Volatility Transmission in Oil Futures Markets and Carbon Emissions Futures

Abstract

This paper examined the oil futures and the carbon emissions futures volatility comovements and spillovers for crude oil, gasoline and heat oil as well as carbon emissions. The data used in this study was the daily data from 2009 to 2014. The three multivariate GARCH models, namely the vector autoregression model (VAR) (3)-diagonal VECH, the VAR (3)-diagonal Baba, Engle, Kraft and Kroner (BEKK) and the VAR (3)- constant conditional correlations (CCC), were employed. The empirical results showed that the estimates of the VAR (3)-diagonal VECH and the VAR (3)-CCC parameters were statistically significant in a case involving oil except in the case of carbon emissions. This indicates that the short run persistence of shocks on the dynamic conditional correlations was greatest for RGASOLINE with RHEATOIL, while the largest long run persistence of shocks to the conditional correlations for RCRUDE with RGASOLINE. At the same time the VAR (3)-diagonal BEKK parameters were statistically significant in all cases. This indicates that the short run persistence of shocks on the dynamic conditional correlations is greatest for RHEATOIL with RCO2, while the largest long run persistence of shocks to the conditional correlations for RCRUDE with RCO2 and RHEATOIL with RCO2. Finally, we would choose the best model next by considering the value of log-likelihood, Akaike information criterion, Schwarz information criterion and Hannan-Quinn information criterion. The value of these figures, it could be concluded that we should choose the VAR (3)-diagonal BEKK model in volatility analysis of the oil futures and the carbon emissions futures returns. In addition, we could conclude that oil futures volatility having an impact on carbon emissions futures volatility.Keywords: The Oil Futures and the Carbon Emissions Futures Volatility; Comovements and Spillovers; Multivariate GARCH ModelsJEL Classifications: C13; C32; G13