Analysis Of Factors Affecting Carbon Trading Data Under The Background Of Dual Carbon Goal

President Xi Jinping announced at the 75th session of the UN General Assembly that China will strive to achieve carbon neutrality by 2060 and peak its carbon dioxide emissions by 2030.To achieve the "30·60" goal,the carbon market is an indispensable policy tool,and the carbon price is the core of the carbon market operation.Stable,effective and predictable carbon price can motivate enterprises to transform and upgrade,reduce the total cost of social emission reduction,and scientifically and orderly promote carbon peak carbon neutrality.In the context of parallel national unified market and pilot market,this paper takes eight regional carbon markets and national carbon markets as research objects,and selects government pricing power,supply and demand,trading mechanism,weather,energy price,exchange rate and power generation structure as potential influencing factors.The regional carbon market was first launched in 2013,and the carbon price sequence contains the change trend after the government’s pricing ability,supply and demand,and trading mechanism have affected it.Therefore,the fixed effect model in the factor regression model is established to quantify the quantitative impact of three factors on carbon price.Compared with the independence of the regional carbon market,the national carbon market has deeper interaction with domestic and foreign energy markets.Therefore,quantile regression model was established to explore the influence of other factors on carbon price,making the study more practical.Moreover,long-term and short-term memory network model was further established to predict carbon price,confirming the feasibility of carbon price prediction.Based on the above research results,it can be concluded that the change of the number of control and emission enterprises,CCER offset ratio and paid bidding times has a great influence on carbon price.Compared with temperature change and energy price,carbon price is more sensitive to exchange rate change,and low-carbon energy power generation structure is the best driving force to promote carbon price upward.In addition,the accuracy of carbon price prediction of long and short term memory network model can reach 96.73%.Through this study and relevant conclusions,firstly,the pilot advantages can be fully utilized to make up for the weak point of the short operation time of the national carbon market,and provide reference for the improvement of the national carbon market trading regulations;Secondly,it can understand the concrete influence of different factors on Chinese carbon market,so as to provide effective suggestions to solve the problem of low carbon price level and insufficient upward power;Finally,it can effectively improve the trading willingness and price forecasting ability of enterprises,attract more capital into the carbon market,improve the activity of the carbon trading market,and better play the role of the carbon market in energy conservation and emission reduction.