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A Fuzzy Stochastic Model for Carbon Price Prediction Under the Effect of Demand-related Policy in China's Carbon Market

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  • Song, Yazhi
  • Liu, Tiansen
  • Liang, Dapeng
  • Li, Yin
  • Song, Xiaoqiu

Abstract

The establishment of China's carbon market has an obvious policy-oriented feature, and the carbon price is easily affected by demand-related policies within a compliance period. As prior models cannot help with clear simulation of the volatility of carbon price in China, this paper develops a fuzzy stochastic model to predict such price under the effect of demand-related policy. First, we quantify corporate final profit obtained from carbon trading based on different free allowance policies to measure the actual allowance demand in the carbon market. Second, based on such demand, we add the fuzzy number in each parameter of a stochastic differential equation and then develop a fuzzy stochastic model that can help to analyse the effect of demand-related policy on carbon price in the immature carbon market. Third, by analysing the demand-related policy formulated in the second-developing-phase of the Shanghai Environment and Energy Exchange (from Nov. 17 in 2016) through our model, we predict the price trend after each demand-related policy publication. Experimental results reveal the accurate fitting effect of the developed model that can help to estimate the supply-and-demand in the carbon market and evaluate the effectiveness of current carbon trading policy as well. Further, our model can provide a robust theoretical implication for both corporate carbon trading strategies and governmental regulations on carbon demand-related policy.

Suggested Citation

  • Song, Yazhi & Liu, Tiansen & Liang, Dapeng & Li, Yin & Song, Xiaoqiu, 2019. "A Fuzzy Stochastic Model for Carbon Price Prediction Under the Effect of Demand-related Policy in China's Carbon Market," Ecological Economics, Elsevier, vol. 157(C), pages 253-265.
    • Handle: RePEc:eee:ecolec:v:157:y:2019:i:c:p:253-265
    DOI: 10.1016/j.ecolecon.2018.10.001
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