Dynamic Spillover and Hedging among Carbon, Biofuel and Oil

Abstract

In recent years, there has been growing interest in the market interactions between carbon (or clean/renewable energy) and traditional fossil energy such as coal and oil, but few studies have discussed their dynamic volatility spillover and time-varying correlation. To investigate these issues, we used the weekly data of the European Union carbon emission allowance (EUA) futures, biofuel and Brent oil prices from 25 October 2009 to 5 July 2020. We employed the vector autoregressive-generalized autoregressive conditional heteroscedasticity (VAR-GARCH) model with the Baba, Engle, Kraft and Krone (BEKK) specification. Our main findings are summarized as follows: First, we identified the sudden changes and the volatility persistence in the EUA, biofuel, and Brent oil markets, and also confirmed that the volatility of the markets has changed significantly over time. Second, we found a weak volatility spillover effect among the three markets, and a strong spillover effect between the EUA and Brent oil markets. In particular, the effect of volatility spillover from the Brent oil market to the EUA market was the strongest than the other cases. Lastly, in financial market, by holding the EUA and energy sources together as assets, investors can effectively hedge their investment risk. The possibility of hedging is more pronounced between the EUA and biofuel markets.

Co-movement between oil price,CO2emission,renewable energy and energy equities: Evidence from GCC countries

“…Further research focused on volatility spillover impacts and dynamic correlation utilising diverse multivariate GARCH models. Boersen and Scholtens (2014), Koch (2014), Chang et al (2019), and Lee and Yoon (2020) have demonstrated the existence of a positive correlation and significant comovements between emissions and oil prices. However, Chang et al (2019), has pointed out the presence of weaker correlation and spillover between emissions and oil prices compared with coal and natural gas using an asymmetric BEKK model.…”

“…Fisher-Vanden et al, 2004;Oh et al, 2010;Andersson and Karpestam, 2013;Alshehry and Belloumi, 2015;Li et al, 2018;Mensah et al, 2019;Wang et al, 2019;Agbanike et al, 2019;Malik et al, 2020;Ullah et al, 2020) and on the other hand, studies have investigated the relationship of oil prices with CO 2 emission allowances prices (e.g. Koljonen and Savolainen, 2005;Diebold and Yilmaz, 2009;Liu and Chen, 2013;Koch, 2014;Hammoudeh et al, 2014;Boersen and Scholtens, 2014;Hammoudeh et al, 2015;Tan and Wang, 2017;Zeng et al, 2017;Wang and Guo, 2018;Ji et al, 2018;Chevallier et al, 2019;Chang et al, 2020;Lee and Yoon, 2020;Wang and Zhao, 2021;Zheng et al, 2021).…”

Dynamic relationships among green bonds, CO2 emissions, and oil prices

“…The results are consistent with Chevallier (2012), who found a dynamic correlation of [−0.05; 0.05] between oil and the CO 2 futures' prices of the European Climate Exchange (ECX) using data from 2005 to 2008. Additionally, several studies have confirmed the existence of a positive correlation and considerable co-movements between CO 2 emissions and oil prices (Boersen and Scholtens, 2014;Koch, 2014;Chang et al, 2019;Chen et al, 2019;Lee and Yoon, 2020).…”

Effectiveness of Artificial Neural Networks in Hedging against WTI Crude Oil Price Risk

“…The opposite is also true. The issue of risk and oil prices was also discussed by Lee and Yoon [41]. They found the effect of volatility spillover from the Brent oil market to the European Union carbon emission allowance (EUA) market.…”