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Quantile coherency networks of international stock markets

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  • Baumöhl, Eduard
  • Shahzad, Syed Jawad Hussain

Abstract

This paper uses the novel quantile coherency approach to examine the tail dependence network of 49 international stock markets in the frequency domain. We find that geographical proximity and state of market development are important factors in stock markets networks. Both the short- and long-run connectedness significantly increased after the global financial crisis and spillover is higher during bearish market states, highlighting the possibility of contagion effect mainly among developed markets. Frontier and emerging markets are relatively less connected. These findings have implications for international equity market diversification and risk management.

Suggested Citation

  • Baumöhl, Eduard & Shahzad, Syed Jawad Hussain, 2019. "Quantile coherency networks of international stock markets," EconStor Preprints 194568, ZBW - Leibniz Information Centre for Economics.
  • Handle: RePEc:zbw:esprep:194568
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    References listed on IDEAS

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    1. Baumöhl, Eduard & Kočenda, Evžen & Lyócsa, Štefan & Výrost, Tomáš, 2018. "Networks of volatility spillovers among stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1555-1574.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. Fenghua Wen & Xin Yang & Wei‐Xing Zhou, 2019. "Tail dependence networks of global stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 558-567, January.
    4. Baumöhl, Eduard, 2019. "Are cryptocurrencies connected to forex? A quantile cross-spectral approach," Finance Research Letters, Elsevier, vol. 29(C), pages 363-372.
    5. Boubaker, Sabri & Jouini, Jamel, 2014. "Linkages between emerging and developed equity markets: Empirical evidence in the PMG framework," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 322-335.
    6. 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.
    7. Shahzad, Syed Jawad Hussain & Hernandez, Jose Areola & Rehman, Mobeen Ur & Al-Yahyaee, Khamis Hamed & Zakaria, Muhammad, 2018. "A global network topology of stock markets: Transmitters and receivers of spillover effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 2136-2153.
    8. Gang-Jin Wang & Chi Xie & H. Eugene Stanley, 2018. "Correlation Structure and Evolution of World Stock Markets: Evidence from Pearson and Partial Correlation-Based Networks," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 607-635, March.
    9. Jozef Baruník & Tobias Kley, 2019. "Quantile coherency: A general measure for dependence between cyclical economic variables," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 131-152.
    10. Bollerslev, Tim & Todorov, Viktor & Li, Sophia Zhengzi, 2013. "Jump tails, extreme dependencies, and the distribution of stock returns," Journal of Econometrics, Elsevier, vol. 172(2), pages 307-324.
    11. Gazi I. Kara & Mary Tian & Margaret Yellen, 2015. "Taxonomy of Studies on Interconnectedness," FEDS Notes 2015-07-31, Board of Governors of the Federal Reserve System (U.S.).
    12. Li, Wenwei & Hommel, Ulrich & Paterlini, Sandra, 2018. "Network topology and systemic risk: Evidence from the Euro Stoxx market," Finance Research Letters, Elsevier, vol. 27(C), pages 105-112.
    13. Mensi, Walid & Boubaker, Ferihane Zaraa & Al-Yahyaee, Khamis Hamed & Kang, Sang Hoon, 2018. "Dynamic volatility spillovers and connectedness between global, regional, and GIPSI stock markets," Finance Research Letters, Elsevier, vol. 25(C), pages 230-238.
    14. Coelho, Ricardo & Gilmore, Claire G. & Lucey, Brian & Richmond, Peter & Hutzler, Stefan, 2007. "The evolution of interdependence in world equity markets—Evidence from minimum spanning trees," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 455-466.
    15. Rodriguez, Juan Carlos, 2007. "Measuring financial contagion: A Copula approach," Journal of Empirical Finance, Elsevier, vol. 14(3), pages 401-423, June.
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    More about this item

    Keywords

    quantile coherency; networks; stock markets; extreme negative returns; financial crisis;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • G01 - Financial Economics - - General - - - Financial Crises
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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