IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v114y2022ics0140988322004340.html
   My bibliography  Save this article

Extreme connectedness between renewable energy tokens and fossil fuel markets

Author

Listed:
  • Yousaf, Imran
  • Nekhili, Ramzi
  • Umar, Muhammad

Abstract

This paper examines the aspect pertaining to the returns connectedness between renewable energy tokens, namely, Powerledger-POWR and WePower-WPR, and the fossil fuel markets, namely, WTI oil, Brent oil, and Natural gas. For this purpose, we employed a quantile-based regression approach, in order to explore the dependence structures that exist under diverse market conditions. The results of the analysis show that the element of connectedness in the renewable energy tokens-fossil fuel market nexus is characterized by asymmetry and heterogeneity in the tails that are compared to the respective mean and the median. Under normal market conditions, the WTI oil market emerges as the main net transmitter of return spillover to the renewable energy tokens. Whereas, Brent oil and natural gas markets are the net receivers of the return spillover from the digital assets. However, under periods of extreme negative returns, the Brent oil market behaves as the main net transmitter of return spillover to the renewable energy digital markets. Whereas, under period of extreme positive returns, the natural gas market appears to be the main net transmitter of return spillover to the renewable energy digital markets. Therefore, it can be fathomed that on aggregate, renewable energy digital tokens are weakly connected with fossil fuel markets, thus suggesting the addition of renewable energy tokens in the portfolio of fossil fuel markets.

