A decision-making model for emission trading based on ABM

Canqi Liu; Xuemei Tang; Lina Wu

doi:10.1117/12.2660141

3 February 2023 A decision-making model for emission trading based on ABM

Canqi Liu, Xuemei Tang, Lina Wu

Proceedings Volume 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022); 125110D (2023) https://doi.org/10.1117/12.2660141
Event: Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 2022, Hulun Buir, China

Abstract

Carbon price forecasting is used to assist emission-regulated firms in decision-making in trading. Based on the ABM method and trading rules of China’s emission trading markets, in this study, we build a decision-making model for emission trading. The model takes into account factors such as risk preference and emission reduction costs for different types of emission-regulated firms. By setting initial values, adjustable parameters, and input variables, the model simulates emission trading decision-making strategies and carbon price trends in different scenarios. In this article, we selected 2,162 emission-regulated firms in China’s national emission trading market for simulation. The results show that the proportion of sellers participating in the market and the proportion of free allowance allocation have a significant impact on the carbon price fluctuations; the introduction of the auction mechanism will cause short-term fluctuations in carbon prices. Through simulation of emission trading decision-making and carbon price forecasting, the model assists emission-regulated firms to minimize their emission regulation compliance costs, and prevent in advance the price and liquidity risks in emission trading markets.

Citation Download Citation

Canqi Liu, Xuemei Tang, and Lina Wu "A decision-making model for emission trading based on ABM", Proc. SPIE 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 125110D (3 February 2023); https://doi.org/10.1117/12.2660141

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