Abstract
Carbon trading price is the core component of the carbon emission trading market. Accurate carbon trading price prediction is of great significance for forming an effective carbon trading market and achieving the "dual carbon" goal. Based on the carbon trading price data in China Emissions Exchange, this paper predicts the carbon trading price through the proposed hybrid model of SSA+LSTM. After comparing with the classical methods based on econometrics, machine learning and deep learning, it is found that the prediction model proposed in this paper achieves the optimal values of RMSE and MAE, and is a relatively effective carbon trading price prediction model.
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