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Energies
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Risk Management in Carbon and Oil Markets
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Risk Management in Carbon and Oil Markets

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "C: Energy Economics and Policy".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 6564

Special Issue Editors

Dr. Lu Yang

E-Mail Website
Guest Editor
College of Economics, Shenzhen University, 3688 Nanhai Blvd, Nanshan, Shenzhen 518060, China
Interests: oil price shocks; oil markets; spillover; carbon markets; finance; economics
Special Issues, Collections and Topics in MDPI journals
Dr. Xiaojing Cai

E-Mail Website
Guest Editor
Graduate School of Humanities and Social Sciences, Okayama University, Okayama 700-0583, Japan
Interests: time series analysis; international financial econometrics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Climate change has been attracting increasing attention from both industries and academics. Carbon emissions trading markets designed to internalize the external cost of carbon emissions have been operating for more than 10 years now, and an abundance of trading data has been generated and recorded. It is thus urgent to utilize the data to improve carbon risk management, implement climate policy, optimize carbon neutrality, etc. All these new challenges also have significant influences on the energy market. We aim to present and discuss frontier research in all areas related to carbon finance, risk management, and high quality, especially the important role of China’s actions in carbon neutrality. With this Special Issue, we will focus on empirical analyses of the carbon market and its growing relevance worldwide.

Papers should focus on global climate change on carbon, energy markets, and climate policies. Topics of particular interest include but are not limited to:

  • Improve the pricing efficiency of energy markets;
  • ESG and green investment;
  • The role of climate policy on carbon risk;
  • Evaluation of recent climate policy actions and outcomes on energy markets;
  • Asset pricing issues resulting from climate change;
  • Firm and household behavior resulting from carbon trading;
  • Low carbon economy and energy;
  • Fin-tech and carbon finance;
  • Fiscal policy and carbon tax.

Dr. Lu Yang
Dr. Xiaojing Cai
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Published Papers (4 papers)

