IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v58y2023ipcs1544612323008590.html
   My bibliography  Save this article

Global geopolitical risk and volatility connectedness among China's sectoral stock markets

Author

Listed:
  • Pan, Changchun
  • Zhang, Weiqi
  • Wang, Weiqiang

Abstract

Employing the time-varying parameter vector autoregressive (TVP-VAR) connectedness index and nonparametric causality-in-quantiles test, this paper investigates the causal effect of global geopolitical risk on the dynamic volatility connectedness within China's sectoral stock markets. The TVP-VAR connectedness index results reveal significant volatility connectedness among China's stock market sectors, and the industrial, consumer discretionary, and raw material sectors play a critical systemic role throughout the sample period. The Granger causality test results show that the causality-in-quantiles test demonstrates superior performance compared to the linear Granger causality test, and it is evident that global geopolitical risk exhibits significant nonlinear causality effects on both the overall volatility connectedness among sectors and the net volatility connectedness across different sectors.

Suggested Citation

  • Pan, Changchun & Zhang, Weiqi & Wang, Weiqiang, 2023. "Global geopolitical risk and volatility connectedness among China's sectoral stock markets," Finance Research Letters, Elsevier, vol. 58(PC).
  • Handle: RePEc:eee:finlet:v:58:y:2023:i:pc:s1544612323008590
    DOI: 10.1016/j.frl.2023.104487
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612323008590
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2023.104487?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. Dario Caldara & Matteo Iacoviello, 2022. "Measuring Geopolitical Risk," American Economic Review, American Economic Association, vol. 112(4), pages 1194-1225, April.
    2. King, Mervyn A & Wadhwani, Sushil, 1990. "Transmission of Volatility between Stock Markets," The Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 5-33.
    3. Zhang, Yaojie & He, Jiaxin & He, Mengxi & Li, Shaofang, 2023. "Geopolitical risk and stock market volatility: A global perspective," Finance Research Letters, Elsevier, vol. 53(C).
    4. 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.
    5. Antonakakis, Nikolaos & Gupta, Rangan & Kollias, Christos & Papadamou, Stephanos, 2017. "Geopolitical risks and the oil-stock nexus over 1899–2016," Finance Research Letters, Elsevier, vol. 23(C), pages 165-173.
    6. Balcilar, Mehmet & Gupta, Rangan & Pierdzioch, Christian, 2016. "Does uncertainty move the gold price? New evidence from a nonparametric causality-in-quantiles test," Resources Policy, Elsevier, vol. 49(C), pages 74-80.
    7. Christos Bouras & Christina Christou & Rangan Gupta & Tahir Suleman, 2020. "Geopolitical Risks, Returns, and Volatility in Emerging Stock Markets: Evidence from a Panel GARCH Model," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(8), pages 1841-1856, July.
    8. Menglong Yang & Qiang Zhang & Adan Yi & Peng Peng & Baogui Xin, 2021. "Geopolitical Risk and Stock Market Volatility in Emerging Economies: Evidence from GARCH-MIDAS Model," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-17, September.
    9. 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.
    10. 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.
    11. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    12. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2020. "Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions," JRFM, MDPI, vol. 13(4), pages 1-23, April.
    13. Adler, Michael & Dumas, Bernard, 1983. "International Portfolio Choice and Corporation Finance: A Synthesis," Journal of Finance, American Finance Association, vol. 38(3), pages 925-984, June.
    14. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Lasisi, Lukman & Olaniran, Abeeb, 2022. "Geopolitical risk and stock market volatility in emerging markets: A GARCH – MIDAS approach," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    15. Jeong, Kiho & Härdle, Wolfgang K. & Song, Song, 2012. "A Consistent Nonparametric Test For Causality In Quantile," Econometric Theory, Cambridge University Press, vol. 28(4), pages 861-887, August.
    16. Li, Tao & Ma, Feng & Zhang, Xuehua & Zhang, Yaojie, 2020. "Economic policy uncertainty and the Chinese stock market volatility: Novel evidence," Economic Modelling, Elsevier, vol. 87(C), pages 24-33.
    17. Nishiyama, Yoshihiko & Hitomi, Kohtaro & Kawasaki, Yoshinori & Jeong, Kiho, 2011. "A consistent nonparametric test for nonlinear causality—Specification in time series regression," Journal of Econometrics, Elsevier, vol. 165(1), pages 112-127.
