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Dynamic Linkages between Japan’s Foreign Exchange and Stock Markets: Response to the Brexit Referendum and the 2016 U.S. Presidential Election

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  • Mirzosaid Sultonov

    (Department of Community Service and Science, Tohoku University of Community Service and Science, 9988580 Sakata, Japan)

  • Shahzadah Nayyar Jehan

    (Department of Community Service and Science, Tohoku University of Community Service and Science, 9988580 Sakata, Japan)

Abstract

In this paper, we analyse the response of Japan’s foreign exchange and stock markets to the outcomes of the Brexit referendum and the U.S. presidential election. We estimate the changes in returns of the daily exchange rates of the yen (JPY), the daily closing price index of the Nikkei and the dynamic conditional correlation (DCC) coefficients between the JPY and the Nikkei caused by both events. The empirical findings showed a significant change in the daily logarithmic returns of exchange rates of the JPY and the closing price index of the Nikkei, as well as their time-varying comovement (DCC) after both events. In general, the impact of the U.S. elections on financial markets and their dynamic correlation was stronger than the impact of the Brexit referendum.

Suggested Citation

  • Mirzosaid Sultonov & Shahzadah Nayyar Jehan, 2018. "Dynamic Linkages between Japan’s Foreign Exchange and Stock Markets: Response to the Brexit Referendum and the 2016 U.S. Presidential Election," JRFM, MDPI, vol. 11(3), pages 1-8, June.
  • Handle: RePEc:gam:jjrfmx:v:11:y:2018:i:3:p:34-:d:155155
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    References listed on IDEAS

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    1. Costas Karfakis & Theodore Panagiotidis, 2015. "The effects of global monetary policy and Greek debt crisis on the dynamic conditional correlations of currency markets," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(4), pages 795-811, November.
    2. Chung, Chae-Shick & Jang, Youngmin, 2000. "Analysis of Changes in the Relationship between the KRW/USD Exchange rate and JPY/USD Exchange Rate Before and After the Economic Crisis," East Asian Economic Review, Korea Institute for International Economic Policy, vol. 4(1), pages 65-93, March.
    3. Hanabusa, Kunihiro, 2010. "Effects of foreign disasters on the petroleum industry in Japan: A financial market perspective," Energy, Elsevier, vol. 35(12), pages 5455-5463.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. Engle, Robert F & Sheppard, Kevin K, 2001. "Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH," University of California at San Diego, Economics Working Paper Series qt5s2218dp, Department of Economics, UC San Diego.
    6. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    7. Chin-Tsai Lin & Yi-Hsien Wang, 2005. "An Analysis of Political Changes on Nikkei 225 Stock Returns and Volatilities," Annals of Economics and Finance, Society for AEF, vol. 6(1), pages 169-183, May.
    8. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    9. Ågren, Martin, 2006. "Does Oil Price Uncertainty Transmit to Stock Markets?," Working Paper Series 2006:23, Uppsala University, Department of Economics.
    10. Engle, Robert F & Sheppard, Kevin K, 2001. "Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH," University of California at San Diego, Economics Working Paper Series qt5s2218dp, Department of Economics, UC San Diego.
    11. Dimitriou, Dimitrios & Kenourgios, Dimitris & Simos, Theodore, 2017. "Financial crises, exchange rate linkages and uncovered interest parity: Evidence from G7 markets," Economic Modelling, Elsevier, vol. 66(C), pages 112-120.
    12. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    13. Lin Wang & Ali M Kutan, 2013. "The Impact of Natural Disasters on Stock Markets: Evidence from Japan and the US," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 55(4), pages 672-686, December.
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    Cited by:

    1. Bilal Ahmed Memon & Hongxing Yao & Rabia Tahir, 2020. "General election effect on the network topology of Pakistan’s stock market: network-based study of a political event," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-14, December.
    2. Mirzosaid Sultonov, 2020. "The Impacts of International Political and Economic Events on Japanese Financial Markets," IJFS, MDPI, vol. 8(3), pages 1-10, July.
    3. Tihana Škrinjarić, 2019. "Stock Market Reactions to Brexit: Case of Selected CEE and SEE Stock Markets," IJFS, MDPI, vol. 7(1), pages 1-14, January.

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