Suggested Citation

  • Yousaf, Imran & Nekhili, Ramzi & Umar, Muhammad, 2022. "Extreme connectedness between renewable energy tokens and fossil fuel markets," Energy Economics, Elsevier, vol. 114(C).
    • Handle: RePEc:eee:eneeco:v:114:y:2022:i:c:s0140988322004340
    DOI: 10.1016/j.eneco.2022.106305
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988322004340
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2022.106305?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jiang, Yonghong & Wang, Jieru & Lie, Jiayi & Mo, Bin, 2021. "Dynamic dependence nexus and causality of the renewable energy stock markets on the fossil energy markets," Energy, Elsevier, vol. 233(C).
    2. Le, Lan-TN & Yarovaya, Larisa & Nasir, Muhammad Ali, 2021. "Did COVID-19 change spillover patterns between Fintech and other asset classes?," Research in International Business and Finance, Elsevier, vol. 58(C).
    3. Elsayed, Ahmed H. & Gozgor, Giray & Yarovaya, Larisa, 2022. "Volatility and return connectedness of cryptocurrency, gold, and uncertainty: Evidence from the cryptocurrency uncertainty indices," Finance Research Letters, Elsevier, vol. 47(PB).
    4. Elie, Bouri & Naji, Jalkh & Dutta, Anupam & Uddin, Gazi Salah, 2019. "Gold and crude oil as safe-haven assets for clean energy stock indices: Blended copulas approach," Energy, Elsevier, vol. 178(C), pages 544-553.
    5. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Ugolini, Andrea, 2017. "Wavelet-based test of co-movement and causality between oil and renewable energy stock prices," Energy Economics, Elsevier, vol. 61(C), pages 241-252.
    6. Li, Yan & Chevallier, Julien & Wei, Yigang & Li, Jing, 2020. "Identifying price bubbles in the US, European and Asian natural gas market: Evidence from a GSADF test approach," Energy Economics, Elsevier, vol. 87(C).
    7. Kocaarslan, Baris & Soytas, Ugur, 2019. "Dynamic correlations between oil prices and the stock prices of clean energy and technology firms: The role of reserve currency (US dollar)," Energy Economics, Elsevier, vol. 84(C).
    8. Tan, Xueping & Geng, Yong & Vivian, Andrew & Wang, Xinyu, 2021. "Measuring risk spillovers between oil and clean energy stocks: Evidence from a systematic framework," Resources Policy, Elsevier, vol. 74(C).
    9. Corbet, Shaen & Lucey, Brian & Yarovaya, Larisa, 2021. "Bitcoin-energy markets interrelationships - New evidence," Resources Policy, Elsevier, vol. 70(C).
    10. Reboredo, Juan C. & Ugolini, Andrea, 2018. "The impact of energy prices on clean energy stock prices. A multivariate quantile dependence approach," Energy Economics, Elsevier, vol. 76(C), pages 136-152.
    11. Pham, Linh, 2019. "Do all clean energy stocks respond homogeneously to oil price?," Energy Economics, Elsevier, vol. 81(C), pages 355-379.
    12. Naeem, Muhammad Abubakr & Peng, Zhe & Suleman, Mouhammed Tahir & Nepal, Rabindra & Shahzad, Syed Jawad Hussain, 2020. "Time and frequency connectedness among oil shocks, electricity and clean energy markets," Energy Economics, Elsevier, vol. 91(C).
    13. Elsayed, Ahmed H. & Gozgor, Giray & Lau, Chi Keung Marco, 2022. "Risk transmissions between bitcoin and traditional financial assets during the COVID-19 era: The role of global uncertainties," International Review of Financial Analysis, Elsevier, vol. 81(C).
    14. Gozgor, Giray, 2016. "Are shocks to renewable energy consumption permanent or transitory? An empirical investigation for Brazil, China, and India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 913-919.
    15. Jiang, Shangrong & Li, Yuze & Lu, Quanying & Wang, Shouyang & Wei, Yunjie, 2022. "Volatility communicator or receiver? Investigating volatility spillover mechanisms among Bitcoin and other financial markets," Research in International Business and Finance, Elsevier, vol. 59(C).
    16. Gozgor, Giray & Lau, Chi Keung Marco & Sheng, Xin & Yarovaya, Larisa, 2019. "The role of uncertainty measures on the returns of gold," Economics Letters, Elsevier, vol. 185(C).
    17. Umar, Muhammad & Farid, Saqib & Naeem, Muhammad Abubakr, 2022. "Time-frequency connectedness among clean-energy stocks and fossil fuel markets: Comparison between financial, oil and pandemic crisis," Energy, Elsevier, vol. 240(C).
    18. Rehman, Mobeen Ur & Kang, Sang Hoon, 2021. "A time–frequency comovement and causality relationship between Bitcoin hashrate and energy commodity markets," Global Finance Journal, Elsevier, vol. 49(C).
    19. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    20. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    21. Yousaf, Imran & Yarovaya, Larisa, 2022. "Static and dynamic connectedness between NFTs, Defi and other assets: Portfolio implication," Global Finance Journal, Elsevier, vol. 53(C).
    22. Lo Prete, Chiara & Hobbs, Benjamin F., 2016. "A cooperative game theoretic analysis of incentives for microgrids in regulated electricity markets," Applied Energy, Elsevier, vol. 169(C), pages 524-541.
    23. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    24. Okorie, David Iheke & Lin, Boqiang, 2020. "Crude oil price and cryptocurrencies: Evidence of volatility connectedness and hedging strategy," Energy Economics, Elsevier, vol. 87(C).
    25. Zeng, Ting & Yang, Mengying & Shen, Yifan, 2020. "Fancy Bitcoin and conventional financial assets: Measuring market integration based on connectedness networks," Economic Modelling, Elsevier, vol. 90(C), pages 209-220.
    26. Xi, Yue & Zeng, Qing & Lu, Xinjie & Huynh, Toan L.D., 2022. "Oil and renewable energy stock markets: Unique role of extreme shocks," Energy Economics, Elsevier, vol. 109(C).
    27. Maghyereh, Aktham & Abdoh, Hussein, 2021. "The impact of extreme structural oil-price shocks on clean energy and oil stocks," Energy, Elsevier, vol. 225(C).
    28. 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.
    29. Naeem, Muhammad Abubakr & Karim, Sitara, 2021. "Tail dependence between bitcoin and green financial assets," Economics Letters, Elsevier, vol. 208(C).
    30. Ji, Qiang & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav, 2019. "Information interdependence among energy, cryptocurrency and major commodity markets," Energy Economics, Elsevier, vol. 81(C), pages 1042-1055.
    31. Dawar, Ishaan & Dutta, Anupam & Bouri, Elie & Saeed, Tareq, 2021. "Crude oil prices and clean energy stock indices: Lagged and asymmetric effects with quantile regression," Renewable Energy, Elsevier, vol. 163(C), pages 288-299.
    32. Hammoudeh, Shawkat & Mokni, Khaled & Ben-Salha, Ousama & Ajmi, Ahdi Noomen, 2021. "Distributional predictability between oil prices and renewable energy stocks: Is there a role for the COVID-19 pandemic?," Energy Economics, Elsevier, vol. 103(C).
    33. Yahya, Muhammad & Kanjilal, Kakali & Dutta, Anupam & Uddin, Gazi Salah & Ghosh, Sajal, 2021. "Can clean energy stock price rule oil price? New evidences from a regime-switching model at first and second moments," Energy Economics, Elsevier, vol. 95(C).
    Full references (including those not matched with items on IDEAS)

