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A statistical analysis of UK financial networks

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  • Chu, J.
  • Nadarajah, S.

Abstract

In recent years, with a growing interest in big or large datasets, there has been a rise in the application of large graphs and networks to financial big data. Much of this research has focused on the construction and analysis of the network structure of stock markets, based on the relationships between stock prices. Motivated by Boginski et al. (2005), who studied the characteristics of a network structure of the US stock market, we construct network graphs of the UK stock market using same method. We fit four distributions to the degree density of the vertices from these graphs, the Pareto I, Fréchet, lognormal, and generalised Pareto distributions, and assess the goodness of fit. Our results show that the degree density of the complements of the market graphs, constructed using a negative threshold value close to zero, can be fitted well with the Fréchet and lognormal distributions.

Suggested Citation

  • Chu, J. & Nadarajah, S., 2017. "A statistical analysis of UK financial networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 445-459.
    • Handle: RePEc:eee:phsmap:v:471:y:2017:i:c:p:445-459
    DOI: 10.1016/j.physa.2016.12.073
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    References listed on IDEAS

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    1. Jung, Woo-Sung & Chae, Seungbyung & Yang, Jae-Suk & Moon, Hie-Tae, 2006. "Characteristics of the Korean stock market correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 361(1), pages 263-271.
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    Cited by:

    1. Arash Sioofy Khoojine & Ziyun Feng & Mahboubeh Shadabfar & Negar Sioofy Khoojine, 2023. "Analyzing volatility patterns in the Chinese stock market using partial mutual information-based distances," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(12), pages 1-21, December.

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