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A novel method of detecting carbon asset price jump characteristics based on significant information shocks

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  • Pan, Di
  • Zhang, Chen
  • Zhu, Dandan
  • Ji, Yuanpu
  • Cao, Wei

Abstract

To identify the jump forms of carbon asset price under the shocks of significant information, this paper focuses on two aspects: different jump directions and jump time points. Therefore, a method for simultaneously optimizing time window size and threshold of the LM jump test is proposed. This optimized method has reduced the omission of jump points and improves the effectiveness of the model. Results show that the shocks of significant information cause large magnitude and asymmetric successive jumps of carbon asset price. A downward high-frequency jump indicates that the downward risk of carbon market is significant, and policy events have the biggest impact on the carbon market, which leads to the biggest jump magnitude. This research helps improve the efficiency of carbon pricing, provides practical guidance for decision process of enterprises, and prevents risk in a timely manner.

Suggested Citation

  • Pan, Di & Zhang, Chen & Zhu, Dandan & Ji, Yuanpu & Cao, Wei, 2022. "A novel method of detecting carbon asset price jump characteristics based on significant information shocks," Finance Research Letters, Elsevier, vol. 47(PA).
    • Handle: RePEc:eee:finlet:v:47:y:2022:i:pa:s1544612321005638
    DOI: 10.1016/j.frl.2021.102626
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    Cited by:

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    2. Song, Yuping & Huang, Jiefei & Zhang, Qichao & Xu, Yang, 2024. "Heterogeneity effect of positive and negative jumps on the realized volatility: Evidence from China," Economic Modelling, Elsevier, vol. 136(C).

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