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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.

Suggested Citation

  • 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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    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.
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