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Quantifying information transfer among clean energy, carbon, oil, and precious metals: A novel transfer entropy-based approach

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  • Dhifaoui, Zouhaier
  • Khalfaoui, Rabeh
  • Abedin, Mohammad Zoynul
  • Shi, Baofeng

Abstract

Measuring the strength and direction of information flow between markets plays a vital role for investors and policymakers. In this study, we propose a novel approach: the empirical mode decomposition variable lag relative transfer entropy (EMD-VL relative transfer entropy) to assess the pairwise relative causal information transfer over time and scale. Using clean and dirty energy, carbon, and precious metals, we show strong evidence of bidirectional causal information transmission between markets over time-frequency domain.

Suggested Citation

  • Dhifaoui, Zouhaier & Khalfaoui, Rabeh & Abedin, Mohammad Zoynul & Shi, Baofeng, 2022. "Quantifying information transfer among clean energy, carbon, oil, and precious metals: A novel transfer entropy-based approach," Finance Research Letters, Elsevier, vol. 49(C).
    • Handle: RePEc:eee:finlet:v:49:y:2022:i:c:s1544612322003610
    DOI: 10.1016/j.frl.2022.103138
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    Cited by:

    1. Chai, Shanglei & Yang, Xiaoli & Zhang, Zhen & Abedin, Mohammad Zoynul & Lucey, Brian, 2022. "Regional imbalances of market efficiency in China’s pilot emission trading schemes (ETS): A multifractal perspective," Research in International Business and Finance, Elsevier, vol. 63(C).
    2. Liu, Ying Lin & Zhang, Jing Jie & Fang, Yan, 2023. "The driving factors of China's carbon prices: Evidence from using ICEEMDAN-HC method and quantile regression," Finance Research Letters, Elsevier, vol. 54(C).
    3. Zouhaier Dhifaoui & Kaies Ncibi & Faicel Gasmi & Abulmajeed Abdallah Alqarni, 2023. "The Nexus between Climate Change and Geopolitical Risk Index in Saudi Arabia Based on the Fourier-Domain Transfer Entropy Spectrum Method," Sustainability, MDPI, vol. 15(18), pages 1-22, September.
    4. Bouteska, Ahmed & Hajek, Petr & Fisher, Ben & Abedin, Mohammad Zoynul, 2023. "Nonlinearity in forecasting energy commodity prices: Evidence from a focused time-delayed neural network," Research in International Business and Finance, Elsevier, vol. 64(C).

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