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Research On Maturity Measurement And Risk Management Of China's Carbon Market

Posted on:2021-02-20Degree:MasterType:Thesis
Country:ChinaCandidate:X X ZhouFull Text:PDF
GTID:2381330647961865Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
Global climate change has become one of the major challenges of human sustainable development in the 21 st century.Carbon market can effectively cope with climate change through carbon pricing control and emission reduction,which has attracted the attention of many countries and regions,including China.Since June 2013,China has set up seven carbon markets in Shenzhen,Beijing,Shanghai,Guangdong,Tianjin,Hubei and Chongqing,and launched the construction of national unified carbon market in December2017.In order to further understand the development status of carbon market,explore the problems exposed in the operation of carbon market and accumulated successful experiences,and form the theoretical basis for the construction of China's unified carbon market.It's necessary to scientifically meaure the maturity of China's carbon market.The maturity of carbon market is the reflection of market operation quality,and also the basis of price discovery and risk management.China's carbon market has been established for a relatively short time,with a large fluctuation of carbon price,and carbon financial risks often occur and gather.On the basis of measuring the maturity,choosing the appropriate model to measure the market risk,studying the risk spillover effect between markets,and managing the risk of the carbon market will help to prevent and control the risk of carbon market and ensure the healthy operation of the unified carbon market.In view of this,this paper studies the maturity and risk management of China's carbon market.In order to measure the maturity of carbon market,the carbon market maturity evaluation index is constructed from three dimensions of internal factor,external factor and interface factor,and the entropy-based TOPSIS model is adopted.In this model,entropy method is used to objectively weight the indicators,and TOPSIS method is used to measure the maturity of seven carbon markets in China.On the basis of maturity measurement,we study the risk management of China's carbon market.Va R and CVa R are used to measure the risks of seven carbon markets in Beijing,Shanghai,Guangdong,Tianjin,Hubei,Shenzhen and Chongqing.GARCH-R-Vine Copula-Co ES model is used to measure the risk spillover effects among three carbon markets with large trading volume in Guangdong,Hubei and Shenzhen.There're two empirical results.The first shows that the maturity of China's carbon market is relatively low as a whole,and there're significant differences among seven carbon markets.Hubei,Guangdong,Beijing,Shenzhen and Shanghai are in the development stage towards mature markets,while Chongqing and Tianjin are not mature.In 2019,the market maturity of Guangdong is the highest,reaching 0.7153.Beijing,Hubei,Shanghai,Shenzhen and Chongqing are the second,reaching 0.5885,0.5838,0.5249,0.4197 and 0.3684 respectively.Tianjin is the lowest,only 0.3585.The second shows that CVa R method can better measure the tail risk of the market.China's carbon market is still in its infancy stage,the development of market mechanism is not sound,and there are greater risks in the carbon market.Among which Chongqing,Tianjin and Shenzhen have greater risks,Hubei and Guangdong have less risks.Only Guangdong and Shenzhen have a risk spillover effect,while Hubei and Shenzhen,Hubei and Guangdong have no risk spillover effect.Finally,we put forward policy suggestions to improve the maturity and manage the market risk from six dimensions of controlling market risk reasonably,improving the accuracy of quota allocation,connecting regional pilot with the national unified carbon market,building a carbon financial risk early warning system,improving the legal system of risk management and strengthening carbon market risk management supervision.
Keywords/Search Tags:Carbon market maturity, Entropy-based TOPSIS model, CVaR, Risk spillover effect, R-Vine Copula-CoES model
PDF Full Text Request
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