SSCI论文——Forecasting crude oil market volatility Further evidence using GARCH-class models.pdf

JNU Energy Economics 32 (2010) 1477–1484 Contents lists available at ScienceDirect Energy Economics journal homepage: www. elsevi /locate/eneco Forecasting crude oil market volatility: Further evidence using GARCH-class models Yu Wei a,⁎, Yudong Wang b, Dengshi Huang a a School of Economics and Management, Southwest Jiaotong University, First Section of Northern Second Ring Road, Chengdu, Sichuan Province, China b Antai College of Economics and Management, Shanghai Jiaotong University, Fahuazhen Road 535, Shanghai, China a r t i c l e i n f o a b s t r a c t Article history: This paper extends the work of Kang et al. (2009). We use a greater number of linear and nonlinear Received 23 May 2010 generalized autoregressive conditional heteroskedasticity (GARCH) class models to capture the volatility Received in revised form 18 July 2010 features of two crude oil markets — Brent and West Texas Intermediate (WTI). The one-, five- and twenty- Accepted 18 July 2010 day out-of-sample volatility forecasts of the GARCH-class models are evaluated using the superior predictive Available online 24 July 2010 ability test and with more loss functions. Unlike Kang et al. (2009), we find that no model can outperform all of the other mo