Multiscale interplay of higher-order moments between the carbon and energy markets during Phase III of the EU ETS

Energy Policy ◽  
2021 ◽  
Vol 156 ◽  
pp. 112428
Author(s):  
Xingyu Dai ◽  
Ling Xiao ◽  
Qunwei Wang ◽  
Gurjeet Dhesi
Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1787
Author(s):  
Pilar Gargallo ◽  
Luis Lample ◽  
Jesús A. Miguel ◽  
Manuel Salvador

This paper analyzes the co-movements of prices of fossil fuels, energy stock markets and EU allowances. This analysis is conducted in order to identify the spillover effect of volatility and correlation among these financial markets, and to provide a scientific basis that shows the interest of incorporating sustainable assets in the design of minimum risk strategies of investment. To achieve this goal, we have used a Vector Autoregressive-Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroscedasticity (VAR-DCC-GARCH) model that also incorporates a stock index of industrial companies as a leading indicator of the level of economic activity. In addition, the paper conducts an impulse response analysis to determine how unexpected shocks to prices are propagated along time, and, in particular, how they affect prices of the others, both in mean, variance and correlation. Therefore, the results of this one- and two-dimensional analysis allow for the study of short and long run dynamics of the relationship among those prices, thus, providing greater meaning and information for investors, which has implications for building their portfolios. The analyzed period was from January 2010 to February 2021, so that the data include half of phase II, full phase III and the onset of phase IV of the EU ETS, as well as the COVID-19 outbreak in the European context. We also analyzed whether the EUA price impulses the demand of clean energy stocks, which has important implications for the objective of triggering the investment in clean energy. Our results show the transmission mechanism of all of those prices, which are relevant not only for investors but also for policymakers to construct an early-warning system, revealing the most important transmission channels. Moreover, from an investment viewpoint, we observe a decline in dirty energies and a rise in the clean energy market, which might be an indication of the progress towards the energy transition to renewables sources within a circular economy perspective. Therefore, this shows that the EU ETS is achieving its goals, and that clean energy companies, aligned with their role towards socially responsible initiatives, are also gaining acceptance in terms of investments, which would be beneficial for the environment.


2008 ◽  
Vol 5 (2) ◽  
pp. 159-181
Author(s):  
Simon Marr ◽  
Johannes Enzmann

AbstractWith the Climate and Energy Package the European Commission has also published its draft for a revised EU Emissions Trading Scheme from 2013 onwards. The draft revision of the EU ETS serves as the EU's main pillar to fight climate change in that it requires a reduction of mainly CO2 of 21% below 2005 figures for the EU's major emissions sources in the energy and industry sectors. In addition, most notably the EU is proposing an EU wide cap and harmonised allocation rules, in order to exploit the full potential of emissions trading making national allocation plans ghosts of the past. The revised EU ETS gives investors into CDM projects the necessary long time planning security for investments into projects. At the same time it sends out a strong signal to the international negotiations for a post-2012 climate agreement in that it allows the use of more project based generated credits within the EU ETS once an ambitious post 2012 agreement is concluded.


2018 ◽  
Vol 1 (1) ◽  
pp. 407-413
Author(s):  
Aneta Włodarczyk ◽  
Marta Kadłubek

Abstract Tightening the environmental norms that result from the priorities of the EU 2030 Energy and Climate Package and the reform of the EU ETS have caused the necessity to implement an effective system of managing the risk of carbon dioxide emission and integrate it with the existing enterprise management system. Evaluation of the direction and strength of correlation between EUA price changes and energy companies stock price returns is crucial from point of view the managerial staff making proper decisions about the use of the CO2 emission permits by energy companies. It is an important stage of carbon emission risk management process. The aim of this paper is to verify the possibility of use the multifactor models with GARCH structure as a tool supporting the carbon emission management process in energy companies. Empirical analysis is connected with the estimation of multifactor models with GARCH structure in the Phase II and Phase III of the EU ETS functioning for two groups of Polish energy companies: group of the Respect Index companies and others. Such an approach allows to check whether the Respect Index companies are more robust than others on the carbon emission risk, in particular the EUA price risk associated with the intensification works on modifying the EU ETS functioning. We found that the impact of EUA price changes on energy companies stock returns and their volatility is statistically insignificant in case of all Respect Index companies.


2021 ◽  
Author(s):  
Majid Mirzaee Ghazani ◽  
Mohammad Ali Jafari

Abstract This study has investigated the changing efficiency for the phase III EU ETS CO2 market using the daily historical data of allowance futures prices and coverage from August 2015 to June 2019. To achieve this goal, we have applied two alternative tests for checking dependency by linear and nonlinear methods, which include Generalized Spectral (GS) and Automatic Portmanteau (AQ). Also, we had a comprehensive look at the carbon market evolution and the EU ETS scheme development over time. The analysis of observed results validates the Adaptive Market Hypothesis (AMH) in the market, which corresponds with the oscillatory behavior of the applied test statistics' p-values. The other aspect of the study was to analyze the existence of evolutionary behavior on the market. To reach this purpose, we checked the results by applying a rolling window technique with four different time windows (50, 100, 150, and 250 days) on the test statistics in harmony with the adaptive market hypothesis. The obtained results show that overall, market efficiency has been improved by moving toward implementing the higher window lengths.


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