IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i9p3937-d1140829.html
   My bibliography  Save this article

Clean Energy Action Index Efficiency: An Analysis in Global Uncertainty Contexts

Author

Listed:
  • Rui Dias

    (ESCE, Instituto Politécnico de Setúbal, 2910-761 Setúbal, Portugal)

  • Nicole Horta

    (ESCE, Instituto Politécnico de Setúbal, 2910-761 Setúbal, Portugal)

  • Mariana Chambino

    (ESCE, Instituto Politécnico de Setúbal, 2910-761 Setúbal, Portugal)

Abstract

Climate change, the scarcity of fossil fuels, advances in clean energy, and volatility of crude oil prices have led to the recognition of clean energy as a viable alternative to dirty energy. This paper investigates the multifractal scaling behavior and efficiency of green finance markets, as well as traditional markets such as gold, crude oil, and natural gas between 1 January 2018, and 9 March 2023. To test the serial dependency (autocorrelation) and the efficient market hypothesis, in its weak form, we employed the Lo and Mackinlay test and the DFA method. The empirical findings showed that returns data series exhibit signs of (in)efficiency. Additionally, there is a negative autocorrelation among the crude oil market, the Clean Energy Fuels Index, the Global Clean Energy Index, the gold market, and the natural gas market. Arbitration strategies can be used to obtain abnormal returns, but caution should be exercised as prices may increase above their actual market value and reduce the profitability of trading. This work contributes to the body of knowledge on sustainable finance by teaching investors how to use predictive strategies on the future values of their investments.

