Research On The Price Prediction Of Carbon Emission Trading In China

Carbon emission is the main cause of global warming.Many countries have been focusing on carbon emission reduction to solve the climate change problem of global warming.Carbon emission trading market is an important way to reduce carbon emission and deal with global climate change.As one of the largest carbon emitting countries,China attaches great importance to global climate change.Since 2013,the pilot market of carbon emission trading has been launched successively,and the national unified carbon emission trading market was launched in July 2021,aiming to use the market mechanism to save energy and reduce emissions,achieve green and low-carbon development,and contribute to solving the problem of global climate change.Taking the carbon emission trading market in the pilot area where China started earlier and the market mechanism is relatively mature as an example,this paper studies the influencing factors causing the price fluctuation of China’s carbon emission trading market,and studies the fitting and prediction of the fluctuation trend of the carbon emission trading price,in order to promote the better development of the carbon emission trading market and achieve the double carbon goal.Combined with the development of carbon emission trading market in China’s pilot areas,this paper compares,summarizes and analyzes the factors affecting the price fluctuation of carbon emission trading in China,studies the influence and change relationship of various factor variables by constructing VAR model,and further constructs lstm-arima prediction model to predict the price of carbon emission trading.In order to verify the applicability of the model,three pilot carbon emission trading markets in Hubei,Guangdong and Beijing are selected for verification.Firstly,in the research on the influencing factors of carbon emission trading price,coal price,HS300 index,oil price,air quality index,euro exchange rate and LNG price are selected as factor index variables.In order to understand the influence mechanism of each influencing factor variable on carbon emission trading price,VAR model is constructed for empirical research.The results show that the trading price of carbon emission rights is most affected by its own historical price.The influence effects of energy price factors,macroeconomic factors and weather factors are not different,which are lower than energy price.The influence of international market factors is relatively small,and the influence profile of factors among regions is slightly different.Secondly,in the prediction of carbon emission trading price,from the perspective of single feature input and multifeature input,that is,the price fluctuation trend is predicted based on the historical data of carbon emission trading price and the influencing factors of carbon emission trading price respectively.The long-term and short-term memory neural network model(LSTM)is used to model and predict the carbon emission trading price,and then autoregressive integrated moving average model(ARIMA)is used to correct the error.Through empirical research,the results show that the prediction effect of lstm-arima prediction model is good,which verifies the applicability and effectiveness of lstm-arima prediction model in carbon emission trading price prediction.Finally,through the comprehensive analysis of the empirical results,combined with China’s national conditions,this paper puts forward some policy suggestions on stabilizing China’s carbon emission trading market.