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Geopolitical risk and stock market volatility in emerging markets: A GARCH – MIDAS approach

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  • Salisu, Afees A.
  • Ogbonna, Ahamuefula E.
  • Lasisi, Lukman
  • Olaniran, Abeeb

Abstract

In this study, we examine the connection between geopolitical risk (GPR) and stock market volatility in emerging economies. Our motivation for this study is premised on the need to assess both the predictability and the associated economic gains in relation to the subject in order to offer more useful insights to investors and practitioners. To the best of our knowledge, this is the first study that jointly considers these objectives. Consequently, we employ the GARCH-MIDAS framework which accommodates mixed data frequencies thereby circumventing information loss or any associated bias. We find that emerging stock market volatility responds more positively to geopolitical risks although the act-related GPR index offers better out-of-sample forecasts than the threat-related GPR. We also find that accounting for global economic factors in the predictability analysis is crucial for robust outcomes. Finally, we provide some utility gains of including GPR in the predictive model of stock market volatility while also highlighting some useful implications of our findings for investment and policy decisions.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:ecofin:v:62:y:2022:i:c:s1062940822001024
    DOI: 10.1016/j.najef.2022.101755
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    1. Das, Sonali & Demirer, Riza & Gupta, Rangan & Mangisa, Siphumlile, 2019. "The effect of global crises on stock market correlations: Evidence from scalar regressions via functional data analysis," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 132-147.
    2. Dario Caldara & Matteo Iacoviello, 2022. "Measuring Geopolitical Risk," American Economic Review, American Economic Association, vol. 112(4), pages 1194-1225, April.
    3. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    4. Stewart C. Myers & Nicholas S. Majluf, 1984. "Corporate Financing and Investment Decisions When Firms Have InformationThat Investors Do Not Have," NBER Working Papers 1396, National Bureau of Economic Research, Inc.
    5. Salisu, Afees A. & Gupta, Rangan & Demirer, Riza, 2022. "Global financial cycle and the predictability of oil market volatility: Evidence from a GARCH-MIDAS model," Energy Economics, Elsevier, vol. 108(C).
    6. Myers, Stewart C. & Majluf, Nicholas S., 1984. "Corporate financing and investment decisions when firms have information that investors do not have," Journal of Financial Economics, Elsevier, vol. 13(2), pages 187-221, June.
    7. Tirimisiyu F. Oloko & Abeeb O. Olaniran & Lukman A. Lasisi, 2021. "Hedging Global and Country-Specific Geopolitical Risks With South Korean Stocks - A Predictability Approach," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 2(3), pages 1-5.
    8. 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.
    9. Libing Fang & Baizhu Chen & Honghai Yu & Yichuo Qian, 2018. "The importance of global economic policy uncertainty in predicting gold futures market volatility: A GARCH‐MIDAS approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 413-422, March.
    10. Mei, Dexiang & Ma, Feng & Liao, Yin & Wang, Lu, 2020. "Geopolitical risk uncertainty and oil future volatility: Evidence from MIDAS models," Energy Economics, Elsevier, vol. 86(C).
    11. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    12. Pástor, Ľuboš & Veronesi, Pietro, 2013. "Political uncertainty and risk premia," Journal of Financial Economics, Elsevier, vol. 110(3), pages 520-545.
    13. Cheng, Chak Hung Jack & Chiu, Ching-Wai (Jeremy), 2018. "How important are global geopolitical risks to emerging countries?," International Economics, Elsevier, vol. 156(C), pages 305-325.
    14. Girardin, Eric & Joyeux, Roselyne, 2013. "Macro fundamentals as a source of stock market volatility in China: A GARCH-MIDAS approach," Economic Modelling, Elsevier, vol. 34(C), pages 59-68.
    15. Anthony C Homan, 2006. "The Impact of 9/11 on Financial Risk, Volatility and Returns of Marine Firms," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 8(4), pages 387-401, December.
    16. 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.
