IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-03816031.html

Which is leading: Renewable or brown energy assets?

Author

Listed:
  • Jamal Bouoiyour

    (TREE - Transitions Energétiques et Environnementales - UPPA - Université de Pau et des Pays de l'Adour - CNRS - Centre National de la Recherche Scientifique)

  • Marie Gauthier

    (TREE - Transitions Energétiques et Environnementales - UPPA - Université de Pau et des Pays de l'Adour - CNRS - Centre National de la Recherche Scientifique)

  • Elie Bouri

    (LAU - Lebanese American University)

Abstract

This study examines the relationship between crude oil, a proxy for brown energy, and several renewable energy stock sector indices (e.g., solar energy, wind energy, bioenergy, and geothermal energy) over various investment horizons. Using daily data from October 15, 2010, to February 23, 2022, we apply a combination of methods involving co-integration, wavelet coherency, and wavelet-based Granger causality. The results show that the relationship between crude oil and renewable energy indices is non-linear and somewhat multifaceted. Firstly, there are sectorial differences in the intensity of the relationships. Notably, the relationship intensity between the wind and crude oil is lower than that involving geothermal energy or bioenergy. Secondly, the relationship evolves with time. For example, the COVID-19 outbreak seems to have increased the relationship between crude oil and renewable energy markets, notably for solar, bioenergy, and geothermal. Thirdly, the relationship varies across scales. When controlling for the VIX (volatility index), a proxy of the sentiment of market participants, and EPU (economic policy uncertainty index), the relationship seems strong in the long term but weak in the short term. This result is confirmed using a Granger causality test on the wavelet-decomposed series. These findings have important implications for long-term investors, short-term speculators, and policymakers regarding the co-movement between brown and renewable energy markets.

Suggested Citation

  • Jamal Bouoiyour & Marie Gauthier & Elie Bouri, 2022. "Which is leading: Renewable or brown energy assets?," Post-Print hal-03816031, HAL.
    • Handle: RePEc:hal:journl:hal-03816031
    DOI: 10.1016/j.eneco.2022.106339
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    Other versions of this item:

    Citations

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


    Cited by:

    1. Awijen, Haithem & Ben Zaied, Younes & Ben Jabeur, Sami, 2025. "Mobilizing FDI in natural resources in the post-COP28 era: Spatial drivers, natural capital, and sustainability dynamics," Resources Policy, Elsevier, vol. 107(C).
    2. Cocca, Teodoro & Gabauer, David & Pomberger, Stefan, 2024. "Clean energy market connectedness and investment strategies: New evidence from DCC-GARCH R2 decomposed connectedness measures," Energy Economics, Elsevier, vol. 136(C).
    3. Gordo, Natali & Hunt, Alistair & Morley, Bruce, 2024. "Alternative monetary policies and renewable energy stock returns," Energy Economics, Elsevier, vol. 136(C).
    4. Rao, Amar & Lucey, Brian & Kumar, Satish & Lim, Weng Marc, 2025. "Corrigendum to “Do green energy markets catch cold when conventional energy markets sneeze?” [Energy Economics Volume 127, Part A, November 2023, 107035]," Energy Economics, Elsevier, vol. 148(C).
    5. Rezvan Pourmansouri & MirFeiz Fallahshams & Reza Ghafari Gol Afshani, 2025. "Designing a Financial Stress Index Based on the GHARCH-DCC Approach and Machine Learning Models," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(1), pages 2689-2718, March.
    6. Anupam Dutta & Kakali Kanjilal & Sajal Ghosh & Donghyun Park & Gazi Salah Uddin, 2023. "Impact of crude oil volatility jumps on sustainable investments: Evidence from India," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(10), pages 1450-1468, October.
    7. Shinwari, Riazullah & Wang, Yangjie & Gozgor, Giray & Mousavi, Mahdi, 2024. "Does FDI affect energy consumption in the belt and road initiative economies? The role of green technologies," Energy Economics, Elsevier, vol. 132(C).
    8. Chishti, Muhammad Zubair & Sinha, Avik & Zaman, Umer & Shahzad, Umer, 2023. "Exploring the dynamic connectedness among energy transition and its drivers: Understanding the moderating role of global geopolitical risk," Energy Economics, Elsevier, vol. 119(C).
    9. Si Mohammed, K. & Mellit, A., 2023. "The relationship between oil prices and the indices of renewable energy and technology companies based on QQR and GCQ techniques," Renewable Energy, Elsevier, vol. 209(C), pages 97-105.
    10. Syuhada, Khreshna & Hakim, Arief & Suprijanto, Djoko, 2024. "Assessing systemic risk and connectedness among dirty and clean energy markets from the quantile and expectile perspectives," Energy Economics, Elsevier, vol. 129(C).
    11. Zhang, Jiahao & Chen, Xiaodan & Wei, Yu & Bai, Lan, 2023. "Does the connectedness among fossil energy returns matter for renewable energy stock returns? Fresh insights from the Cross-Quantilogram analysis," International Review of Financial Analysis, Elsevier, vol. 88(C).
    12. Wu, Ruirui & Li, Bin & Qin, Zhongfeng, 2024. "Spillovers and dependency between green finance and traditional energy markets under different market conditions," Energy Policy, Elsevier, vol. 192(C).
    13. Banerjee, Ameet Kumar & Sensoy, Ahmet & Goodell, John W., 2024. "Connectivity and spillover during crises: Highlighting the prominent and growing role of green energy," Energy Economics, Elsevier, vol. 129(C).
    14. Lyócsa, Štefan & Todorova, Neda, 2024. "Forecasting of clean energy market volatility: The role of oil and the technology sector," Energy Economics, Elsevier, vol. 132(C).
    15. Nini Johana Marín-Rodríguez & Juan David González-Ruiz & Sergio Botero, 2023. "A Wavelet Analysis of the Dynamic Connectedness among Oil Prices, Green Bonds, and CO 2 Emissions," Risks, MDPI, vol. 11(1), pages 1-21, January.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:hal:journl:hal-03816031. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.