IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v84y2019ics0140988319303597.html
   My bibliography  Save this article

The dynamic dependence of fossil energy, investor sentiment and renewable energy stock markets

Author

Listed:
  • Song, Yingjie
  • Ji, Qiang
  • Du, Ya-Juan
  • Geng, Jiang-Bo

Abstract

This study investigates the dynamic directional information spillover of return and volatility between the fossil energy market, investor sentiment towards renewable energy and the renewable energy stock market using the connectedness network approach. Empirical results show that the spillover effects of the volatility system are generally stronger than that of the return system, which suggest that risk transmission among the markets is more obvious. In both systems, the impact of the fossil energy market, especially crude oil, on the renewable energy stock market is greater than the impact of investor sentiment on the renewable energy stock market. This finding shows that the renewable energy stock market is closely related to the fossil energy market. Furthermore, the rolling window approach is adopted to examine the time-varying information spillover among them. The dynamic findings suggest that investor sentiment towards renewable energy can explain the return and volatility of renewable energy stock to a certain degree.

Suggested Citation

  • Song, Yingjie & Ji, Qiang & Du, Ya-Juan & Geng, Jiang-Bo, 2019. "The dynamic dependence of fossil energy, investor sentiment and renewable energy stock markets," Energy Economics, Elsevier, vol. 84(C).
    • Handle: RePEc:eee:eneeco:v:84:y:2019:i:c:s0140988319303597
    DOI: 10.1016/j.eneco.2019.104564
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988319303597
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2019.104564?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. Ji, Qiang & Guo, Jian-Feng, 2015. "Oil price volatility and oil-related events: An Internet concern study perspective," Applied Energy, Elsevier, vol. 137(C), pages 256-264.
    2. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    3. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    4. Ma, Yan-Ran & Zhang, Dayong & Ji, Qiang & Pan, Jiaofeng, 2019. "Spillovers between oil and stock returns in the US energy sector: Does idiosyncratic information matter?," Energy Economics, Elsevier, vol. 81(C), pages 536-544.
    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. Qadan, Mahmoud & Nama, Hazar, 2018. "Investor sentiment and the price of oil," Energy Economics, Elsevier, vol. 69(C), pages 42-58.
    7. Kim, Neri & Lučivjanská, Katarína & Molnár, Peter & Villa, Roviel, 2019. "Google searches and stock market activity: Evidence from Norway," Finance Research Letters, Elsevier, vol. 28(C), pages 208-220.
    8. 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.
    9. Pham, Linh, 2019. "Do all clean energy stocks respond homogeneously to oil price?," Energy Economics, Elsevier, vol. 81(C), pages 355-379.
    10. Ji, Qiang & Li, Jianping & Sun, Xiaolei, 2019. "Measuring the interdependence between investor sentiment and crude oil returns: New evidence from the CFTC's disaggregated reports," Finance Research Letters, Elsevier, vol. 30(C), pages 420-425.
    11. Guo, Jian-Feng & Ji, Qiang, 2013. "How does market concern derived from the Internet affect oil prices?," Applied Energy, Elsevier, vol. 112(C), pages 1536-1543.
    12. Bijl, Laurens & Kringhaug, Glenn & Molnár, Peter & Sandvik, Eirik, 2016. "Google searches and stock returns," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 150-156.
    13. Afkhami, Mohamad & Cormack, Lindsey & Ghoddusi, Hamed, 2017. "Google search keywords that best predict energy price volatility," Energy Economics, Elsevier, vol. 67(C), pages 17-27.
    14. Yan‐ran Ma & Qiang Ji & Jiaofeng Pan, 2019. "Oil financialization and volatility forecast: Evidence from multidimensional predictors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(6), pages 564-581, September.
    15. Henriques, Irene & Sadorsky, Perry, 2008. "Oil prices and the stock prices of alternative energy companies," Energy Economics, Elsevier, vol. 30(3), pages 998-1010, May.
    16. 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.
    17. Ji, Qiang & Zhang, Dayong, 2019. "How much does financial development contribute to renewable energy growth and upgrading of energy structure in China?," Energy Policy, Elsevier, vol. 128(C), pages 114-124.
    18. Chen, Shiu-Sheng & Hsu, Kai-Wei, 2012. "Reverse globalization: Does high oil price volatility discourage international trade?," Energy Economics, Elsevier, vol. 34(5), pages 1634-1643.
    19. Bohl, Martin T. & Kaufmann, Philipp & Stephan, Patrick M., 2013. "From hero to zero: Evidence of performance reversal and speculative bubbles in German renewable energy stocks," Energy Economics, Elsevier, vol. 37(C), pages 40-51.
    20. Sadorsky, Perry, 2012. "Correlations and volatility spillovers between oil prices and the stock prices of clean energy and technology companies," Energy Economics, Elsevier, vol. 34(1), pages 248-255.
    21. 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.
    22. Zhang, Dayong, 2017. "Oil shocks and stock markets revisited: Measuring connectedness from a global perspective," Energy Economics, Elsevier, vol. 62(C), pages 323-333.
