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Measuring the network connectedness of global stock markets

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  • Gong, Chen
  • Tang, Pan
  • Wang, Yutong

Abstract

This paper makes an analysis of stock market network connectedness by using transfer entropy method, and discovers that nodes of regions affected by the crisis become closer to each other and the total network connectedness rises during the crisis. Moreover, the closer the stock market is towards the center of the network, the more likely it is affected by the shock. Last but not the least, dynamics of total network connectedness obtained by transfer entropy method is more stable and easier to interpret, avoiding the jumping points in calculation with the VAR model. Theory of transfer entropy shows its great potential in understanding the correlation and information flow of financial markets.

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  • Gong, Chen & Tang, Pan & Wang, Yutong, 2019. "Measuring the network connectedness of global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    • Handle: RePEc:eee:phsmap:v:535:y:2019:i:c:s0378437119313548
    DOI: 10.1016/j.physa.2019.122351
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    1. 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.
    2. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Estimating global bank network connectedness," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(1), pages 1-15, January.
    3. Jinkyu Kim & Gunn Kim & Sungbae An & Young-Kyun Kwon & Sungroh Yoon, 2013. "Entropy-Based Analysis and Bioinformatics-Inspired Integration of Global Economic Information Transfer," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-10, January.
    4. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    5. 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.
    6. Tobias Adrian & Markus K. Brunnermeier, 2016. "CoVaR," American Economic Review, American Economic Association, vol. 106(7), pages 1705-1741, July.
      • Tobias Adrian & Markus K. Brunnermeier, 2008. "CoVaR," Staff Reports 348, Federal Reserve Bank of New York.
      • Tobias Adrian & Markus K. Brunnermeier, 2011. "CoVaR," NBER Working Papers 17454, National Bureau of Economic Research, Inc.
    7. Bekiros, Stelios & Nguyen, Duc Khuong & Sandoval Junior, Leonidas & Uddin, Gazi Salah, 2017. "Information diffusion, cluster formation and entropy-based network dynamics in equity and commodity markets," European Journal of Operational Research, Elsevier, vol. 256(3), pages 945-961.
    8. Mathieu Jacomy & Tommaso Venturini & Sebastien Heymann & Mathieu Bastian, 2014. "ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-12, June.
    9. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
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    Cited by:

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    6. Jianxu Liu & Quanrui Song & Yang Qi & Sanzidur Rahman & Songsak Sriboonchitta, 2020. "Measurement of Systemic Risk in Global Financial Markets and Its Application in Forecasting Trading Decisions," Sustainability, MDPI, vol. 12(10), pages 1-15, May.
    7. Yizhuo Zhang & Rui Chen & Ding Ma, 2020. "A Weighted and Directed Perspective of Global Stock Market Connectedness: A Variance Decomposition and GERGM Framework," Sustainability, MDPI, vol. 12(11), pages 1-23, June.
    8. Manel Youssef & Khaled Mokni & Ahdi Noomen Ajmi, 2021. "Dynamic connectedness between stock markets in the presence of the COVID-19 pandemic: does economic policy uncertainty matter?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
    9. Díaz, Antonio & Esparcia, Carlos & López, Raquel, 2022. "The diversifying role of socially responsible investments during the COVID-19 crisis: A risk management and portfolio performance analysis," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 39-60.
    10. Kazi Sohag & Anna Gainetdinova & Shawkat Hammoudeh & Riad Shams, 2022. "Dynamic Connectedness among Vaccine Companies’ Stock Prices: Before and after Vaccines Released," Mathematics, MDPI, vol. 10(15), pages 1-26, August.

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