carbon market
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Author(s):  
Po Yun ◽  
Chen Zhang ◽  
Yaqi Wu ◽  
Yu Yang

The carbon market is recognized as the most effective means for reducing global carbon dioxide emissions. Effective carbon price forecasting can help the carbon market to solve environmental problems at a lower economic cost. However, the existing studies focus on the carbon premium explanation from the perspective of return and volatility spillover under the framework of the mean-variance low-order moment. Specifically, the time-varying, high-order moment shock of market asymmetry and extreme policies on carbon price have been ignored. The innovation of this paper is constructing a new hybrid model, NAGARCHSK-GRU, that is consistent with the special characteristics of the carbon market. In the proposed model, the NAGARCHSK model is designed to extract the time-varying, high-order moment parameter characteristics of carbon price, and the multilayer GRU model is used to train the obtained time-varying parameter and improve the forecasting accuracy. The results conclude that the NAGARCHSK-GRU model has better accuracy and robustness for forecasting carbon price. Moreover, the long-term forecasting performance has been proved. This conclusion proves the rationality of incorporating the time-varying impact of asymmetric information and extreme factors into the forecasting model, and contributes to a powerful reference for investors to formulate investment strategies and assist a reduction in carbon emissions.


2022 ◽  
Vol 2022 ◽  
pp. 1-13
Author(s):  
Shaohui Zou ◽  
Tian Zhang

With the continuous expansion scale of carbon market and the development of carbon trading mechanism, carbon emission right, as a new financial asset, is being brought into the category of asset allocation by more and more investors. As the burning of coal is the major source of carbon dioxide, China is facing serious ecological and environmental problems, which restrict the development of low-carbon economy. In order to reach the carbon dioxide emission reduction targets and promote the development of green investment market, the carbon market should be a good emission reduction measure. The correlation and dynamic volatility spillover among coal, carbon, and green investing markets are becoming a hot topic for current research. The paper applies both VAR-GARCH-DCC and VAR-GARCH-BEKK models to draw some significant conclusions. (1) The green investment market, coal market, and Shenzhen carbon market show obvious time-varying correlation, and the volatility of the green investment market is higher. (2) There is a bidirectional Granger causality between green investing and coal markets. (3) The investment portfolio and hedging mechanism of the market are established to reduce the risk and help investors obtain higher returns.


2022 ◽  
Vol 14 (2) ◽  
pp. 655
Author(s):  
Huangwei Deng ◽  
Ying Su ◽  
Zhenliang Liao ◽  
Jiang Wu

To slow down climate warming and achieve sustainable development, the Paris Agreement attempts to establish cooperative approaches (Article 6.2 in the Paris Agreement) and a sustainable development mechanism (Article 6.4 in the Paris Agreement) for carbon trading. However, deficiencies in implementation exist due to a lack of systematic execution regulations and an integrated management system. To strengthen the effectiveness of the two carbon trading mechanisms for reducing carbon emission, this paper aims to propose an implementation framework of cooperative approaches and a sustainable development mechanism. Based on the international regime theory in global climate change and the nine elements of the market mechanism, the paper makes use of comparative analysis to discuss the type of mechanism, coverage of the system, operational framework, governance framework, and implementation framework of cooperative approaches and a sustainable development mechanism. The main results and conclusions are as follows: (1) Cooperative approaches are considered as project-based and quota-/credit-based carbon market mechanisms. Under cooperative approaches, trading units should be authorized at the international-regional and sub-regional levels. CO2, CH4, N2O, HFCs, PFCs, SF6, and NF3 are the seven types of greenhouse gases that could be traded through cooperative approaches, and they shall be accounted by the unit of CO2-eq. (2) The sustainable development mechanism is considered as an industry-based and credit-based carbon market framework. Under the sustainable development mechanism, trading units should be authorized at the international level. CO2, CH4, N2O, and PFCs can work in the sustainable development mechanism as subject matters. The unit of gases shall be CO2-eq as well. (3) The implementation framework of cooperative approaches ought to follow three stages: project preparation, project submission, and auditing, as well as internationally transferred mitigation outcomes transfer. The implementation framework of the sustainable development mechanism ought to contain three stages: project development and review, project implementation and monitoring, and project acceptance and unit transfer. The authors hope it can work as a guideline for the early implementation stage of the cooperative approaches and sustainable development mechanism to stimulate carbon reduction and further slow climate change.


