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Option pricing of carbon asset and its application in digital decision-making of carbon asset

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  • Liu, Yue
  • Tian, Lixin
  • Sun, Huaping
  • Zhang, Xiling
  • Kong, Chuimin

Abstract

Carbon emission allowances are issued to limit the carbon emission by enterprises, but some unforeseen variables may cause their demand unpredictable. Together with the high volatility of carbon price dynamic, management of carbon asset is of great significance and difficulty for those enterprises with heavy carbon consumption. To cope with the demand and price uncertainty of carbon emission right, carbon derivative provides a feasible solution for those enterprises. This paper proposes applying the carbon option for carbon management. For better applying this tool, carbon option is evaluated through a geometric Brownian motion model with regime-switching. Based on the value estimation and analysis of carbon option, decision making and strategy design for carbon asset management are achieved by the quantitative results of option pricing and digital detection during the operation. Development of the modeling and algorithm for carbon option pricing is the main theoretical contribution, also it enriches the theory of real option property of carbon. Moreover, it provides a detailed schema and an inspiring case study of applying the options for carbon asset management and facilitating the decision-making digitally in line with the market information constantly updated, and it is applicable and believed to optimize the risk control for all enterprises with carbon-consumption.

Suggested Citation

  • Liu, Yue & Tian, Lixin & Sun, Huaping & Zhang, Xiling & Kong, Chuimin, 2022. "Option pricing of carbon asset and its application in digital decision-making of carbon asset," Applied Energy, Elsevier, vol. 310(C).
    • Handle: RePEc:eee:appene:v:310:y:2022:i:c:s0306261921016160
    DOI: 10.1016/j.apenergy.2021.118375
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    Cited by:

    1. Liu, Yue & Sun, Huaping & Meng, Bo & Jin, Shunlin & Chen, Bin, 2023. "How to purchase carbon emission right optimally for energy-consuming enterprises? Analysis based on optimal stopping model," Energy Economics, Elsevier, vol. 124(C).
    2. Yelin Dai & Yue Liu & Xuhui Ding & Chundu Wu & Yu Chen, 2022. "Environmental Regulation Promotes Eco-Efficiency through Industrial Transfer: Evidence from the Yangtze River Economic Belt in China," IJERPH, MDPI, vol. 19(16), pages 1-31, August.
    3. Yue Qi & Yue Wang, 2023. "Innovating and Pricing Carbon-Offset Options of Asian Styles on the Basis of Jump Diffusions and Fractal Brownian Motions," Mathematics, MDPI, vol. 11(16), pages 1-22, August.
    4. Luo, Haizhi & Li, Yingyue & Gao, Xinyu & Meng, Xiangzhao & Yang, Xiaohu & Yan, Jinyue, 2023. "Carbon emission prediction model of prefecture-level administrative region: A land-use-based case study of Xi'an city, China," Applied Energy, Elsevier, vol. 348(C).

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