    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. Tan, Xueping & Geng, Yong & Vivian, Andrew & Wang, Xinyu, 2021. "Measuring risk spillovers between oil and clean energy stocks: Evidence from a systematic framework," Resources Policy, Elsevier, vol. 74(C).
    2. El Khoury, Rim & Alshater, Muneer M. & Li, Yanshuang & Xiong, Xiong, 2024. "Quantile time-frequency connectedness among G7 stock markets and clean energy markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 93(C), pages 71-90.
    3. Farid, Saqib & Karim, Sitara & Naeem, Muhammad A. & Nepal, Rabindra & Jamasb, Tooraj, 2023. "Co-movement between dirty and clean energy: A time-frequency perspective," Energy Economics, Elsevier, vol. 119(C).
    4. Pham, Linh & Karim, Sitara & Naeem, Muhammad Abubakr & Long, Cheng, 2022. "A tale of two tails among carbon prices, green and non-green cryptocurrencies," International Review of Financial Analysis, Elsevier, vol. 82(C).
    5. 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).
    6. Ahmed, Walid M.A. & Sleem, Mohamed A.E., 2023. "Short- and long-run determinants of the price behavior of US clean energy stocks: A dynamic ARDL simulations approach," Energy Economics, Elsevier, vol. 124(C).
    7. Ren, Boru & Lucey, Brian, 2022. "A clean, green haven?—Examining the relationship between clean energy, clean and dirty cryptocurrencies," Energy Economics, Elsevier, vol. 109(C).
    8. Urom, Christian & Mzoughi, Hela & Ndubuisi, Gideon & Guesmi, Khaled, 2022. "Directional predictability and time-frequency spillovers among clean energy sectors and oil price uncertainty," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 326-341.
    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. Umar, Muhammad & Farid, Saqib & Naeem, Muhammad Abubakr, 2022. "Time-frequency connectedness among clean-energy stocks and fossil fuel markets: Comparison between financial, oil and pandemic crisis," Energy, Elsevier, vol. 240(C).
    11. Gong, Xiao-Li & Zhao, Min & Wu, Zhuo-Cheng & Jia, Kai-Wen & Xiong, Xiong, 2023. "Research on tail risk contagion in international energy markets—The quantile time-frequency volatility spillover perspective," Energy Economics, Elsevier, vol. 121(C).
    12. Sharif, Arshian & Brahim, Mariem & Dogan, Eyup & Tzeremes, Panayiotis, 2023. "Analysis of the spillover effects between green economy, clean and dirty cryptocurrencies," Energy Economics, Elsevier, vol. 120(C).
    13. Dutta, Anupam & Bouri, Elie & Rothovius, Timo & Uddin, Gazi Salah, 2023. "Climate risk and green investments: New evidence," Energy, Elsevier, vol. 265(C).
    14. Rui Dias & Paulo Alexandre & Nuno Teixeira & Mariana Chambino, 2023. "Clean Energy Stocks: Resilient Safe Havens in the Volatility of Dirty Cryptocurrencies," Energies, MDPI, vol. 16(13), pages 1-24, July.
    15. Al-Fayoumi, Nedal & Bouri, Elie & Abuzayed, Bana, 2023. "Decomposed oil price shocks and GCC stock market sector returns and volatility," Energy Economics, Elsevier, vol. 126(C).
    16. Su, Chi-Wei & Pang, Li-Dong & Qin, Meng & Lobonţ, Oana-Ramona & Umar, Muhammad, 2023. "The spillover effects among fossil fuel, renewables and carbon markets: Evidence under the dual dilemma of climate change and energy crises," Energy, Elsevier, vol. 274(C).
    17. Fu, Zheng & Chen, Zhiguo & Sharif, Arshian & Razi, Ummara, 2022. "The role of financial stress, oil, gold and natural gas prices on clean energy stocks: Global evidence from extreme quantile approach," Resources Policy, Elsevier, vol. 78(C).
    18. Matteo Foglia & Eliana Angelini, 2020. "Volatility Connectedness between Clean Energy Firms and Crude Oil in the COVID-19 Era," Sustainability, MDPI, vol. 12(23), pages 1-22, November.
    19. Dutta, Anupam & Dutta, Probal, 2022. "Geopolitical risk and renewable energy asset prices: Implications for sustainable development," Renewable Energy, Elsevier, vol. 196(C), pages 518-525.
    20. Mesut Doğan & Sutbayeva Raikhan & Nurbossynova Zhanar & Bodaukhan Gulbagda, 2023. "Analysis of Dynamic Connectedness Relationships among Clean Energy, Carbon Emission Allowance, and BIST Indexes," Sustainability, MDPI, vol. 15(7), pages 1-13, March.

    More about this item

    Keywords

    Renewable energy tokens; Fossil fuel markets; Quantile spillover;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:eee:eneeco:v:114:y:2022:i:c:s0140988322004340. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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.