IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v53y2023ics1544612322007966.html
   My bibliography  Save this article

Geopolitical risk and stock market volatility: A global perspective

Author

Listed:
  • Zhang, Yaojie
  • He, Jiaxin
  • He, Mengxi
  • Li, Shaofang

Abstract

This paper investigates the relationship between geopolitical risk (GPR) and stock market volatility from a global perspective. We use dynamic panel data including 32 countries and regions and the bias-corrected least-squares dummy variable (LSDV) estimator. Empirical results show that GPR has a significant positive effect on stock market volatility, which is not affected by control variables. Moreover, we find that the effect of GPR on stock market volatility is more significant for emerging economies, crude oil exporters, and countries at peace. Our study provides new evidence for the relationship between GPR and stock market volatility.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:finlet:v:53:y:2023:i:c:s1544612322007966
    DOI: 10.1016/j.frl.2022.103620
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612322007966
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2022.103620?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. Zhang, Yaojie & Ma, Feng & Wang, Yudong, 2019. "Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 97-117.
    3. Andrew J. Patton & Kevin Sheppard, 2015. "Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility," The Review of Economics and Statistics, MIT Press, vol. 97(3), pages 683-697, July.
    4. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    5. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    6. Bruno, Giovanni S.F., 2005. "Approximating the bias of the LSDV estimator for dynamic unbalanced panel data models," Economics Letters, Elsevier, vol. 87(3), pages 361-366, June.
    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. He, Mengxi & Zhang, Yaojie & Wen, Danyan & Wang, Yudong, 2021. "Forecasting crude oil prices: A scaled PCA approach," Energy Economics, Elsevier, vol. 97(C).
    9. Liu, Jing & Ma, Feng & Tang, Yingkai & Zhang, Yaojie, 2019. "Geopolitical risk and oil volatility: A new insight," Energy Economics, Elsevier, vol. 84(C).
    10. Lee, Kiryoung, 2023. "Geopolitical risk and household stock market participation," Finance Research Letters, Elsevier, vol. 51(C).
    11. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    12. Ma, Feng & Lu, Fei & Tao, Ying, 2022. "Geopolitical risk and excess stock returns predictability: New evidence from a century of data," Finance Research Letters, Elsevier, vol. 50(C).
    13. Chao Liang & Feng Ma & Lu Wang & Qing Zeng, 2021. "The information content of uncertainty indices for natural gas futures volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1310-1324, November.
    14. Umar B. Ndako & Afees A. Salisu & Muritala O. Ogunsiji, 2021. "Geopolitical Risk and the Return Volatility of Islamic Stocks in Indonesia and Malaysia - A GARCH-MIDAS Approach," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 2(3), pages 1-5.
    15. Eckstein, Zvi & Tsiddon, Daniel, 2004. "Macroeconomic consequences of terror: theory and the case of Israel," Journal of Monetary Economics, Elsevier, vol. 51(5), pages 971-1002, July.
    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. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2022. "Geopolitical risk trends and crude oil price predictability," Energy, Elsevier, vol. 258(C).
    18. Arin, K. Peren & Ciferri, Davide & Spagnolo, Nicola, 2008. "The price of terror: The effects of terrorism on stock market returns and volatility," Economics Letters, Elsevier, vol. 101(3), pages 164-167, December.
    19. Olanipekun, Ifedolapo Olabisi & Alola, Andrew Adewale, 2020. "Crude oil production in the Persian Gulf amidst geopolitical risk, cost of damage and resources rents: Is there asymmetric inference?," Resources Policy, Elsevier, vol. 69(C).
    20. Wang, Yudong & Wei, Yu & Wu, Chongfeng & Yin, Libo, 2018. "Oil and the short-term predictability of stock return volatility," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 90-104.
    21. 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).
    22. Xiafei Li & Yu Wei & Xiaodan Chen & Feng Ma & Chao Liang & Wang Chen, 2022. "Which uncertainty is powerful to forecast crude oil market volatility? New evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4279-4297, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Niu, Zibo & Wang, Chenlu & Zhang, Hongwei, 2023. "Forecasting stock market volatility with various geopolitical risks categories: New evidence from machine learning models," International Review of Financial Analysis, Elsevier, vol. 89(C).
    2. Wang, Jiqian & Ma, Feng & Wang, Tianyang & Wu, Lan, 2023. "International stock volatility predictability: New evidence from uncertainties," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).

