IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v72y2024ics1062940824000640.html
   My bibliography  Save this article

Geopolitical risks, investor sentiment and industry stock market volatility in China: Evidence from a quantile regression approach

Author

Listed:
  • Guo, Peng
  • Shi, Jing

Abstract

From an industry perspective, we apply the quantile regression to investigate the impact of investor sentiment (IS) and China’s/U.S. geopolitical risks (GPR) on Chinese stock market volatility. Considering the structural break of the stock market, we find that China’s and U.S. GPR/IS and their interaction effects have no significant impact on China’s stock market volatility at the market level. However, there has an asymmetric dependence between China’s and U.S. GPR/IS and stock market volatility, and the dependence structure is changing. At the industry level, the impact of geopolitical risk on industry stock market volatility is highly heterogeneous, and its significance mostly occurs in the upper and lower tails. Second, China’s and U.S. GPR/IS can exacerbate industry stock market volatility in bullish and bearish markets. In addition, China’s and U.S. GPR/IS and their interaction effects are heterogeneous and asymmetric, and the effects changes with the break point. Finally, compared with China’s GPR, the U.S. GPR has a larger impact on the industry stock market. The interactive effects of the U.S. GPR and IS can influence more industry stock market volatility.

Suggested Citation

  • Guo, Peng & Shi, Jing, 2024. "Geopolitical risks, investor sentiment and industry stock market volatility in China: Evidence from a quantile regression approach," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
  • Handle: RePEc:eee:ecofin:v:72:y:2024:i:c:s1062940824000640
    DOI: 10.1016/j.najef.2024.102139
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062940824000640
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.najef.2024.102139?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. Yang, Yung-Lieh & Chang, Chia-Lin, 2008. "A double-threshold GARCH model of stock market and currency shocks on stock returns," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 458-474.
    3. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    4. 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.
    5. Chi-Wei Su & Xu-Yu Cai & Ran Tao, 2020. "Can Stock Investor Sentiment Be Contagious in China?," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    6. Han, Xing & Li, Youwei, 2017. "Can investor sentiment be a momentum time-series predictor? Evidence from China," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 212-239.
    7. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    8. Bin Gao & Jun Xie, 2020. "Forecasting Excess Returns and Abnormal Trading Volume using Investor Sentiment: Evidence from Chinese Stock Index Futures Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(3), pages 593-612, February.
    9. Reuven Glick & Alan M. Taylor, 2010. "Collateral Damage: Trade Disruption and the Economic Impact of War," The Review of Economics and Statistics, MIT Press, vol. 92(1), pages 102-127, February.
    10. Ruan, Qingsong & Yang, Haiquan & Lv, Dayong & Zhang, Shuhua, 2018. "Cross-correlations between individual investor sentiment and Chinese stock market return: New perspective based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 243-256.
    11. Constantinos Antoniou & John A. Doukas & Avanidhar Subrahmanyam, 2016. "Investor Sentiment, Beta, and the Cost of Equity Capital," Management Science, INFORMS, vol. 62(2), pages 347-367, February.
    12. Smales, L.A., 2021. "Geopolitical risk and volatility spillovers in oil and stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 358-366.
    13. Yonghong Jiang & Gengyu Tian & Yiqi Wu & Bin Mo, 2022. "Impacts of geopolitical risks and economic policy uncertainty on Chinese tourism‐listed company stock," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 320-333, January.
    14. Zhou, Mei-Jing & Huang, Jian-Bai & Chen, Jin-Yu, 2020. "The effects of geopolitical risks on the stock dynamics of China's rare metals: A TVP-VAR analysis," Resources Policy, Elsevier, vol. 68(C).
    15. Balcilar, Mehmet & Bonato, Matteo & Demirer, Riza & Gupta, Rangan, 2018. "Geopolitical risks and stock market dynamics of the BRICS," Economic Systems, Elsevier, vol. 42(2), pages 295-306.
    16. Gkillas, Konstantinos & Gupta, Rangan & Wohar, Mark E., 2018. "Volatility jumps: The role of geopolitical risks," Finance Research Letters, Elsevier, vol. 27(C), pages 247-258.
    17. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    18. Shi, Yujie & Wang, Liming & Ke, Jian, 2021. "Does the US-China trade war affect co-movements between US and Chinese stock markets?," Research in International Business and Finance, Elsevier, vol. 58(C).
    19. Yanjian Zhu & Zhaoying Wu & Hua Zhang & Jing Yu, 2017. "Media sentiment, institutional investors and probability of stock price crash: evidence from Chinese stock markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(5), pages 1635-1670, December.
    20. Zhu, Huiming & Guo, Yawei & You, Wanhai & Xu, Yaqin, 2016. "The heterogeneity dependence between crude oil price changes and industry stock market returns in China: Evidence from a quantile regression approach," Energy Economics, Elsevier, vol. 55(C), pages 30-41.
    21. Baur, Dirk G., 2013. "The structure and degree of dependence: A quantile regression approach," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 786-798.
