Forecasting China’s carbon emissions trading volume by an improved weighted grey power model

Abstract

ABSTRACT China’s carbon emissions trading volume has been increasing rapidly since the online trading system was officially launched in July 2021. China’s annual carbon emissions trading volume is 246 million tons in 2021, 1.74 times that of 2020. To study this uncertain market, this study proposes an improved weighted Hausdorf fractional discrete grey power model (WDGPM) to predict the market size of China’s emissions trading volume. The WDGPM’s discrete structure avoids complex integral calculation, which improves the calculation efficiency and accuracy. The proposed WDGPM model includes an interactive power structure term that performs well in the nonlinear prediction task. Furthermore, a new information parameter is introduced to construct the weight function of the weighted least squares method, which distinguishes the temporal differences of observations. A sparrow search algorithm is used to optimize the two hyperparameters of the WDGPM model. Numerical examples show the effectiveness of the proposed method, with forecast results indicating that the proposed WDGPM has higher accuracy than other competitive algorithms. The expected trading volume of China’s emissions trading market is projected to reach 466.84 million tons in 2025, with an annual growth rate of 17%, which is 1.9 times that of 2021.