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Are clean energy markets efficient? A multifractal scaling and herding behavior analysis of clean and renewable energy markets before and during the COVID19 pandemic.
Memon, Bilal Ahmed; Aslam, Faheem; Asadova, Shakhnoza; Ferreira, Paulo.
Afiliação
  • Memon BA; School of Business and Economics, Westminster International University in Tashkent, Uzbekistan.
  • Aslam F; Department of Management Sciences, COMSATS University Islamabad, Pakistan.
  • Asadova S; School of Business and Economics, Westminster International University in Tashkent, Uzbekistan.
  • Ferreira P; VALORIZA-Research Center for Endogenous Resource Valorization, 7300-555 Portalegre, Portugal.
Heliyon ; 9(12): e22694, 2023 Dec.
Article em En | MEDLINE | ID: mdl-38213596
ABSTRACT
The literature lacks thorough and adequate evidence of the efficiency and herding behavior of clean and renewable energy markets. Therefore, the key objective of this paper is to explore the multifractality and efficiency of six clean energy markets by applying a robust method of Multifractal detrended fluctuation analysis (MFDFA) on daily data over a lengthy period. In addition, to examine the inner dynamics of clean energy markets around the global pandemic (COVID19), the data are further divided into two sub-periods of before and during COVID19. Our sampled clean energy markets exhibit multifractal behavior with a significant impact on the efficiency and intensified presence of multifractality during the COVID19 period. Overall, TXCT and BSEGRNX were the most efficient clean energy markets, but the ranking of TXCT deteriorated significantly in the sub-periods. The presence of multifractality and herding behavior symmetry intensified during the crisis period, which gives a potential for advancing portfolio management techniques. Moreover, our study provides practical implications and new insights for various market participants for better management and understanding of risks.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article