摘要
科学预测碳排放权交易价格对我国碳排放市场建设以及“双碳”目标实现具有重要意义。本文在综合考虑能源价格、气候环境、国际碳排放权交易市场以及工业发展水平等多种影响因素后,引入LSTM算法对碳排放权交易价格进行多因素预测,并将实证结果与单因素预测相对照,实证结果发现:多因素预测比单一因素预测更加精准,能够有效地预测未来短期碳排放权交易价格的趋势与波动,为市场参与者的交易策略提供参考依据,发挥其价格信号功能,从而进一步推进我国碳排放交易市场的发展与稳定。
Scientifically predicting carbon emission trading prices is of significant importance for the development of China's carbon emission market and the achievement of the carbon peaking and carbon neutrality goals.This study comprehensively considers various influencing factors such as energy prices,climate environment,international carbon emission trading market,and industrial development level,the LSTM algorithm is introduced to conduct multi-factor prediction of carbon emission trading prices,and the empirical results are compared with single-factor predictions.The empirical results show that:multi-factor prediction is more accurate than single-factor prediction.It can effectively forecast the trend and volatility of future short-term carbon emission trading prices,providing reference for market participants'trading strategies and leveraging its price signaling function.This further promotes the development and stability of China's carbon emission trading market.
作者
沈蕾
罗梦丝
SHEN Lei;LUO Mengsi
出处
《价格理论与实践》
北大核心
2022年第7期64-68,共5页
Price:Theory & Practice
