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Grouping characteristics of industry sectors in financial markets

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  • Oh, Gabjin

Abstract

We investigated the grouping coefficients of industrial sectors in the stock network based on stock data for the U.S. and Korean stock markets. These complex networks were modeled using the minimal spanning tree (MST) method. We propose a novel approach based on the shortest path length (SPL) between stocks to quantify the grouping characteristics of the industrial sectors. We find that the grouping coefficients for the industrial sector in the U.S. are larger than those of the Korean stock market. In particular, for the Korean stock market the conglomerates, comprised of a diverse of industrial companies, have a significant grouping coefficient.

Suggested Citation

  • Oh, Gabjin, 2014. "Grouping characteristics of industry sectors in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 261-268.
    • Handle: RePEc:eee:phsmap:v:395:y:2014:i:c:p:261-268
    DOI: 10.1016/j.physa.2013.09.031
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    References listed on IDEAS

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    1. Mantegna,Rosario N. & Stanley,H. Eugene, 2007. "Introduction to Econophysics," Cambridge Books, Cambridge University Press, number 9780521039871, October.
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    2. Nobi, Ashadun & Alam, Shafiqul & Lee, Jae Woo, 2017. "Dynamic of consumer groups and response of commodity markets by principal component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 337-344.
    3. Wang, Yanli & Li, Huajiao & Guan, Jianhe & Liu, Nairong, 2019. "Similarities between stock price correlation networks and co-main product networks: Threshold scenarios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 66-77.
    4. Djauhari, Maman Abdurachman & Gan, Siew Lee, 2015. "Optimality problem of network topology in stocks market analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 108-114.
    5. Shi, Huai-Long & Chen, Huayi, 2024. "Understanding co-movements based on heterogeneous information associations," International Review of Financial Analysis, Elsevier, vol. 94(C).
    6. Nobi, Ashadun & Maeng, Seong Eun & Ha, Gyeong Gyun & Lee, Jae Woo, 2014. "Effects of global financial crisis on network structure in a local stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 135-143.
    7. Shi, Huai-Long & Chen, Huayi, 2023. "Revisiting asset co-movement: Does network topology really matter?," Research in International Business and Finance, Elsevier, vol. 66(C).

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