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Stock Market Integration: Granger Causality Testing with Respect to Nonsynchronous Trading Effects

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Abstract

In this paper, we perform Granger causality analysis on stock market indices from several Asian, European, and U.S. markets. Using daily data, we point out the potential problems caused by the presence of nonsynchronous trading effects. We deal with two kinds of nonsynchronicity – one induced by differing numbers of observations in the series being analyzed and the other related to the different time zones in which the markets operate. To address the first problem, we propose a data-matching process. To address the second problem, we modify the regressions used in the Granger causality testing. When comparing the empirical results obtained using the standard technique and our modified methodology, we find substantially different results. Most of the relationships that are subject to nonsynchronous trading are not significant in the general case. However, when we use the adjusted methodology, the null hypothesis of a Granger non-causal relationship is rejected in all cases.

Suggested Citation

  • Eduard Baumöhl & Tomáš Výrost, 2010. "Stock Market Integration: Granger Causality Testing with Respect to Nonsynchronous Trading Effects," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 60(5), pages 414-425, December.
  • Handle: RePEc:fau:fauart:v:60:y:2010:i:5:p:414-425
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    Cited by:

    1. Joanna Olbrys, 2013. "Price and Volatility Spillovers in the Case of Stock Markets Located in Different Time Zones," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 49(S2), pages 145-157, March.
    2. Joanna Olbrys, 2013. "Asymmetric impact of innovations on volatility in the case of the US and CEEC-3 markets: EGARCH based approach," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 13, pages 33-50.
    3. Baumöhl, Eduard & Lyócsa, Štefan, 2014. "Volatility and dynamic conditional correlations of worldwide emerging and frontier markets," Economic Modelling, Elsevier, vol. 38(C), pages 175-183.
    4. Andrey Kudryavtsev & Gil Cohen & Julia Pavlodsky, 2012. "Incorporating Weekend Information in Stock Prices: Evidence from Israeli Stock Market," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 1(4), pages 1-1.
    5. Ceylan Onay & Gözde Ünal, 2012. "Cointegration and Extreme Value Analyses of Bovespa and the Istanbul Stock Exchange," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(1), pages 66-90, February.
    6. Mikhail Stolbov, 2017. "Assessing systemic risk and its determinants for advanced and major emerging economies: the case of ΔCoVaR," International Economics and Economic Policy, Springer, vol. 14(1), pages 119-152, January.
    7. Iikka Korhonen & Anatoly Peresetsky, 2016. "What Influences Stock Market Behavior in Russia and Other Emerging Countries?," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(5), pages 1210-1225, May.
    8. repec:mes:emfitr:v:52:y:2016:i:5:p:1210-1225 is not listed on IDEAS
    9. Výrost, Tomáš & Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Granger causality stock market networks: Temporal proximity and preferential attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 262-276.
    10. Baumöhl, Eduard & Lyócsa, Štefan, 2012. "Constructing weekly returns based on daily stock market data: A puzzle for empirical research?," MPRA Paper 43431, University Library of Munich, Germany.
    11. Akpan, Sunday Brownson & Udoh, Edet Joshua & Udo, Udoro Jacob, 2. "Monthly Price Analysis Of Cowpea (Beans) And Maize In Akwa Ibom State, Southern Nigeria," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 2(2).
    12. repec:eco:journ1:2017-03-24 is not listed on IDEAS
    13. Joanna Olbrys & Elzbieta Majewska, 2014. "Implications of market frictions: serial correlations in indexes on the emerging stock markets in Central and Eastern Europe," Operations Research and Decisions, Wroclaw University of Technology, Institute of Organization and Management, vol. 1, pages 51-70.
    14. repec:eee:rensus:v:81:y:2018:i:p2:p:1859-1867 is not listed on IDEAS
    15. Silvo Dajcman, 2012. "The Dynamics of Return Comovement and Spillovers Between the Czech and European Stock Markets in the Period 1997–2010," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(4), pages 368-390, August.
    16. Eduard Baumöhl & Štefan Lyócsa, 2014. "Risk-Return Convergence in CEE Stock Markets: Structural Breaks and Market Volatility," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(5), pages 352-373, November.
    17. Baumohl, Eduard & Lyocsa, Stefan, 2013. "Volatility and dynamic conditional correlations of European emerging stock markets," MPRA Paper 49898, University Library of Munich, Germany.
    18. Michal Adam & Piotr Banbula & Michal Markun, 2015. "International Dependence and Contagion across Asset Classes: The Case of Poland," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(3), pages 254-270, May.
    19. Baumöhl, Eduard, 2013. "Stock market integration between the CEE-4 and the G7 markets: Asymmetric DCC and smooth transition approach," MPRA Paper 43834, University Library of Munich, Germany.

    More about this item

    Keywords

    stock market integration; nonsynchronous trading; Granger causality;

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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