Carbon Markets Based On The Theory Of The Gray Market Price Prediction Research

In the backdrop of the global warming, with the rapid development of social economy, the sustainable development will also increasingly highlighted. The signing of the Kyoto protocol to North America and European Union countries have to form a carbon market trading activities. On June 18,2013, shenzhen launched the first domestic carbon emissions trading market, China’s carbon trading market also started from that moment on. In the face of the increasingly active carbon emissions trading on the market, to a need for carbon trading decisions, fully grasp the future carbon trading prices over a period of time is very necessary.This article will obtain from the following three aspects to study how to make use of grey theory for carbon trading price forecasts. First of all, according to China’s current trading mechanism of carbon trading market and operation condition, analyze the related factors affecting enterprise for carbon trading decision, and on this basis, establish enterprise decision-making path; Secondly, based on the research of the decision-making path, exert important influence factors in the decision path, this paper puts forward the basic idea of grey prediction model was constructed, and then combined with the difficulty in the carbon market price prediction, and the characteristics of the grey theory, analyzes the GM (1,1) prediction model to predict the feasibility of reality, and set up GM (1,1) forecast model and the optimization of prediction model GM (1,1); Lastly, China’s carbon emissions trading in the pilot carbon trading prices as a case study object, respectively, using GM (1,1) forecast model and GM (1,1) to optimize the forecasting model to forecast the price of carbon trading.Research shows that there are many factors that affect enterprise carbon trading decisions, such as the enterprise internal environment, policy, system, market trading environment and so on, according to these factors, it is concluded that enterprise path for carbon trading decisions. In the realistic society, the enterprise can not only to the identity of the buyer to participate in the carbon emissions trading, but also to the identity of the seller to participate in the carbon emissions trading, that is to say, no matter in what capacity for enterprise carbon emissions trading, all need a template system and valuable price forecast for reference. By positive we can see that the end of this article, using GM (1,1) model and residual correction of GM (1,1) optimal model for carbon emissions trading price forecasting, the result is satisfactory.