    22. Hsin-Yi Lin, 2013. "Dynamic Stock Return–Volume Relation: Evidence From Emerging Asian Markets," Bulletin of Economic Research, Wiley Blackwell, vol. 65(2), pages 178-193, April.
    23. Ni, Zhong-Xin & Wang, Da-Zhong & Xue, Wen-Jun, 2015. "Investor sentiment and its nonlinear effect on stock returns—New evidence from the Chinese stock market based on panel quantile regression model," Economic Modelling, Elsevier, vol. 50(C), pages 266-274.
    24. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    25. Yang, Jianlei & Yang, Chunpeng, 2021. "The impact of mixed-frequency geopolitical risk on stock market returns," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 226-240.
    26. Ling Hu, 2006. "Dependence patterns across financial markets: a mixed copula approach," Applied Financial Economics, Taylor & Francis Journals, vol. 16(10), pages 717-729.
    27. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    28. Utku Uygur & Oktay Taş, 2014. "The impacts of investor sentiment on returns and conditional volatility of international stock markets," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(3), pages 1165-1179, May.
    29. Muhammad A. Cheema & Yimei Man & Kenneth R. Szulczyk, 2020. "Does Investor Sentiment Predict the Near‐Term Returns of the Chinese Stock Market?," International Review of Finance, International Review of Finance Ltd., vol. 20(1), pages 225-233, March.
    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. Zhu, Huiming & Huang, Hui & Peng, Cheng & Yang, Yan, 2016. "Extreme dependence between crude oil and stock markets in Asia-Pacific regions: Evidence from quantile regression," Economics Discussion Papers 2016-46, Kiel Institute for the World Economy (IfW Kiel).
    2. Zhu, Huiming & Guo, Yawei & You, Wanhai & Xu, Yaqin, 2016. "The heterogeneity dependence between crude oil price changes and industry stock market returns in China: Evidence from a quantile regression approach," Energy Economics, Elsevier, vol. 55(C), pages 30-41.
    3. He, Zhifang, 2023. "Geopolitical risks and investor sentiment: Causality and TVP-VAR analysis," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    4. Sohag, Kazi & Hammoudeh, Shawkat & Elsayed, Ahmed H. & Mariev, Oleg & Safonova, Yulia, 2022. "Do geopolitical events transmit opportunity or threat to green markets? Decomposed measures of geopolitical risks," Energy Economics, Elsevier, vol. 111(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. Lee, Chien-Chiang & Zeng, Jhih-Hong, 2011. "The impact of oil price shocks on stock market activities: Asymmetric effect with quantile regression," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(9), pages 1910-1920.
    7. Nusair, Salah A. & Olson, Dennis, 2019. "The effects of oil price shocks on Asian exchange rates: Evidence from quantile regression analysis," Energy Economics, Elsevier, vol. 78(C), pages 44-63.
    8. 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).
    9. Maud Korley & Evangelos Giouvris, 2022. "The Impact of Oil Price and Oil Volatility Index (OVX) on the Exchange Rate in Sub-Saharan Africa: Evidence from Oil Importing/Exporting Countries," Economies, MDPI, vol. 10(11), pages 1-29, November.
    10. 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).
    11. Choi, Sun-Yong, 2022. "Evidence from a multiple and partial wavelet analysis on the impact of geopolitical concerns on stock markets in North-East Asian countries," Finance Research Letters, Elsevier, vol. 46(PB).
    12. Tan, Xue-Ping & Wang, Xin-Yu, 2017. "Dependence changes between the carbon price and its fundamentals: A quantile regression approach," Applied Energy, Elsevier, vol. 190(C), pages 306-325.
    13. Yilmazkuday, Hakan, 2024. "Geopolitical risk and stock prices," European Journal of Political Economy, Elsevier, vol. 83(C).
    14. Dong, Xiyong & Li, Changhong & Yoon, Seong-Min, 2020. "Asymmetric dependence structures for regional stock markets: An unconditional quantile regression approach," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    15. Dimic, Nebojsa & Piljak, Vanja & Swinkels, Laurens & Vulanovic, Milos, 2021. "The structure and degree of dependence in government bond markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    16. Ben Rejeb, Aymen, 2017. "On the volatility spillover between lslamic and conventional stock markets: A quantile regression analysis," Research in International Business and Finance, Elsevier, vol. 42(C), pages 794-815.
    17. Yang, Jianlei & Yang, Chunpeng, 2021. "The impact of mixed-frequency geopolitical risk on stock market returns," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 226-240.
    18. Salah A. Nusair & Jamal A. Al-Khasawneh, 2018. "Oil price shocks and stock market returns of the GCC countries: empirical evidence from quantile regression analysis," Economic Change and Restructuring, Springer, vol. 51(4), pages 339-372, November.
    19. Lee, Chien-Chiang & Chen, Mei-Ping, 2020. "Do natural disasters and geopolitical risks matter for cross-border country exchange-traded fund returns?," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    20. You, Wanhai & Guo, Yawei & Zhu, Huiming & Tang, Yong, 2017. "Oil price shocks, economic policy uncertainty and industry stock returns in China: Asymmetric effects with quantile regression," Energy Economics, Elsevier, vol. 68(C), pages 1-18.

    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:ecofin:v:72:y:2024:i:c:s1062940824000640. 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/inca/620163 .

    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.