    18. McQueen, Grant & Roley, V Vance, 1993. "Stock Prices, News, and Business Conditions," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 683-707.
    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. Fasanya, Ismail O. & Oyewole, Oluwatomisin & Dauda, Mariam, 2023. "Uncertainty due to infectious diseases and bitcoin-gold nexus: Evidence from a non-parametric causality-in-quantiles approach," Resources Policy, Elsevier, vol. 82(C).
    2. Chen, Huayi & Shi, Huai-Long & Zhou, Wei-Xing, 2024. "Carbon volatility connectedness and the role of external uncertainties: Evidence from China," Journal of Commodity Markets, Elsevier, vol. 33(C).
    3. Zou, Fei & Huang, Lingyu & Ghaemi Asl, Mahdi & Delnavaz, Mohammad & Tiwari, Sunil, 2023. "Natural resources and green economic recovery in responsible investments: Role of ESG in context of Islamic sustainable investments," Resources Policy, Elsevier, vol. 86(PA).
    4. Szafranek, Karol & Rubaszek, Michał & Uddin, Gazi Salah, 2024. "The role of uncertainty and sentiment for intraday volatility connectedness between oil and financial markets," Energy Economics, Elsevier, vol. 137(C).
    5. Ahmed H. Elsayed & Mohamad Husam Helmi, 2021. "Volatility transmission and spillover dynamics across financial markets: the role of geopolitical risk," Annals of Operations Research, Springer, vol. 305(1), pages 1-22, October.
    6. Ozcan Ceylan, 2023. "Analysis of Dynamic Connectedness among Sovereign CDS Premia," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 9(1), pages 33-47, June.
    7. Kamal, Javed Bin & Wohar, Mark & Kamal, Khaled Bin, 2022. "Do gold, oil, equities, and currencies hedge economic policy uncertainty and geopolitical risks during covid crisis?," Resources Policy, Elsevier, vol. 78(C).
    8. Foglia, Matteo & Palomba, Giulio & Tedeschi, Marco, 2023. "Disentangling the geopolitical risk and its effects on commodities. Evidence from a panel of G8 countries," Resources Policy, Elsevier, vol. 85(PB).
    9. Abdollahi, Hooman & Fjesme, Sturla L. & Sirnes, Espen, 2024. "Measuring market volatility connectedness to media sentiment," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    10. Le, Thanh Ha, 2023. "Quantile time-frequency connectedness between cryptocurrency volatility and renewable energy volatility during the COVID-19 pandemic and Ukraine-Russia conflicts," Renewable Energy, Elsevier, vol. 202(C), pages 613-625.
    11. Li, Sufang & Tu, Dalun & Zeng, Yan & Gong, Chenggang & Yuan, Di, 2022. "Does geopolitical risk matter in crude oil and stock markets? Evidence from disaggregated data," Energy Economics, Elsevier, vol. 113(C).
    12. Antonakakis, Nikolaos & Cunado, Juncal & Filis, George & Gabauer, David & de Gracia, Fernando Perez, 2023. "Dynamic connectedness among the implied volatilities of oil prices and financial assets: New evidence of the COVID-19 pandemic," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 114-123.
    13. Chen, Yanhui & Zhou, Xiaoyu & Chen, Shun & Mi, Jackson Jinhong, 2024. "LNG freight rate and LNG price, carbon price, geopolitical risk: A dynamic connectedness analysis," Energy, Elsevier, vol. 302(C).
    14. Shang, Jin & Hamori, Shigeyuki, 2024. "Quantile time-frequency connectedness analysis between crude oil, gold, financial markets, and macroeconomic indicators: Evidence from the US and EU," Energy Economics, Elsevier, vol. 132(C).
    15. Evrim Mandaci, Pınar & Azimli, Asil & Mandaci, Nazif, 2023. "The impact of geopolitical risks on connectedness among natural resource commodities: A quantile vector autoregressive approach," Resources Policy, Elsevier, vol. 85(PA).
    16. 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).
    17. Feng, Huiqun & Zhang, Jun & Guo, Na, 2023. "Time-varying linkages between energy and stock markets: Dynamic spillovers and driving factors," International Review of Financial Analysis, Elsevier, vol. 89(C).
    18. Emmanuel Joel Aikins Abakah & Aviral Kumar Tiwari & Chi‐Chuan Lee & Matthew Ntow‐Gyamfi, 2023. "Quantile price convergence and spillover effects among Bitcoin, Fintech, and artificial intelligence stocks," International Review of Finance, International Review of Finance Ltd., vol. 23(1), pages 187-205, March.
    19. Gong, Xu & Xu, Jun, 2022. "Geopolitical risk and dynamic connectedness between commodity markets," Energy Economics, Elsevier, vol. 110(C).
    20. Lang, Chunlin & Xu, Danyang & Corbet, Shaen & Hu, Yang & Goodell, John W., 2024. "Global financial risk and market connectedness: An empirical analysis of COVOL and major financial markets," International Review of Financial Analysis, Elsevier, vol. 93(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:finlet:v:58:y:2023:i:pc:s1544612323008590. 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/frl .

    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.