Suggested Citation

  • Rui Dias & Nicole Horta & Mariana Chambino, 2023. "Clean Energy Action Index Efficiency: An Analysis in Global Uncertainty Contexts," Energies, MDPI, vol. 16(9), pages 1-18, May.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:9:p:3937-:d:1140829
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/9/3937/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/9/3937/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Takashi Kanamura, 2022. "A model of price correlations between clean energy indices and energy commodities," Journal of Sustainable Finance & Investment, Taylor & Francis Journals, vol. 12(2), pages 319-359, April.
    2. Benlagha, Noureddine & Karim, Sitara & Naeem, Muhammad Abubakr & Lucey, Brian M. & Vigne, Samuel A., 2022. "Risk connectedness between energy and stock markets: Evidence from oil importing and exporting countries," Energy Economics, Elsevier, vol. 115(C).
    3. Kristjanpoller, Werner & Bouri, Elie, 2019. "Asymmetric multifractal cross-correlations between the main world currencies and the main cryptocurrencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1057-1071.
    4. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    5. Yeonjeong Lee & Seong-Min Yoon, 2020. "Dynamic Spillover and Hedging among Carbon, Biofuel and Oil," Energies, MDPI, vol. 13(17), pages 1-19, August.
    6. Gong, Xu & Liu, Yun & Wang, Xiong, 2021. "Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method," International Review of Financial Analysis, Elsevier, vol. 76(C).
    7. Gustafsson, Robert & Dutta, Anupam & Bouri, Elie, 2022. "Are energy metals hedges or safe havens for clean energy stock returns?," Energy, Elsevier, vol. 244(PA).
    8. Shahzad, Syed Jawad Hussain & Nor, Safwan Mohd & Mensi, Walid & Kumar, Ronald Ravinesh, 2017. "Examining the efficiency and interdependence of US credit and stock markets through MF-DFA and MF-DXA approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 351-363.
    9. Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
    10. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    11. Fernanda Fuentes & Rodrigo Herrera, 2020. "Dynamics of Connectedness in Clean Energy Stocks," Energies, MDPI, vol. 13(14), pages 1-19, July.
    12. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    13. Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh, 2021. "Dynamic frequency relationships and volatility spillovers in natural gas, crude oil, gas oil, gasoline, and heating oil markets: Implications for portfolio management," Resources Policy, Elsevier, vol. 73(C).
    14. Yao, Can-Zhong & Mo, Yi-Na & Zhang, Ze-Kun, 2021. "A study of the efficiency of the Chinese clean energy stock market and its correlation with the crude oil market based on an asymmetric multifractal scaling behavior analysis," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    15. Özgür Arslan-Ayaydin & James Thewissen, 2016. "The financial reward for environmental performance in the energy sector," Energy & Environment, , vol. 27(3-4), pages 389-413, May.
    16. Uddin, Gazi Salah & Rahman, Md Lutfur & Hedström, Axel & Ahmed, Ali, 2019. "Cross-quantilogram-based correlation and dependence between renewable energy stock and other asset classes," Energy Economics, Elsevier, vol. 80(C), pages 743-759.
    17. Wan, Daoxia & Xue, Rui & Linnenluecke, Martina & Tian, Jinfang & Shan, Yuli, 2021. "The impact of investor attention during COVID-19 on investment in clean energy versus fossil fuel firms," Finance Research Letters, Elsevier, vol. 43(C).
    18. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    19. Qin, Yun & Hong, Kairong & Chen, Jinyu & Zhang, Zitao, 2020. "Asymmetric effects of geopolitical risks on energy returns and volatility under different market conditions," Energy Economics, Elsevier, vol. 90(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rosa Galvão & Rui Dias, 2024. "Asymmetric Efficiency: Contrasting Sustainable Energy Indices with Dirty Cryptocurrencies," Financial Economics Letters, Anser Press, vol. 3(1), pages 28-39, January.
    2. Rui Dias & Mariana Chambino & Rosa Galvão & Paulo Alexandre & Mohammad Irfan, 2024. "Side Effects and Interactions: Exploring the Relationship between Dirty and Green Cryptocurrencies and Clean Energy Stock Indices," International Journal of Energy Economics and Policy, Econjournals, vol. 14(3), pages 411-416, May.
    3. Rui Dias & Nuno Teixeira & Paulo Alexandre & Mariana Chambino, 2023. "Exploring the Connection between Clean and Dirty Energy: Implications for the Transition to a Carbon-Resilient Economy," Energies, MDPI, vol. 16(13), pages 1-21, June.
    4. Rui Manuel Dias & Mariana Chambino & Nuno Teixeira & Paulo Alexandre & Paula Heliodoro, 2023. "Balancing Portfolios with Metals: A Safe Haven for Green Energy Investors?," Energies, MDPI, vol. 16(20), pages 1-21, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Derick Quintino & Cristiane Ogino & Inzamam Ul Haq & Paulo Ferreira & Márcia Oliveira, 2023. "An Analysis of Dynamic Correlations among Oil, Natural Gas and Ethanol Markets: New Evidence from the Pre- and Post-COVID-19 Crisis," Energies, MDPI, vol. 16(5), pages 1-14, February.
    2. Pourazarm, Elham & Cooray, Arusha, 2013. "Estimating and forecasting residential electricity demand in Iran," Economic Modelling, Elsevier, vol. 35(C), pages 546-558.
    3. Kul B. Luintel, 2000. "Real exchange rate behaviour: evidence from black markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(2), pages 161-185.
    4. à ureo Manuel & Rui Dias & Rosa Galvão & Miguel Varela, 2024. "Analysing Financial Market Integration between Stock and Precious Metals Indices," International Journal of Economics and Financial Issues, Econjournals, vol. 14(4), pages 222-238, July.
    5. Neaime, Simon, 2015. "Are emerging MENA stock markets mean reverting? A Monte Carlo simulation," Finance Research Letters, Elsevier, vol. 13(C), pages 74-80.
    6. Peter Farkas & Laszlo Matyas, 2015. "Testing for Unit Roots in Panel Data with Boundary Crossing Counts," CEU Working Papers 2015_5, Department of Economics, Central European University, revised 03 Nov 2015.
    7. Bosker, Maarten & Brakman, Steven & Garretsen, Harry & Schramm, Marc, 2008. "A century of shocks: The evolution of the German city size distribution 1925-1999," Regional Science and Urban Economics, Elsevier, vol. 38(4), pages 330-347, July.
    8. Olimpia Neagu, 2019. "The Link between Economic Complexity and Carbon Emissions in the European Union Countries: A Model Based on the Environmental Kuznets Curve (EKC) Approach," Sustainability, MDPI, vol. 11(17), pages 1-27, August.
    9. Cheng Hsiao, 2007. "Panel data analysis—advantages and challenges," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(1), pages 1-22, May.
    10. Wilman-Santiago Ochoa-Moreno & Byron Alejandro Quito & Carlos Andrés Moreno-Hurtado, 2021. "Foreign Direct Investment and Environmental Quality: Revisiting the EKC in Latin American Countries," Sustainability, MDPI, vol. 13(22), pages 1-18, November.
    11. Campo, Jacobo & Mendoza, Henry, 2018. "Gasto público y crecimiento económico: un análisis regional para Colombia, 1984-2012," Revista Lecturas de Economía, Universidad de Antioquia, CIE, issue 88, pages 77-108, January.
    12. Tsangyao Chang & Tsung-Pao Wu & Rangan Gupta, 2015. "Are house prices in South Africa really nonstationary? Evidence from SPSM-based panel KSS test with a Fourier function," Applied Economics, Taylor & Francis Journals, vol. 47(1), pages 32-53, January.
    13. Valérie Mignon & Christophe Hurlin, 2005. "Une synthèse des tests de racine unitaire sur données de panel," Économie et Prévision, Programme National Persée, vol. 169(3), pages 253-294.
    14. Carlos Alberto Barreto Nieto & Jacobo Campo Robledo, 2012. "Relación a largo plazo entre consumo de energía y PIB en América Latina: Una evaluación empírica con datos panel," Revista Ecos de Economía, Universidad EAFIT, October.
    15. Hakimi, Abdelaziz & Hamdi, Helmi, 2016. "Trade liberalization, FDI inflows, environmental quality and economic growth: A comparative analysis between Tunisia and Morocco," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1445-1456.
    16. Guneratne B Wickremasinghe & Jae H Kim, 2008. "Weak-Form Efficiency of Foreign Exchange Markets of Developing Economies," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 7(2), pages 169-196, August.
    17. Alberto Bagnai, 2010. "CEEC vs. PIGS: a comparative panel assessment of financial sustainability and twin deficits," Working Papers LuissLab 1088, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    18. Francis M. Kemegue & Marthinus C. Breitenbach & Mulatu F. Zerihun, 2015. "Assessment of Monetary Union in SADC: Evidence from Cointegration and Panel Unit Root Tests," Working Papers 495, Economic Research Southern Africa.
    19. Yaya, OlaOluwa S & Ogbonna, Ephraim A & Furuoka, Fumitaka & Gil-Alana, Luis A., 2019. "A new unit root analysis for testing hysteresis in unemployment," MPRA Paper 96621, University Library of Munich, Germany.
    20. Chang, Yoosoon, 2012. "Taking a new contour: A novel approach to panel unit root tests," Journal of Econometrics, Elsevier, vol. 169(1), pages 15-28.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:9:p:3937-:d:1140829. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.