Time-varying correlations in oil, gas and CO2 prices: an application using BEKK, CCC, and DCC-MGARCH models
AbstractPrevious literature has identified oil and gas prices as being the main drivers of CO2 prices in a univariate Generalized Autoregressive Conditional Heteroscedasticity (GARCH) econometric framework (Alberola et al., 2008; Oberndorfer, 2009). By contrast, we argue in this article that the interrelationships between energy and emissions markets shall be modelled in a Vector Autoregressive (VAR) and Multivariate GARCH (MGARCH) framework, so as to reflect the dynamics of the correlations between the oil, gas and CO2 variables overtime. Using the Baba–Engle–Kraft–Kroner (BEKK), Constant Conditional Correlation (CCC) and Dynamic Conditional Correlation MGARCH (DCC-MGARCH) models on daily data from April 2005 to December 2008, we highlight significant own-volatility, cross-volatility spillovers, and own persistent volatility effects for nearly all markets, indicating the presence of strong Autoregressive Conditional Heteroscedasticity (ARCH) and GARCH effects. Besides, we provide strong empirical evidence of time-varying correlations in the range of [−0.3; 0.3] between oil and gas, [−0.05; 0.05] between oil and CO2, and [−0.2; 0.2] between gas and CO2, that have not been considered by previous studies. These findings are of interest for traders and utilities in the energy sector, but also for a broader applied economics audience.
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Bibliographic InfoPaper provided by Paris Dauphine University in its series Economics Papers from University Paris Dauphine with number 123456789/6790.
Date of creation: Nov 2012
Date of revision:
Publication status: Published in Applied Economics, 2012, Vol. 44, no. 32. pp. 4257-4274.Length: 17 pages
DCC-MGARCH model; CCC-MGARCH model; BEKK-MGARCH model; time-varying correlation; multivariate GARCH; vector autoregression; EU ETS; CO2; oil; gas;
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- Hammoudeh, Shawkat & Nguyen, Duc Khuong & Sousa, Ricardo M., 2014. "Energy prices and CO2 emission allowance prices: A quantile regression approach," Energy Policy, Elsevier, vol. 70(C), pages 201-206.
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