Abstract
The carbon market is recognized as the most effective means for reducing global carbon dioxide emissions. Effective carbon price forecasting can help the carbon market to solve environmental problems at a lower economic cost. However, the existing studies focus on the carbon premium explanation from the perspective of return and volatility spillover under the framework of the mean-variance low-order moment. Specifically, the time-varying, high-order moment shock of market asymmetry and extreme policies on carbon price have been ignored. The innovation of this paper is constructing a new hybrid model, NAGARCHSK-GRU, that is consistent with the special characteristics of the carbon market. In the proposed model, the NAGARCHSK model is designed to extract the time-varying, high-order moment parameter characteristics of carbon price, and the multilayer GRU model is used to train the obtained time-varying parameter and improve the forecasting accuracy. The results conclude that the NAGARCHSK-GRU model has better accuracy and robustness for forecasting carbon price. Moreover, the long-term forecasting performance has been proved. This conclusion proves the rationality of incorporating the time-varying impact of asymmetric information and extreme factors into the forecasting model, and contributes to a powerful reference for investors to formulate investment strategies and assist a reduction in carbon emissions.
Highlights
The multilayer GRU network model is designed to realize the nonlinear prediction based on the time-varying, high-order moment parameters estimated by the NAGARCHSK model
We use the NAGARCHSK model to estimate the time-varying, high-order moment parameter characteristics that represent the shock from the asymmetric information and extreme external impact
It is worth noting that the NAGARCHSK-LSTM model, which still has obvious forecasting advantages in error evaluation criteria and is relatively better has the advantage in fitting financial time series, has the worst performance in carbon in market-expected criteria compared with other benchmark models
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. The continuous growth of carbon dioxide emissions leads to the rise of global temperature, triggers sea-level rise, aggravates glacier melting and other severe environmental problems, and threatens human health, and affects the sustainability of global economy and human civilization. It has become an urgent task for human society to effectively curb the global climate problems and reduce greenhouse gas emissions. Studying the pricing mechanism of the carbon market in this paper can better serve the emission reduction practice of entity enterprises and create a healthier social environment. The structure of this paper is as follows: the second part is the literature review; the third section analyzes the econometric model; the fourth section is the empirical analysis and discussion; the last part summarizes the conclusion and the prospects
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