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Dynamic Asymmetric Volatility Spillover and Connectedness Network Analysis among Sectoral Renewable Energy Stocks

Author

Listed:
  • Hleil Alrweili

    (Department of Mathematics, College of Science, Northern Border University, Arar P.O. Box 73312, Saudi Arabia)

  • Ousama Ben-Salha

    (Department of Finance and Insurance, College of Business Administration, Northern Border University, Arar P.O. Box 73312, Saudi Arabia)

Abstract

A wide range of statistical and econometric models have been applied in the extant literature to compute and assess the volatility spillovers among renewable stock prices. This research adds to the body of knowledge by analyzing the dynamic asymmetric volatility spillover between major NASDAQ OMX Green Economy Indices, including solar, wind, geothermal, fuel cell, and developer/operator. The novelty of the research is that it distinguishes between positive and negative volatility spillovers in a time-varying fashion and conducts a connectedness network analysis. To do so, the study implements the Time-Varying Parameter Vector Autoregression (TVP-VAR) approach, as well as the connectedness network. The empirical investigation is based on high-frequency data between 18 October 2010, and 2 April 2022. The main findings may be summarized as follows. First, the analysis reveals a shift in the dominance of positive and negative volatility transmission during the study period, which represents compelling evidence of dynamic asymmetric spillover in the volatility transmission between renewable energy stocks. Second, the connectedness analysis indicates that the operator/developer and solar sectors are the net transmitters of both positive and negative volatility to the system. In contrast, the wind, geothermal and fuel cell sectors receive shocks from other renewable energy stocks. The asymmetric spillovers between the renewable energy stocks are confirmed using the block bootstrapping technique. Finally, the dynamic analysis reveals a substantial impact of the COVID-19 outbreak on the interdependence between renewable energy stocks. The findings above are robust to different lag orders and prediction ranges.

Suggested Citation

  • Hleil Alrweili & Ousama Ben-Salha, 2024. "Dynamic Asymmetric Volatility Spillover and Connectedness Network Analysis among Sectoral Renewable Energy Stocks," Mathematics, MDPI, vol. 12(12), pages 1-20, June.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:12:p:1816-:d:1412874
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    References listed on IDEAS

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    1. Managi, Shunsuke & Okimoto, Tatsuyoshi, 2013. "Does the price of oil interact with clean energy prices in the stock market?," Japan and the World Economy, Elsevier, vol. 27(C), pages 1-9.
    2. 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.
    3. Emrah Ismail Cevik & Sel Dibooglu & Atif Awad Abdallah & Eisa Abdulrahman Al-Eisa, 2021. "Oil prices, stock market returns, and volatility spillovers: evidence from Saudi Arabia," International Economics and Economic Policy, Springer, vol. 18(1), pages 157-175, February.
    4. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    5. Doğan, Mesut & Raikhan, Sutbayeva & Zhanar, Nurbossynova & Gulbagda, Bodaukhan, 2023. "Analysis of Dynamic Connectedness Relationships among Clean Energy, Carbon Emission Allowance, and BIST Indexes," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 15(7), pages 1-13.
    6. 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.
    7. Koop, Gary & Korobilis, Dimitris, 2014. "A new index of financial conditions," European Economic Review, Elsevier, vol. 71(C), pages 101-116.
    8. Janda, Karel & Kristoufek, Ladislav & Zhang, Binyi, 2022. "Return and volatility spillovers between Chinese and U.S. clean energy related stocks," Energy Economics, Elsevier, vol. 108(C).
    9. Kuang, Wei, 2021. "Which clean energy sectors are attractive? A portfolio diversification perspective," Energy Economics, Elsevier, vol. 104(C).
    10. 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.
    11. BenSaïda, Ahmed & Litimi, Houda & Abdallah, Oussama, 2018. "Volatility spillover shifts in global financial markets," Economic Modelling, Elsevier, vol. 73(C), pages 343-353.
    12. 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).
    13. Mhd Ruslan, Siti Marsila & Mokhtar, Kasypi, 2021. "Stock market volatility on shipping stock prices: GARCH models approach," The Journal of Economic Asymmetries, Elsevier, vol. 24(C).
    14. Hammoudeh, Shawkat & Li, Huimin & Jeon, Bang, 2003. "Causality and volatility spillovers among petroleum prices of WTI, gasoline and heating oil in different locations," The North American Journal of Economics and Finance, Elsevier, vol. 14(1), pages 89-114, March.
    15. Dong, Chunlong & Wu, Hao & Zhou, Jianwen & Lin, Huifang & Chang, Lei, 2023. "Role of renewable energy investment and geopolitical risk in green finance development: Empirical evidence from BRICS countries," Renewable Energy, Elsevier, vol. 207(C), pages 234-241.
    16. BenSaïda, Ahmed, 2019. "Good and bad volatility spillovers: An asymmetric connectedness," Journal of Financial Markets, Elsevier, vol. 43(C), pages 78-95.
    17. Ahmad, Wasim & Sadorsky, Perry & Sharma, Amit, 2018. "Optimal hedge ratios for clean energy equities," Economic Modelling, Elsevier, vol. 72(C), pages 278-295.
    18. Raggad, Bechir, 2023. "Can implied volatility predict returns on oil market? Evidence from Cross-Quantilogram Approach," Resources Policy, Elsevier, vol. 80(C).
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