Influencing Factors And Prediction Analysis Of Carbon Trading Price Under The ’Double Carbon’ Target

General Secretary Xi Jin Ping has proposed that green mountains are golden mountains and silver mountains to achieve the goal of " double carbon " by 2060,highlighting the responsibility of a big country.As the world ’s largest energy consumer and producer,China ’s carbon market has made great strides.From 2010 to2021,from the first proposal to build a carbon market to the opening of a national carbon market,it means that China ’s low-carbon development has achieved a phased victory.In order to achieve a broader market for new energy transformation,based on this,it is of strategic significance and practical value to deeply explore the influencing factors and internal mechanisms of carbon emission trading prices(hereinafter referred to as carbon trading prices)to predict carbon trading prices and help establish a stable and effective carbon pricing mechanism.Firstly,by combing the relevant literature on the influencing factors of carbon trading price and carbon price prediction,the theoretical characteristics and attributes of carbon emission rights and carbon trading price are deeply explored.At the same time,the index system affecting carbon trading price is constructed from six aspects :economic situation,financial market,international carbon market,energy price,climate environment and Internet big data.Linear interpolation is used to incomplete the data,and finally descriptive statistical analysis is carried out.Secondly,based on the time series data of 23 variables from July 16,2021 to September 1,2022,the influence of six first-level indicators on carbon trading prices is analyzed with the regularized sparse model as the reference point.Through empirical analysis,it is verified that macroeconomic factors and financial markets have a significant impact on carbon trading prices,while the international carbon market and atmospheric environment have no significant impact on carbon trading prices.Internet big data has a small but influential impact on carbon trading prices.Among them,fossil energy prices have a significant impact on carbon trading prices.Natural gas prices are negatively correlated with carbon trading prices,and coal prices are negatively correlated with carbon trading prices.Finally,the prediction of carbon trading price is carried out in the following two aspects.First,the explanatory variables are directly predicted by the LSTM model for single factor prediction,and then all the explanatory variables and explanatory variables are included in the LSTM model for multi-factor prediction.Based on the SVR and LSTM models,eight regularization models such as Lasso,elastic net and elastic MCP are introduced to select variables,and the carbon trading price is predicted and analyzed by constructing a variable combination model.The study found that by comparing and analyzing the accuracy of the prediction results,it is concluded that the combined model has better prediction effect and lower evaluation index,and it is predicted that the carbon trading price will rise steadily from September 1 to September 5,2022.Through empirical results,this paper concludes that the flexible MCP-LSTM combination model can predict carbon trading prices more effectively.Based on the above research and analysis,this paper puts forward suggestions from the aspects of promoting the expansion of the participation scale of the national carbon trading market,optimizing the emission accounting standards and quota allocation schemes,and developing carbon financial derivatives,so as to contribute to the steady development of the national carbon trading market and reduce greenhouse gas emissions.