Forecasting the realized volatility of the oil futures market: A regime switching approach

• Published in: Energy economics Vol. 67; pp. 136 - 145
• Main Authors: Ma, Feng, Wahab, M.I.M., Huang, Dengshi, Xu, Weiju
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier B.V 01.09.2017; Elsevier Science Ltd
• Subjects: Autoregressive models; Autoregressive processes; Benchmarks; Crude oil; Economic forecasting; Energy economics; Forecasting; Forecasting evaluation; Futures market; HAR-RV-type models; Markets; Markov analysis; Markov chains; Petroleum; Regime switching approach; Studies; Switching; Volatility; Volatility forecasting; Windows; C53; C22; HAR-RV-type models; C58; Regime switching approach; E37; Volatility forecasting; E27; G14; Forecasting evaluation
• ISSN: 0140-9883; 1873-6181
• DOI: 10.1016/j.eneco.2017.08.004

Considering nonlinear and highly persistent dynamics of realized volatility, we introduce Markov regime switching models to the Heterogeneous Autoregressive model of the Realized Volatility (HAR-RV) models to forecast the realized volatility of the crude oil futures market. In-sample results demonstrate that the high volatility regime is short-lived. Out-of-sample results suggest that HAR-RV models with regime switching increase the forecasting ability significantly than those without regime switching. Moreover, these findings are robust for different actual volatility benchmarks, forecasting windows, and model settings. •Forecast the realized volatility of oil futures price using the HAR-RV and its various extensions•Introduce the regime switching to the HAR-RV-type models and evaluate the forecasting performance•In-sample results demonstrate that the high volatility regime is short-lived.•We find that HAR-RV models with regime switching can increase the forecasting ability significantly.