IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v11y2018i3p34-d155155.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/11/3/34/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1911-8074/11/3/34/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. Robert F. Engle & Kevin Sheppard, 2001. "Theoretical and Empirical properties of Dynamic Conditional Correlation Multivariate GARCH," NBER Working Papers 8554, National Bureau of Economic Research, Inc.
    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. 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.
    11. 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.
    12. 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.
    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. 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.

    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. Mirzosaid Sultonov, 2020. "The Impacts of International Political and Economic Events on Japanese Financial Markets," IJFS, MDPI, vol. 8(3), pages 1-10, July.
    2. Mirzosaid Sultonov, 2021. "External Shocks and Volatility Overflow among the Exchange Rate of the Yen, Nikkei, TOPIX and Sectoral Stock Indices," JRFM, MDPI, vol. 14(11), pages 1-13, November.
    3. Pelletier, Denis, 2006. "Regime switching for dynamic correlations," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 445-473.
    4. Otranto, Edoardo, 2010. "Identifying financial time series with similar dynamic conditional correlation," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 1-15, January.
    5. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2021. "The impact of Euro through time: Exchange rate dynamics under different regimes," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1375-1408, January.
    6. Emerson Fernandes Marcal & Pedro Valls Pereira & Diogenes Manoel Leiva Martin & Wilson Toshiro Nakamura, 2011. "Evaluation of contagion or interdependence in the financial crises of Asia and Latin America, considering the macroeconomic fundamentals," Applied Economics, Taylor & Francis Journals, vol. 43(19), pages 2365-2379.
    7. Shi Chen & Cathy Yi-Hsuan Chen & Wolfgang Karl Hardle, 2020. "A first econometric analysis of the CRIX family," Papers 2009.12129, arXiv.org.
    8. Marçal, Emerson Fernandes & Pereira, Pedro L. Valls, 2008. "Testing the Hypothesis of Contagion Using Multivariate Volatility Models," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 28(2), November.
    9. Mark, Joy, 2011. "Gold and the US dollar: Hedge or haven?," Finance Research Letters, Elsevier, vol. 8(3), pages 120-131, September.
    10. Zhang, Wenting & He, Xie & Hamori, Shigeyuki, 2022. "Volatility spillover and investment strategies among sustainability-related financial indexes: Evidence from the DCC-GARCH-based dynamic connectedness and DCC-GARCH t-copula approach," International Review of Financial Analysis, Elsevier, vol. 83(C).
    11. Annastiina Silvennoinen & Timo Teräsvirta, 2009. "Modeling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model," Journal of Financial Econometrics, Oxford University Press, vol. 7(4), pages 373-411, Fall.
    12. Dimitrios Kartsonakis-Mademlis & Nikolaos Dritsakis, 2020. "Does the Choice of the Multivariate GARCH Model on Volatility Spillovers Matter? Evidence from Oil Prices and Stock Markets in G7 Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 164-182.
    13. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know about the Dynamic Conditional Correlation Representation," Econometrics, MDPI, vol. 1(1), pages 1-12, June.
    14. Jieye Qin & Christopher J. Green & Kavita Sirichand, 2019. "Determinants of Nikkei futures mispricing in international markets: Dividend clustering, currency risk, and transaction costs," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(10), pages 1269-1300, October.
    15. Marçal, Emerson F. & Valls Pereira, Pedro L., 2008. "Testando A Hipótese De Contágio A Partir De Modelos Multivariados De Volatilidade [Testing the contagion hypotheses using multivariate volatility models]," MPRA Paper 10356, University Library of Munich, Germany.
    16. Afees A. Salisu & Kazeem Isah, 2017. "Modeling the spillovers between stock market and money market in Nigeria," Working Papers 023, Centre for Econometric and Allied Research, University of Ibadan.
    17. Fresoli, Diego E. & Ruiz, Esther, 2016. "The uncertainty of conditional returns, volatilities and correlations in DCC models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 170-185.
    18. Carlo Drago & Andrea Scozzari, 2022. "Evaluating conditional covariance estimates via a new targeting approach and a networks-based analysis," Papers 2202.02197, arXiv.org.
    19. M. Hakan Eratalay & Evgenii V. Vladimirov, 2020. "Mapping the stocks in MICEX: Who is central in the Moscow Stock Exchange?," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 28(4), pages 581-620, October.
    20. Francq, Christian & Zakoian, Jean-Michel, 2010. "QML estimation of a class of multivariate GARCH models without moment conditions on the observed process," MPRA Paper 20779, University Library of Munich, Germany.

    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:gam:jjrfmx:v:11:y:2018:i:3:p:34-:d:155155. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.