    17. Aysan, Ahmet Faruk & Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco, 2019. "Effects of the geopolitical risks on Bitcoin returns and volatility," Research in International Business and Finance, Elsevier, vol. 47(C), pages 511-518.
    18. Wang, Lu & Ma, Feng & Hao, Jianyang & Gao, Xinxin, 2021. "Forecasting crude oil volatility with geopolitical risk: Do time-varying switching probabilities play a role?," International Review of Financial Analysis, Elsevier, vol. 76(C).
    19. Liu, Yang & Han, Liyan & Xu, Yang, 2021. "The impact of geopolitical uncertainty on energy volatility," International Review of Financial Analysis, Elsevier, vol. 75(C).
    20. Robert F. Engle & Eric Ghysels & Bumjean Sohn, 2013. "Stock Market Volatility and Macroeconomic Fundamentals," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 776-797, July.
    21. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    22. 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.
    23. Clements, Michael P & Galvão, Ana Beatriz, 2008. "Macroeconomic Forecasting With Mixed-Frequency Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 546-554.
    24. Lin, Boqiang & Su, Tong, 2020. "Mapping the oil price-stock market nexus researches: A scientometric review," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 133-147.
    25. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    26. 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).
    27. Alqahtani, Abdullah & Bouri, Elie & Vo, Xuan Vinh, 2020. "Predictability of GCC stock returns: The role of geopolitical risk and crude oil returns," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 239-249.
    28. Colacito, Riccardo & Engle, Robert F. & Ghysels, Eric, 2011. "A component model for dynamic correlations," Journal of Econometrics, Elsevier, vol. 164(1), pages 45-59, September.
    29. Baur, Dirk G. & Smales, Lee A., 2020. "Hedging geopolitical risk with precious metals," Journal of Banking & Finance, Elsevier, vol. 117(C).
    30. Afees A. Salisu & Tirimisiyu F. Oloko, 2015. "Modelling spillovers between stock market and FX market: evidence for Nigeria," Journal of African Business, Taylor & Francis Journals, vol. 16(1-2), pages 84-108, January.
    31. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    32. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    33. Nikkinen, Jussi & Omran, Mohammad M. & Sahlstrom, Petri & Aijo, Janne, 2008. "Stock returns and volatility following the September 11 attacks: Evidence from 53 equity markets," International Review of Financial Analysis, Elsevier, vol. 17(1), pages 27-46.
    34. Choudhry, Taufiq, 2010. "World War II events and the Dow Jones industrial index," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 1022-1031, May.
    35. Wang, Lu & Ma, Feng & Liu, Jing & Yang, Lin, 2020. "Forecasting stock price volatility: New evidence from the GARCH-MIDAS model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 684-694.
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    Cited by:

    1. 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).
    2. Wu, Xinyu & Zhao, An & Cheng, Tengfei, 2023. "A Real-Time GARCH-MIDAS model," Finance Research Letters, Elsevier, vol. 56(C).
    3. Tumala, Mohammed M. & Salisu, Afees A. & Gambo, Ali I., 2023. "Disentangled oil shocks and stock market volatility in Nigeria and South Africa: A GARCH-MIDAS approach," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 707-717.
    4. Salisu, Afees A. & Olaniran, Abeeb & Lasisi, Lukman, 2023. "Climate risk and gold," Resources Policy, Elsevier, vol. 82(C).
    5. Lee, Chien-Chiang & Wang, Chih-Wei & Thinh, Bui Tien & Purnama, Muhammad Yusuf Indra, 2023. "Cash holdings and cash flows: Do oil price uncertainty and geopolitical risk matter?," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 134-152.
    6. Kai‐Hua Wang & Zu‐Shan Wang & Hong‐Wen Liu & Xin Li, 2023. "Economic policy uncertainty and geopolitical risk: evidence from China and Southeast Asia," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 37(2), pages 96-118, November.

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    More about this item

    Keywords

    Geopolitical risk; Stock market volatility; Emerging markets; GARCH-MIDAS;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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