    23. Wen, Xiaoqian & Guo, Yanfeng & Wei, Yu & Huang, Dengshi, 2014. "How do the stock prices of new energy and fossil fuel companies correlate? Evidence from China," Energy Economics, Elsevier, vol. 41(C), pages 63-75.
    24. Ferrer, Román & Shahzad, Syed Jawad Hussain & López, Raquel & Jareño, Francisco, 2018. "Time and frequency dynamics of connectedness between renewable energy stocks and crude oil prices," Energy Economics, Elsevier, vol. 76(C), pages 1-20.
    25. Kumar, Surender & Managi, Shunsuke & Matsuda, Akimi, 2012. "Stock prices of clean energy firms, oil and carbon markets: A vector autoregressive analysis," Energy Economics, Elsevier, vol. 34(1), pages 215-226.
    26. Ji, Qiang & Bouri, Elie & Lau, Chi Keung Marco & Roubaud, David, 2019. "Dynamic connectedness and integration in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 257-272.
    27. Ji, Qiang & Geng, Jiang-Bo & Tiwari, Aviral Kumar, 2018. "Information spillovers and connectedness networks in the oil and gas markets," Energy Economics, Elsevier, vol. 75(C), pages 71-84.
    28. Joseph, Kissan & Babajide Wintoki, M. & Zhang, Zelin, 2011. "Forecasting abnormal stock returns and trading volume using investor sentiment: Evidence from online search," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1116-1127, October.
    29. Reboredo, Juan C. & Ugolini, Andrea, 2018. "The impact of Twitter sentiment on renewable energy stocks," Energy Economics, Elsevier, vol. 76(C), pages 153-169.
    30. Luo, Jiawen & Ji, Qiang, 2018. "High-frequency volatility connectedness between the US crude oil market and China's agricultural commodity markets," Energy Economics, Elsevier, vol. 76(C), pages 424-438.
    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. Capucine Nobletz, 2021. "Return spillovers between green energy indexes and financial markets: a first sectoral approach," EconomiX Working Papers 2021-24, University of Paris Nanterre, EconomiX.
    2. Ji, Qiang & Bahloul, Walid & Geng, Jiang-Bo & Gupta, Rangan, 2020. "Trading behaviour connectedness across commodity markets: Evidence from the hedgers’ sentiment perspective," Research in International Business and Finance, Elsevier, vol. 52(C).
    3. Elsayed, Ahmed H. & Nasreen, Samia & Tiwari, Aviral Kumar, 2020. "Time-varying co-movements between energy market and global financial markets: Implication for portfolio diversification and hedging strategies," Energy Economics, Elsevier, vol. 90(C).
    4. Tiantian Liu & Shigeyuki Hamori, 2020. "Spillovers to Renewable Energy Stocks in the US and Europe: Are They Different?," Energies, MDPI, vol. 13(12), pages 1-28, June.
    5. 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).
    6. 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).
    7. Shah, Adil Ahmad & Sahay, Arvind, 2024. "Is gold a preferable diversifier of cleaner equity risk across diverse scenarios? Evidence from multidimensional connectedness and spillover measures," Energy, Elsevier, vol. 305(C).
    8. 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.
    9. Urom, Christian & Mzoughi, Hela & Abid, Ilyes & Brahim, Mariem, 2021. "Green markets integration in different time scales: A regional analysis," Energy Economics, Elsevier, vol. 98(C).
    10. 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.
    11. Elsayed, Ahmed H. & Billah, Mabruk & Goodell, John W. & Hadhri, Sinda, 2024. "Examining connections between the fourth industrial revolution and energy markets," Energy Economics, Elsevier, vol. 133(C).
    12. 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).
    13. Dan Nie & Yanbin Li & Xiyu Li & Xuejiao Zhou & Feng Zhang, 2022. "The Dynamic Spillover between Renewable Energy, Crude Oil and Carbon Market: New Evidence from Time and Frequency Domains," Energies, MDPI, vol. 15(11), pages 1-28, May.
    14. Xia, Tongshui & Yao, Chen-Xi & Geng, Jiang-Bo, 2020. "Dynamic and frequency-domain spillover among economic policy uncertainty, stock and housing markets in China," International Review of Financial Analysis, Elsevier, vol. 67(C).
    15. Fernanda Fuentes & Rodrigo Herrera, 2020. "Dynamics of Connectedness in Clean Energy Stocks," Energies, MDPI, vol. 13(14), pages 1-19, July.
    16. Geng, Jiang-Bo & Liu, Changyu & Ji, Qiang & Zhang, Dayong, 2021. "Do oil price changes really matter for clean energy returns?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    17. Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel & Doğan, Buhari & Adekoya, Oluwasegun B. & Wohar, Mark, 2024. "Asymmetric spillover effects in energy markets," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 470-502.
    18. Samir Cedic & Alwan Mahmoud & Matteo Manera & Gazi Salah Uddin, 2021. "Information Diffusion and Spillover Dynamics in Renewable Energy Markets," Working Papers 2021.10, Fondazione Eni Enrico Mattei.
    19. Guglielmo Maria Caporale & Nicola Spagnolo & Awon Almajali, 2022. "Fossil and Renewable Energy Stock Indices: Connectedness and the COP Meetings," CESifo Working Paper Series 9824, CESifo.
    20. Li, Jingpeng & Umar, Muhammad & Huo, Jiale, 2023. "The spillover effect between Chinese crude oil futures market and Chinese green energy stock market," Energy Economics, Elsevier, vol. 119(C).

    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:84:y:2019:i:c:s0140988319303597. 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.