Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Efficiency in Green Investing: A Multifractal Perspective on Sustainability Indexes

Rui Dias
* ORCID logo ,
Mariana Chambino
,
Paula Heliodoro
ORCID logo ,
Paulo Alexandre
,
Cristina Palma
ORCID logo ,
Vanda Martins
,
Ricardo Soares
,
Liliana Almeida
,
Sónia Fernandes
Version 1 : Received: 29 October 2023 / Approved: 30 October 2023 / Online: 30 October 2023 (10:33:16 CET)

How to cite: Dias, R.; Chambino, M.; Heliodoro, P.; Alexandre, P.; Palma, C.; Martins, V.; Soares, R.; Almeida, L.; Fernandes, S. Efficiency in Green Investing: A Multifractal Perspective on Sustainability Indexes. Preprints 2023, 2023101902. https://doi.org/10.20944/preprints202310.1902.v1 Dias, R.; Chambino, M.; Heliodoro, P.; Alexandre, P.; Palma, C.; Martins, V.; Soares, R.; Almeida, L.; Fernandes, S. Efficiency in Green Investing: A Multifractal Perspective on Sustainability Indexes. Preprints 2023, 2023101902. https://doi.org/10.20944/preprints202310.1902.v1

Abstract

The rising global concern for environmental sustainability has driven a surge in green invest-ments' popularity. This study examines the multifractal characteristics and efficiency of various green stock indexes, such as Clean Science and Technology, ISE Clean Edge Global Wind Energy Index, iShares Global Clean Energy ETF, Nasdaq Clean Edge Green Energy, and Solactive Clean Energy. The research covers the period from October 4, 2021, to October 4, 2023. The central ob-jective of this research is to evaluate the efficiency of clean energy stock markets and dissect their influence on investment decisions and market performance in the realm of green investments. To accomplish this, the study employs the Wright test (2000) and the Detrended Fluctuation Analysis (DFA) method. The findings indicate the presence of negative serial autocorrelation within the Rankings and Signals tests. Furthermore, the DFA analysis concurrently reveals long memory patterns in most green indexes, with the notable exception being the Nasdaq Clean Edge index, which exhibits tendencies toward anti-persistence. These results imply that prices inadequately incorporate available information, resulting in non-i.i.d. price fluctuations. These implications are significant for investors, as they indicate the potential for predictable returns and opportunities for arbitrage and abnormal profits, challenging the assumptions of random walk and information efficiency hypotheses.

Keywords

Serial autocorrelation; Stock markets; Green energy; Sustainability

Subject

Business, Economics and Management, Business and Management

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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