    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. Xiao, Jihong & Wen, Fenghua & He, Zhifang, 2023. "Impact of geopolitical risks on investor attention and speculation in the oil market: Evidence from nonlinear and time-varying analysis," Energy, Elsevier, vol. 267(C).
    2. Zhang, Zhikai & Wang, Yudong & Xiao, Jihong & Zhang, Yaojie, 2023. "Not all geopolitical shocks are alike: Identifying price dynamics in the crude oil market under tensions," Resources Policy, Elsevier, vol. 80(C).
    3. Yang, Tianle & Dong, Qingyuan & Du, Min & Du, Qunyang, 2023. "Geopolitical risks, oil price shocks and inflation: Evidence from a TVP–SV–VAR approach," Energy Economics, Elsevier, vol. 127(PB).
    4. Ahdi Noomen Ajmi & Roula Inglesi-Lotz, 2021. "Revisiting the Kuznets Curve Hypothesis for Tunisia: Carbon Dioxide vs. Ecological Footprint," Working Papers 202171, University of Pretoria, Department of Economics.
    5. Niu, Zibo & Wang, Chenlu & Zhang, Hongwei, 2023. "Forecasting stock market volatility with various geopolitical risks categories: New evidence from machine learning models," International Review of Financial Analysis, Elsevier, vol. 89(C).
    6. Tam NguyenHuu & Deniz Karaman Orsal, 2022. "Geopolitical risks and financial stress in emerging economies," Working Papers 2022.09, International Network for Economic Research - INFER.
    7. Cheng, Xian & Wu, Peng & Liao, Stephen Shaoyi & Wang, Xuelian, 2023. "An integrated model for crude oil forecasting: Causality assessment and technical efficiency," Energy Economics, Elsevier, vol. 117(C).
    8. Wang, Jiqian & Ma, Feng & Bouri, Elie & Zhong, Juandan, 2022. "Volatility of clean energy and natural gas, uncertainty indices, and global economic conditions," Energy Economics, Elsevier, vol. 108(C).
    9. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
    10. Zhang, Yulian & Hamori, Shigeyuki, 2022. "A connectedness analysis among BRICS’s geopolitical risks and the US macroeconomy," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 182-203.
    11. Dogan, Eyup & Majeed, Muhammad Tariq & Luni, Tania, 2021. "Analyzing the impacts of geopolitical risk and economic uncertainty on natural resources rents," Resources Policy, Elsevier, vol. 72(C).
    12. He, Mengxi & Zhang, Yaojie, 2022. "Climate policy uncertainty and the stock return predictability of the oil industry," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    13. 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).
    14. Jin, Daxiang & He, Mengxi & Xing, Lu & Zhang, Yaojie, 2022. "Forecasting China's crude oil futures volatility: How to dig out the information of other energy futures volatilities?," Resources Policy, Elsevier, vol. 78(C).
    15. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2022. "Geopolitical risk trends and crude oil price predictability," Energy, Elsevier, vol. 258(C).
    16. Liu, Yang & Han, Liyan & Xu, Yang, 2021. "The impact of geopolitical uncertainty on energy volatility," International Review of Financial Analysis, Elsevier, vol. 75(C).
    17. Layal Mansour-Ichrakieh, 2021. "The Impact of Israeli and Saudi Arabian Geopolitical Risks on the Lebanese Financial Market," JRFM, MDPI, vol. 14(3), pages 1-24, February.
    18. Li, Xiafei & Liang, Chao & Chen, Zhonglu & Umar, Muhammad, 2022. "Forecasting crude oil volatility with uncertainty indicators: New evidence," Energy Economics, Elsevier, vol. 108(C).
    19. Zhang, Yaojie & Lei, Likun & Wei, Yu, 2020. "Forecasting the Chinese stock market volatility with international market volatilities: The role of regime switching," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    20. Asai, Manabu & Gupta, Rangan & McAleer, Michael, 2020. "Forecasting volatility and co-volatility of crude oil and gold futures: Effects of leverage, jumps, spillovers, and geopolitical risks," International Journal of Forecasting, Elsevier, vol. 36(3), pages 933-948.

    More about this item

    Keywords

    Geopolitical risk; Stock market volatility; Global perspective; Dynamic panel data; LSDV estimator;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    Statistics

    Access and download statistics

    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:53:y:2023:i:c:s1544612322007966. 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.