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Information transfer network of global market indices

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  • Kim, Yup
  • Kim, Jinho
  • Yook, Soon-Hyung

Abstract

We study the topological properties of the information transfer networks (ITN) of the global financial market indices for six different periods. ITN is a directed weighted network, in which the direction and weight are determined by the transfer entropy between market indices. By applying the threshold method, it is found that ITN undergoes a crossover from the complete graph to a small-world (SW) network. SW regime of ITN for a global crisis is found to be much more enhanced than that for ordinary periods. Furthermore, when ITN is in SW regime, the average clustering coefficient is found to be synchronized with average volatility of markets. We also compare the results with the topological properties of correlation networks.

Suggested Citation

  • Kim, Yup & Kim, Jinho & Yook, Soon-Hyung, 2015. "Information transfer network of global market indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 39-45.
    • Handle: RePEc:eee:phsmap:v:430:y:2015:i:c:p:39-45
    DOI: 10.1016/j.physa.2015.02.081
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    References listed on IDEAS

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    1. Bouchaud,Jean-Philippe & Potters,Marc, 2003. "Theory of Financial Risk and Derivative Pricing," Cambridge Books, Cambridge University Press, number 9780521819169, October.
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    Cited by:

    1. Nie, Chun-Xiao, 2023. "Time-varying characteristics of information flow networks in the Chinese market: An analysis based on sector indices," Finance Research Letters, Elsevier, vol. 54(C).
    2. Bhattacharjee, Biplab & Kumar, Rajiv & Senthilkumar, Arunachalam, 2022. "Unidirectional and bidirectional LSTM models for edge weight predictions in dynamic cross-market equity networks," International Review of Financial Analysis, Elsevier, vol. 84(C).
    3. Bowen Zhang & Jinping Lin & Man Luo & Changxian Zeng & Jiajia Feng & Meiqi Zhou & Fuying Deng, 2022. "Changes in Public Sentiment under the Background of Major Emergencies—Taking the Shanghai Epidemic as an Example," IJERPH, MDPI, vol. 19(19), pages 1-20, October.
    4. Lu, Jingen & Chen, Xiaohong & Liu, Xiaoxing, 2018. "Stock market information flow: Explanations from market status and information-related behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 837-848.

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    Econophysics; Complex networks;

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