Author(s):  
Callum Murdoch ◽  
Lisa Keppler ◽  
Tillem Burlace ◽  
Christine Wörlen

AbstractIn 2013, the United Kingdom Department for International Development and the Department of Business, Energy, and Industrial Strategy published a business case for the Carbon Market Finance Programme (CMFP). The core mandate: to build capacity and develop aids for least developed countries in sub-Saharan Africa to access finance via the carbon market. The chosen strategy involved signing emission reduction purchase agreements with private sector enterprises, using the United Nations Framework Convention for Climate Change’s Clean Development Mechanism (CDM) to verify generation of tradeable certified emissions reductions. The World Bank’s Carbon Initiative for Development (Ci-Dev) would implement the 12-year program. The team for the 2019 midterm evaluation found that program uncertainty—from sociopolitical challenges in pilot markets to global indecision on the future of Article 6 and carbon markets—would complicate assessing progress toward business case objectives. The collapse and failed recovery of the carbon market impacted underlying assumptions of the CMFP’s theory of change, and uncertainty about CDM’s future complicated evaluation of program sustainability. This chapter presents a practical approach to using realist evaluation to overcome the contextual uncertainties of the carbon market landscape, providing strengths and weaknesses of the approach applied and recommending a revised approach for future evaluations.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Hua Xu ◽  
Minggang Wang

Carbon price fluctuation is affected by both internal market mechanisms and the heterogeneous environment. Moreover, it is a complex dynamic evolution process. This paper focuses on carbon price fluctuation trend prediction. In order to promote the accuracy of the forecasting model, this paper proposes the idea of integrating network topology information into carbon price data; that is, carbon price data are mapped into a complex network through a visibility graph algorithm, and the network topology information is extracted. The extracted network topology structure information is used to reconstruct the data, which are used to train the model parameters, thus improving the prediction accuracy of the model. Five prediction models are selected as the benchmark model, and the price data of the EU and seven pilot carbon markets in China from June 19, 2014, to October 9, 2020, are chosen as the sample for empirical analysis. The research finds that the integration of network topology information can significantly improve the price trend prediction of the five benchmark models for the EU carbon market. However, there are great differences in the accuracy improvement effects of China’s seven pilot carbon market price forecasts. Moreover, the forecasting accuracy of the four carbon markets (i.e., Guangdong, Chongqing, Tianjin, and Shenzhen) has improved slightly, but the prediction accuracy of the carbon price trend in Beijing, Shanghai, and Hubei has not improved. We analyze the reasons leading to this result and offer suggestions to improve China’s pilot carbon market.


Author(s):  
Neydi Cruz ◽  
Mireille Meneses

AbstractMexico has participated in different international climate initiatives and has benefited from international collaboration. This cooperation, both at the political and technical levels, has been crucial for the design and implementation of the national carbon market. Through its climate diplomacy leadership, Mexico has played a key role in international carbon pricing initiatives, and in the technical sphere, the country has benefited from peer-to-peer international experiences and knowledge. This chapter analyzes those initiatives and their contribution to continue broadening collaboration towards a carbon market in the country. It explores how recent changes to the environmental agenda, adopted as of 2018 by the new federal administration, could hinder the implementation of the market mechanism.


2021 ◽  
Vol 9 ◽  
Author(s):  
Sen Qiao ◽  
Chen Xi Zhao ◽  
Kai Quan Zhang ◽  
Zheng Yu Ren

With the improvement of China’s carbon emission trading system, the spillover effect between carbon and energy markets is becoming more and more prominent. This paper selects four representative pilot carbon markets, including Beijing (BEA), Guangdong (GDEA), Hubei (HBEA) and Shanghai (SHEA). And three representative energy markets, including Crude Oil Futures (SC), power index (L11655) and China Securities new energy index (NEI). Combining the rolling window technology with DY spillover index, set a 50-weeks rolling window to measure the spillover index, and deeply analyze the time-varying two-way spillover effect between China’s carbon and energy markets. The results show that the spillover effect between China’s carbon and energy markets has significant time variability and two-way asymmetry. The time-varying spillover effect of different carbon pilot markets on the energy market has regional heterogeneity. The volatility spillover effect of Beijing and Shanghai carbon markets mainly comes from the crude oil futures market, Guangdong carbon market mainly comes from the new energy market, and Hubei carbon market mainly comes from crude oil and electricity market. The above research results contribute to the prevention of potential risk spillover between carbon and energy markets, which can promote the establishment of China’s unified carbon market and the prevention of systemic financial risks in energy market.


2021 ◽  
Vol 9 ◽  
Author(s):  
Wangzi Xu

As the country with the largest CO2 emissions in the world, the Chinese government has put forward clear goals of hitting peak carbon emissions by 2030 and carbon neutralization by 2060. Thus, China started piloting carbon emission trading in 2013, and in July 2021 China opened national carbon trading, which is the largest carbon market in the world (China Launches World, 2021). Therefore, it is very important for China to study the role and mechanism of carbon trading at present. Based on the quasi-natural experiment of China’s carbon market pilot, this paper uses panel data of 30 provinces in mainland China from 2008 to 2019 to conduct an empirical study on carbon emission reduction and the economic effects in China’s pilot provinces through a Time-varying Differences-in-Differences method model. The results show that the implementation of a carbon trading policy can significantly inhibit carbon emissions and promote economic growth. At the same time, this paper further analyzes the emission reduction mechanism of the carbon emissions trading policy through the intermediary effect test and finds that the policy mainly realizes carbon emission reduction by changing the energy consumption structure, promoting low-carbon innovation, and upgrading the industrial structure. In addition, innovative research has found the impact of a carbon price signal and marketization on the emission reduction effect of the carbon market. Finally, targeted suggestions are put forward.


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