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Research

17 pages, 1121 KiB  
Article
Features and Evolution of Global Energy Trade Patterns from the Perspective of Complex Networks
by Yingnan Cong, Yufei Hou, Jiaming Jiang, Shuangzi Chen and Xiaojing Cai
Energies 2023, 16(15), 5677; https://doi.org/10.3390/en16155677 - 28 Jul 2023
Cited by 2 | Viewed by 1692
Abstract
As an integral part of economic trade, energy trade is crucial to international dynamics and national interests. In this study, an international energy trade network is constructed by abstracting countries as nodes and representing energy trade relations as edges. A variety of indicators [...] Read more.
As an integral part of economic trade, energy trade is crucial to international dynamics and national interests. In this study, an international energy trade network is constructed by abstracting countries as nodes and representing energy trade relations as edges. A variety of indicators are designed in terms of networks, nodes, bilaterals, and communities to analyze the temporal and spatial evolution of the global energy trade network from 2001 to 2020. The results indicate that network density and strength have been steadily increasing since the beginning of the 21st century. It is observed that the position of the United States as the core of the international energy market is being impacted by emerging developing countries, thus affecting the existing trade balance based on topological analysis. The weighted analysis of bilateral relations demonstrates that emerging countries such as China, Brazil, and Saudi Arabia are pursuing closer cooperation. The community analysis reveals that an increasing number of countries possess strong energy trade capabilities, resulting in a corresponding increase in energy trade volumes. Full article
(This article belongs to the Special Issue Risk Management in Carbon and Oil Markets)
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22 pages, 1856 KiB  
Article
Prediction of Regional Carbon Price in China Based on Secondary Decomposition and Nonlinear Error Correction
by Beibei Hu and Yunhe Cheng
Energies 2023, 16(11), 4444; https://doi.org/10.3390/en16114444 - 31 May 2023
Viewed by 1017
Abstract
Effective prediction of carbon prices matters a great deal for risk management in the carbon financial market. This article designs a blended approach incorporating secondary decomposition and nonlinear error-correction technology to predict the regional carbon price in China. Firstly, the variational mode decomposition [...] Read more.
Effective prediction of carbon prices matters a great deal for risk management in the carbon financial market. This article designs a blended approach incorporating secondary decomposition and nonlinear error-correction technology to predict the regional carbon price in China. Firstly, the variational mode decomposition (VMD) method is used to decompose the carbon price, and then, the time-varying filter-based empirical mode decomposition (TVFEMD) is introduced to decompose the residual term generated by VMD, and the multiple kernel-based extreme learning machine (MKELM) optimized by the sparrow search algorithm (SSA) is innovatively built to forecast the carbon subsequences. Finally, in order to mine the hidden information contained in the forecasted error, the nonlinear error-correction method based on the SSA-MKELM model is introduced to correct the initial prediction of carbon price. The empirical results show that the proposed model improves the prediction accuracy of carbon prices, with RMSE, MAE, MAPE, and DS up to 0.1363, 0.1160, 0.0015, and 0.9231 in Guangdong, respectively. In the case of the Hubei market, the model also performs best. This research innovatively expands the prediction theory and method of China’s regional carbon price. Full article
(This article belongs to the Special Issue Risk Management in Carbon and Oil Markets)
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18 pages, 981 KiB  
Article
Does Environmental Regulation Promote Eco-Innovation Performance of Manufacturing Firms?—Empirical Evidence from China
by Jieqiong Wang, Shichao Hu and Ziyi Zhang
Energies 2023, 16(6), 2899; https://doi.org/10.3390/en16062899 - 21 Mar 2023
Cited by 3 | Viewed by 1529
Abstract
As the world becomes more concerned about carbon emissions, the Chinese government, which is a large contributor to carbon emissions, has also begun to pay attention to the issue of carbon emissions. Environmental regulatory policies have been implemented to improve the environment, but [...] Read more.
As the world becomes more concerned about carbon emissions, the Chinese government, which is a large contributor to carbon emissions, has also begun to pay attention to the issue of carbon emissions. Environmental regulatory policies have been implemented to improve the environment, but are these policies really conducive to improving firms’ eco-innovation performance? This paper empirically investigates the relationship between environmental regulation policies and firms’ eco-innovation performance in China and finds that: firstly, environmental regulation in China is inadequate and that manufacturing eco-innovation performance is generally low; secondly, there is a U-shaped relationship between environmental regulation policies and firms’ eco-innovation performance; thirdly, there is significant industry and regional heterogeneity in the induced effects of environmental regulation tools; and fourthly, there is a mediating effect of industrial agglomeration on the promotion of firms’ eco-innovation performance. The conclusions of this paper are: firstly, that the Chinese government should continue to improve environmental regulations and strictly enforce them so that green becomes the colour of ‘economic recovery’; secondly, that the Chinese government should develop scientific and reasonable environmental regulatory policies according to local conditions; thirdly, that Chinese companies should increase their spending on research and development; and fourthly, that the Chinese government needs to optimise the industrial layout and support mechanisms. The Chinese government should play an active role in industrial agglomeration in technological innovation. Full article
(This article belongs to the Special Issue Risk Management in Carbon and Oil Markets)
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14 pages, 3659 KiB  
Article
Technology Trend Analysis of Japanese Green Vehicle Powertrains Technology Using Patent Citation Data
by Jiaming Jiang and Yu Zhao
Energies 2023, 16(5), 2221; https://doi.org/10.3390/en16052221 - 24 Feb 2023
Cited by 4 | Viewed by 1842
Abstract
As automobiles are major contributors to greenhouse gas emissions, the technological shift towards vehicle powertrain systems is an attempt to lower problems such as emissions of carbon dioxide and nitrogen oxides. Patent data are the most reliable measure of business performance for applied [...] Read more.
As automobiles are major contributors to greenhouse gas emissions, the technological shift towards vehicle powertrain systems is an attempt to lower problems such as emissions of carbon dioxide and nitrogen oxides. Patent data are the most reliable measure of business performance for applied research and development activities when investigating knowledge domains or technology evolution. This is the first study on Japanese patent citation data of the green vehicle powertrains technology industry, using the social network analysis method, which emphasizes centrality estimates and community detection. This study not only elucidates the knowledge by visualizing flow patterns but also provides a precious and congregative method for verifying important patents under the International Patent Classification system and grasping the trend of the new technology industry. This study detects leading companies, not only in terms of the number of patents but also the importance of the patents. The empirical result shows that the International Patent Classification (IPC) class that starts with “B60K”, which includes hybrid electric vehicle (HEV) and battery electric vehicle (BEV), is more likely to be the technology trend in the green vehicle powertrains industry. Full article
(This article belongs to the Special Issue Risk Management in Carbon and Oil Markets)
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