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Correlation and causality between carbon and energy markets: a complexity perspective.
Jiuli Yin1, Yan Zhu1, Xinghua Fan2
1Center for Energy Development and Environmental Protection Strategy Research, Jiangsu University, Zhenjiang, 212013, China.
Environmental Science and Pollution Research International
|November 18, 2022
Summary
Global warming necessitates understanding carbon and energy markets. This study reveals the carbon market is less complex than energy markets, with significant information flow and a 50-unit time delay influencing their dynamic relationship.
Area of Science:
- Environmental Economics
- Financial Market Analysis
- Complexity Science
Background:
- Global warming drives the need to analyze carbon and energy market interdependencies.
- Understanding market complexity and causality is crucial for effective policy and investment.
Purpose of the Study:
- To investigate the complex relationship between Chinese carbon and energy markets.
- To quantify market complexities, identify time delays, and analyze causality.
Main Methods:
- Multi-scale fuzzy entropy to measure market complexity.
- Pearson correlation and detrended cross-correlation analysis to identify time delays.
- Transfer entropy to explore causality.
Main Results:
- The carbon market exhibits lower complexity than energy markets.
- Market complexity is higher at smaller time scales.
- A critical time delay of approximately 50 units maximizes market correlation.
- Causality varies: carbon market expectations influence oil, gas, and coal; electricity and new energy impact the carbon market; coal and carbon markets show cross-causality.
Conclusions:
- Significant information transmission exists between carbon and energy markets.
- Market participants should monitor interdependencies and dynamic complexity.
- Findings offer insights for navigating climate change mitigation strategies.
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