TY - JOUR
T1 - Co-movement between dirty and clean energy
T2 - A time-frequency perspective
AU - Farid, Saqib
AU - Karim, Sitara
AU - Naeem, Muhammad A.
AU - Nepal, Rabindra
AU - Jamasb, Tooraj
N1 - Publisher Copyright:
© 2023 Elsevier B.V.
PY - 2023/3
Y1 - 2023/3
N2 - In the backdrop of the recent covid-19 pandemic there is a renewed interest to understand the interlinkages between dirty and clean energies. In this regard, the study examines the co-movement structure between clean energy stocks and dirty energies before and during the covid-19 outbreak. The study analyses the interlinkages between the underlying markets by utilizing a vast sample of dirty energies namely crude oil, heating oil, gas oil, gasoline and natural gas, whereas clean energy sector is proxied by S&P Global clean energy index and Wilder Hill clean energy index. We make use of rolling window wavelet approach and wavelet coherence analysis to identify interdependencies between the clean energy stocks and dirty energies. The results exhibit weak linkages between clean energy equities and dirty energies in the short-run, while; we also record few occasions of high co-movements among dirty and clean energy markets in the long-run. Noticeably, a distinct decoupling effect persisted between dirty and clean energy markets. In addition, the findings also illustrate that clean energy market is relatively isolated from dirty energies during the recent pandemic crisis, amplifying portfolio diversification benefits across clean and dirty energy markets. The findings of the study hold meaningful insights for investors, policy makers and other market participants in energy financial markets.
AB - In the backdrop of the recent covid-19 pandemic there is a renewed interest to understand the interlinkages between dirty and clean energies. In this regard, the study examines the co-movement structure between clean energy stocks and dirty energies before and during the covid-19 outbreak. The study analyses the interlinkages between the underlying markets by utilizing a vast sample of dirty energies namely crude oil, heating oil, gas oil, gasoline and natural gas, whereas clean energy sector is proxied by S&P Global clean energy index and Wilder Hill clean energy index. We make use of rolling window wavelet approach and wavelet coherence analysis to identify interdependencies between the clean energy stocks and dirty energies. The results exhibit weak linkages between clean energy equities and dirty energies in the short-run, while; we also record few occasions of high co-movements among dirty and clean energy markets in the long-run. Noticeably, a distinct decoupling effect persisted between dirty and clean energy markets. In addition, the findings also illustrate that clean energy market is relatively isolated from dirty energies during the recent pandemic crisis, amplifying portfolio diversification benefits across clean and dirty energy markets. The findings of the study hold meaningful insights for investors, policy makers and other market participants in energy financial markets.
KW - Clean-energy stocks
KW - Co-movement
KW - Dirty energy markets
KW - Wavelet coherence
KW - Wavelet correlations
UR - http://www.scopus.com/inward/record.url?scp=85147731777&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85147731777&partnerID=8YFLogxK
U2 - 10.1016/j.eneco.2023.106565
DO - 10.1016/j.eneco.2023.106565
M3 - Article
AN - SCOPUS:85147731777
SN - 0140-9883
VL - 119
JO - Energy Economics
JF - Energy Economics
M1 - 106565
ER -