Correlation between CBCFI and Carbon Trading Price Mining from An Econometric Perspective

Abstract

As China's carbon emissions trading market continues to develop, the study of factors affecting carbon trading prices has become increasingly important. Data mining is a kind of analyzing technology of considering from the data itself, carrying on the scientific classification, estimation, prediction, and sequence pattern mining. The mining process is capable to provide good support for decision making. Data mining also has certain applications in carbon trading price analysis. This paper investigates the relationship between carbon trading price and CBCFI based on econometric methods, so as to obtain more accurate data analysis results, and provide more reliable trading strategies for carbon rights trading. Econometrics, a comprehensive discipline combining statistics, computer science and economics, has been widely used in the field of carbon emissions trading and is an excellent choice to study the correlation between China's coastal coal transportation price index and carbon trading prices. We constructed a VAR model using the China Coastal Coal Transportation Price Index and the China Carbon Emissions Trading Market Index to determine the mechanism of the relationship between these two indices. According to the results of this study, there is a one-way Granger causality between the carbon emission trading price and the China carbon market price index. Moreover, a hybrid nonlinear model of VAR and BP was constructed to forecast the CBCFI and carbon trading price, where results indicated the nonlinear combination model work well with both objects.