Carbon Credit Price Research and Forecasting
Abstract
This paper selects Beijing, Shanghai, Shenzhen and Guangdong carbon emission rights from January 2018 to August 2021 as the research objects. The impact of each factor on the price of their carbon credits is studied. Through multiple regression analysis, it is found that only Beijing and Shanghai can pass the model overall significance assumption. Examining the correlation coefficients, it is found that the price of natural gas and oil are negatively correlated with carbon credits, and coal is positively correlated with the price of carbon credits in both places. In this paper, the lenvenberg-marquardt algorithm is selected as the training function and its prediction is made by neural network.
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DOI: http://dx.doi.org/10.18686/fm.v8i4.9476
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