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Abstract(s)
The energy markets have recently undergone important transformations (e.g. deregulation, technological
progress, renewable energy deployment and changing energy consumer behaviour) and witnessed a
variety of crisis periods, affecting the relationships among energy commodities and their interactions
with clean energy indices. This has implications for price discovery, asset allocation and risk management, which requires in-depth analysis to uncover and identify which energy indices (or forms of energy) lead others or are the most influential, while accounting for asymmetry and non-linearity
characteristics. To uncover the complex structure of the relationship across the returns of seven different
energy commodities and two clean energy stock indices, we apply Granger causality and transfer entropy
in both static and dynamic approaches. The results from the Granger causality analysis identify the influence of the other energy products on natural gas, whereas the transfer entropy analysis reveals the
importance of WTI oil and the influence of clean energy indices. Diesel is the most influenced energy
commodity. A rolling windows analysis confirms those findings and shows evidence of a time-variation
that reflects the impacts of crisis periods, especially the pandemic, on the dynamics of relationships
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Keywords
Energy markets Clean and dirty energy assets Granger causality Transfer entropy Influencer
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