predicting downside volatility. The out‐of‐sample analysis indicates that the HAR‐DV‐SC model outperforms the HAR‐DV model, suggesting that structural changes contain incremental out‐of‐sample information on future downside volatility. These results are robust and have important implications for risk management of stakeholders.