In this paper, we forecast energy market volatility using both univariate and multivariate GARCH-class models. First, we forecast volatilities of individual assets and find that multivariate models display better performance than univariate models. Second, we forecast crack spread volatility and...

This paper extends the work of Kang et al. (2009). We use a greater number of linear and nonlinear generalized autoregressive conditional heteroskedasticity (GARCH) class models to capture the volatility features of two crude oil markets -- Brent and West Texas Intermediate (WTI). The one-,...

This paper extends the work in Tabak and Cajueiro [Are the crude oil markets becoming weakly efficient over time, Energy Economics 29 (2007) 28-36] and Alvarez-Ramirez et al. [Short-term predictability of crude oil markets: a detrended fluctuation analysis approach, Energy Economics 30 (2008)...

While the impacts of oil price changes on agricultural commodity markets are of great interest to economists, previous studies do not differentiate oil-specific shocks from aggregate demand shocks. In this paper, we address this issue using a structural VAR analysis. Our findings indicate that...

In this paper, we explore the strategy on hedging crude oil using refined product. We develop a regime switching asymmetric DCC (RS-ADCC) model by taking into account both of regime switching and asymmetry in correlations. Our out-of-sample findings indicate that RS-ADCC displays greater hedging...

In this paper, we forecast excess stock returns of S&P 500 index from January 1997 to December 2012 using both well-known traditional macroeconomic indicators and oil market variables. Based on a dynamic model selection approach, we find that the forecasting accuracy can be improved after adding...