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Dynamic spillover and systemic importance analysis of global clean energy companies: A tail risk network perspective

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  • Deng, Jing
  • Zheng, Huike
  • Xing, Xiaoyun

Abstract

This paper conducts tail risk spillover and systemic importance analysis based on the firm-level data of global clean energy system. The tail risk network is constructed based on the ΔCoVaR method, where the correlation is calculated from three perspectives: market, sector and institution. Moreover, the systematically important institutions are identified through a PageRank-based approach. We find that two industries contribute the largest in the risk transmission process, and most of the identified important institutions come from these industries as well. Also, it is observed that the COVID-19 pandemic and the Russia–Ukraine conflict would render different impacts on the risk contagion.

Suggested Citation

  • Deng, Jing & Zheng, Huike & Xing, Xiaoyun, 2023. "Dynamic spillover and systemic importance analysis of global clean energy companies: A tail risk network perspective," Finance Research Letters, Elsevier, vol. 55(PB).
    • Handle: RePEc:eee:finlet:v:55:y:2023:i:pb:s1544612323003628
    DOI: 10.1016/j.frl.2023.103990
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    1. Hanif, Waqas & Arreola Hernandez, Jose & Mensi, Walid & Kang, Sang Hoon & Uddin, Gazi Salah & Yoon, Seong-Min, 2021. "Nonlinear dependence and connectedness between clean/renewable energy sector equity and European emission allowance prices," Energy Economics, Elsevier, vol. 101(C).
    2. Geng, Jiang-Bo & Du, Ya-Juan & Ji, Qiang & Zhang, Dayong, 2021. "Modeling return and volatility spillover networks of global new energy companies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    3. Zhou, Wei & Chen, Yan & Chen, Jin, 2022. "Risk spread in multiple energy markets: Extreme volatility spillover network analysis before and during the COVID-19 pandemic," Energy, Elsevier, vol. 256(C).
    4. Chen, Xia & Fu, Qiang & Chang, Chun-Ping, 2021. "What are the shocks of climate change on clean energy investment: A diversified exploration," Energy Economics, Elsevier, vol. 95(C).
    5. Huang, Wei-Qiang & Zhuang, Xin-Tian & Yao, Shuang & Uryasev, Stan, 2016. "A financial network perspective of financial institutions’ systemic risk contributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 183-196.
    6. Zhou, Wei & Gu, Qinen & Chen, Jin, 2021. "From volatility spillover to risk spread: An empirical study focuses on renewable energy markets," Renewable Energy, Elsevier, vol. 180(C), pages 329-342.
    7. Sylvain Benoit & Jean-Edouard Colliard & Christophe Hurlin & Christophe Pérignon, 2017. "Where the Risks Lie: A Survey on Systemic Risk," Review of Finance, European Finance Association, vol. 21(1), pages 109-152.
    8. Xing, Xiaoyun & Xu, Zihan & Chen, Ying & Ouyang, WenPei & Deng, Jing & Pan, Huanxue, 2023. "The impact of the Russia–Ukraine conflict on the energy subsector stocks in China: A network-based approach," Finance Research Letters, Elsevier, vol. 53(C).
    9. Kazemilari, Mansooreh & Mardani, Abbas & Streimikiene, Dalia & Zavadskas, Edmundas Kazimieras, 2017. "An overview of renewable energy companies in stock exchange: Evidence from minimal spanning tree approach," Renewable Energy, Elsevier, vol. 102(PA), pages 107-117.
    10. Wang, Qunwei & Fan, Zining, 2023. "Green finance and investment behavior of renewable energy enterprises: A case study of China," International Review of Financial Analysis, Elsevier, vol. 87(C).
    11. Ghosh, Bikramaditya & Pham, Linh & Teplova, Tamara & Umar, Zaghum, 2023. "COVID-19 and the quantile connectedness between energy and metal markets," Energy Economics, Elsevier, vol. 117(C).
    12. Zhang, Weiping & Zhuang, Xintian & Wang, Jian & Lu, Yang, 2020. "Connectedness and systemic risk spillovers analysis of Chinese sectors based on tail risk network," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    13. Yahya, Muhammad & Ghosh, Sajal & Kanjilal, Kakali & Dutta, Anupam & Uddin, Gazi Salah, 2020. "Evaluation of cross-quantile dependence and causality between non-ferrous metals and clean energy indexes," Energy, Elsevier, vol. 202(C).
    14. Deng, Jing & Xu, Zihan & Xing, Xiaoyun, 2023. "Dynamic spillovers between clean energy and non-ferrous metals markets in China: A network-based analysis during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 83(C).
    15. Nerlinger, Martin & Utz, Sebastian, 2022. "The impact of the Russia-Ukraine conflict on energy firms: A capital market perspective," Finance Research Letters, Elsevier, vol. 50(C).
    16. Abban, Abdul Rashid & Hasan, Mohammad Zahid, 2021. "Revisiting the determinants of renewable energy investment - New evidence from political and government ideology," Energy Policy, Elsevier, vol. 151(C).
    17. Wang, Ze & Gao, Xiangyun & An, Haizhong & Tang, Renwu & Sun, Qingru, 2020. "Identifying influential energy stocks based on spillover network," International Review of Financial Analysis, Elsevier, vol. 68(C).
    18. Tiantian Liu & Tadahiro Nakajima & Shigeyuki Hamori, 2022. "The impact of economic uncertainty caused by COVID-19 on renewable energy stocks," Empirical Economics, Springer, vol. 62(4), pages 1495-1515, April.
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    More about this item

    Keywords

    Clean energy companies; Tail risk spillover; Systemic importance; The COVID-19 pandemic; The Russia–Ukraine conflict;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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