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Understanding stock market volatility: What is the role of U.S. uncertainty?

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  • Su, Zhi
  • Fang, Tong
  • Yin, Libo

Abstract

This study investigates the spillover of U.S. economic uncertainty on the stock market volatility of six industrialized and three emerging-market countries, using a bivariate GARCH-MIDAS model. We consider three different U.S. uncertainty indices: economic policy uncertainty (EPU), financial uncertainty (FU), and news implied uncertainty (NVIX). Our results indicate that EPU is positively associated with the industrialized countries’ stock market volatility; FU does not appropriately predict long-term stock market volatility; and NVIX is the more powerful predictor of market volatility, with higher NVIX leading to lower volatility. Our study highlights a new channel of market contagion and furthers our understanding of the sources of stock market volatility.

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  • Su, Zhi & Fang, Tong & Yin, Libo, 2019. "Understanding stock market volatility: What is the role of U.S. uncertainty?," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 582-590.
  • Handle: RePEc:eee:ecofin:v:48:y:2019:i:c:p:582-590
    DOI: 10.1016/j.najef.2018.07.014
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    1. 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.
    2. Yao, Can-Zhong & Sun, Bo-Yi, 2018. "The study on the tail dependence structure between the economic policy uncertainty and several financial markets," The North American Journal of Economics and Finance, Elsevier, vol. 45(C), pages 245-265.
    3. Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun, 2015. "Effects of macroeconomic uncertainty on the stock and bond markets," Finance Research Letters, Elsevier, vol. 13(C), pages 10-16.
    4. Libo Yin & Liyan Han, 2014. "Spillovers of macroeconomic uncertainty among major economies," Applied Economics Letters, Taylor & Francis Journals, vol. 21(13), pages 938-944, September.
    5. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    6. Bekaert, Geert & Harvey, Campbell R, 1995. "Time-Varying World Market Integration," Journal of Finance, American Finance Association, vol. 50(2), pages 403-444, June.
    7. Ozturk, Ezgi O. & Sheng, Xuguang Simon, 2018. "Measuring global and country-specific uncertainty," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 276-295.
    8. Colombo, Valentina, 2013. "Economic policy uncertainty in the US: Does it matter for the Euro area?," Economics Letters, Elsevier, vol. 121(1), pages 39-42.
    9. Pan, Zhiyuan & Wang, Yudong & Wu, Chongfeng & Yin, Libo, 2017. "Oil price volatility and macroeconomic fundamentals: A regime switching GARCH-MIDAS model," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 130-142.
    10. Bekiros, Stelios & Gupta, Rangan & Kyei, Clement, 2016. "On economic uncertainty, stock market predictability and nonlinear spillover effects," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 184-191.
    11. Bali, Turan G. & Brown, Stephen J. & Caglayan, Mustafa O., 2014. "Macroeconomic risk and hedge fund returns," Journal of Financial Economics, Elsevier, vol. 114(1), pages 1-19.
    12. Arshanapalli, Bala & Doukas, John, 1993. "International stock market linkages: Evidence from the pre- and post-October 1987 period," Journal of Banking & Finance, Elsevier, vol. 17(1), pages 193-208, February.
    13. Klößner, Stefan & Sekkel, Rodrigo, 2014. "International spillovers of policy uncertainty," Economics Letters, Elsevier, vol. 124(3), pages 508-512.
    14. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    15. Steven J. Davis, 2016. "An Index of Global Economic Policy Uncertainty," NBER Working Papers 22740, National Bureau of Economic Research, Inc.
    16. 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.
    17. Boubaker, Sabri & Jouini, Jamel & Lahiani, Amine, 2016. "Financial contagion between the US and selected developed and emerging countries: The case of the subprime crisis," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 14-28.
    18. Manela, Asaf & Moreira, Alan, 2017. "News implied volatility and disaster concerns," Journal of Financial Economics, Elsevier, vol. 123(1), pages 137-162.
    19. Christian Conrad & Karin Loch, 2015. "Anticipating Long‐Term Stock Market Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1090-1114, November.
    20. Geert Bekaert & Campbell R. Harvey & Angela Ng, 2005. "Market Integration and Contagion," The Journal of Business, University of Chicago Press, vol. 78(1), pages 39-70, January.
    21. Hamao, Yasushi & Masulis, Ronald W & Ng, Victor, 1990. "Correlations in Price Changes and Volatility across International Stock Markets," The Review of Financial Studies, Society for Financial Studies, vol. 3(2), pages 281-307.
    22. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
    23. Bernal, Oscar & Gnabo, Jean-Yves & Guilmin, Grégory, 2016. "Economic policy uncertainty and risk spillovers in the Eurozone," Journal of International Money and Finance, Elsevier, vol. 65(C), pages 24-45.
    24. Hossein Asgharian & Ai Jun Hou & Farrukh Javed, 2013. "The Importance of the Macroeconomic Variables in Forecasting Stock Return Variance: A GARCH‐MIDAS Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(7), pages 600-612, November.
    25. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    26. R. David Mclean & Jeffrey Pontiff, 2016. "Does Academic Research Destroy Stock Return Predictability?," Journal of Finance, American Finance Association, vol. 71(1), pages 5-32, February.
    27. Officer, R R, 1973. "The Variability of the Market Factor of the New York Stock Exchange," The Journal of Business, University of Chicago Press, vol. 46(3), pages 434-453, July.
    28. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
    29. Bams, Dennis & Blanchard, Gildas & Honarvar, Iman & Lehnert, Thorsten, 2017. "Does oil and gold price uncertainty matter for the stock market?," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 270-285.
    30. Su, Zhi & Fang, Tong & Yin, Libo, 2017. "The role of news-based implied volatility among US financial markets," Economics Letters, Elsevier, vol. 157(C), pages 24-27.
    31. Harvey, Campbell R, 1991. "The World Price of Covariance Risk," Journal of Finance, American Finance Association, vol. 46(1), pages 111-157, March.
    32. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2013. "International Stock Return Predictability: What Is the Role of the United States?," Journal of Finance, American Finance Association, vol. 68(4), pages 1633-1662, August.
    33. Kristin J. Forbes & Roberto Rigobon, 2002. "No Contagion, Only Interdependence: Measuring Stock Market Comovements," Journal of Finance, American Finance Association, vol. 57(5), pages 2223-2261, October.
    34. Itamar Drechsler, 2013. "Uncertainty, Time-Varying Fear, and Asset Prices," Journal of Finance, American Finance Association, vol. 68(5), pages 1843-1889, October.
    35. Fang, Libing & Qian, Yichuo & Chen, Ying & Yu, Honghai, 2018. "How does stock market volatility react to NVIX? Evidence from developed countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 490-499.
    36. Su, Zhi & Fang, Tong & Yin, Libo, 2018. "Does NVIX matter for market volatility? Evidence from Asia-Pacific markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 506-516.
    37. Carrieri, Francesca & Errunza, Vihang & Hogan, Ked, 2007. "Characterizing World Market Integration through Time," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(4), pages 915-940, December.
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    More about this item

    Keywords

    U.S. uncertainty; GARCH-MIDAS model; Stock market volatility; Market contagion;
    All these keywords.

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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