Price forecasting algorithm of carbon emission rights under multiscale fractal characteristics
YANG Xing
LIANG Jing-li
JIANG Jin-liang
MI Jun-long
Abstract：In this paper,the daubechies wavelet--genetic algorithm--radial basis function neural network(Db3--GA--RBF) model is constructed by nonlinear paradigm,and the price forecasting problem of European Union carbon emissions market (EU--ETS)is discussed. The research showed that: 1)The European Union allowance(EUA)spot price fluctuation in the three stage of the EU carbon emissions market has the characteristics of local scale diversity,and the third stage carbon price series has the strongest multifractal characteristics.Essentially,the carbon emission rights market is a multifractal and chaotic market;2)The Db3--GA--RBF model can effectively improve the accuracy of data and the generalization ability of the model, and make the prediction accuracy of the model stronger; 3)Compared with other forecasting models, the prediction accuracy of Db3--GA--RBF(SIC)model based on Schwartz's information criterion(SIC)is improved by about 70%.
Keywords：EU carbon emissions marketfractal and chaoswavelet decompositionradial basis function networkspredictive analytics
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 224-231 )