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Time-varying correlations in oil, gas and CO2 prices: an application using BEKK, CCC, and DCC-MGARCH models

Julien Chevallier

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Abstract: Previous literature has identified oil and gas prices as being the main drivers of CO2 prices in a univariate 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 modeled in a vector autoregressive and multivariate GARCH framework, so as to reflect the dynamics of the correlations between the oil, gas and CO2 variables overtime. Using BEKK, CCC, and 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 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.

Keywords: Social; Sciences; &; Humanities (search for similar items in EconPapers)
Date: 2011-07-11
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Published in Applied Economics, Taylor & Francis (Routledge), 2011, pp.1. ⟨10.1080/00036846.2011.589809⟩

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Journal Article: Time-varying correlations in oil, gas and CO 2 prices: an application using BEKK, CCC and DCC-MGARCH models (2012) Downloads
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