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Structure and causality relations in a global network of financial companies

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  • Leonidas Sandoval Junior

Abstract

This work uses the stocks of the 197 largest companies in the world, in terms of market capitalization, in the financial area in the study of causal relationships between them using Transfer Entropy, which is calculated using the stocks of those companies and their counterparts lagged by one day. With this, we can assess which companies influence others according to sub-areas of the financial sector, which are banks, diversified financial services, savings and loans, insurance, private equity funds, real estate investment companies, and real estate trust funds. We also analyzed the causality relations between those stocks and the network formed by them based on this measure, verifying that they cluster mainly according to countries of origin, and then by industry and sub-industry. Then we collected data on the stocks of companies in the financial sector of some countries that are suffering the most with the current credit crisis: Greece, Cyprus, Ireland, Spain, Portugal, and Italy, and assess, also using transfer entropy, which companies from the largest 197 are most affected by the stocks of these countries in crisis. The intention is to map a network of influences that may be used in the study of possible contagions originating in those countries in financial crisis.

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  • Leonidas Sandoval Junior, 2013. "Structure and causality relations in a global network of financial companies," Papers 1310.5388, arXiv.org.
    • Handle: RePEc:arx:papers:1310.5388
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    References listed on IDEAS

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    1. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    2. Upper, Christian, 2011. "Simulation methods to assess the danger of contagion in interbank markets," Journal of Financial Stability, Elsevier, vol. 7(3), pages 111-125, August.
    3. Onnela, J.-P. & Chakraborti, A. & Kaski, K. & Kertész, J., 2003. "Dynamic asset trees and Black Monday," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 247-252.
    4. Sitabhra Sinha & Raj Kumar Pan, 2007. "Uncovering the Internal Structure of the Indian Financial Market: Cross-correlation behavior in the NSE," Papers 0704.2115, arXiv.org.
    5. Ausloos, M. & Lambiotte, R., 2007. "Clusters or networks of economies? A macroeconomy study through Gross Domestic Product," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 16-21.
    6. Leonidas Junior Sandoval, 2013. "Cluster formation and evolution in networks of financial market indices," Algorithmic Finance, IOS Press, vol. 2(1), pages 3-43.
    7. J.-P. Onnela & K. Kaski & J. Kertész, 2004. "Clustering and information in correlation based financial networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 38(2), pages 353-362, March.
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    Cited by:

    1. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.

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