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Complexity of major UK companies between 2006 and 2010: Hierarchical structure method approach

Listed author(s):
  • Ulusoy, Tolga
  • Keskin, Mustafa
  • Shirvani, Ayoub
  • Deviren, Bayram
  • Kantar, Ersin
  • Çaǧrı Dönmez, Cem
Registered author(s):

    This study reports on topology of the top 40 UK companies that have been analysed for predictive verification of markets for the period 2006–2010, applying the concept of minimal spanning tree and hierarchical tree (HT) analysis. Construction of the minimal spanning tree (MST) and the hierarchical tree (HT) is confined to a brief description of the methodology and a definition of the correlation function between a pair of companies based on the London Stock Exchange (LSE) index in order to quantify synchronization between the companies. A derivation of hierarchical organization and the construction of minimal-spanning and hierarchical trees for the 2006–2008 and 2008–2010 periods have been used and the results validate the predictive verification of applied semantics. The trees are known as useful tools to perceive and detect the global structure, taxonomy and hierarchy in financial data. From these trees, two different clusters of companies in 2006 were detected. They also show three clusters in 2008 and two between 2008 and 2010, according to their proximity. The clusters match each other as regards their common production activities or their strong interrelationship. The key companies are generally given by major economic activities as expected. This work gives a comparative approach between MST and HT methods from statistical physics and information theory with analysis of financial markets that may give new valuable and useful information of the financial market dynamics.

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    Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

    Volume (Year): 391 (2012)
    Issue (Month): 21 ()
    Pages: 5121-5131

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    Handle: RePEc:eee:phsmap:v:391:y:2012:i:21:p:5121-5131
    DOI: 10.1016/j.physa.2012.01.026
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    1. Miccichè, Salvatore & Bonanno, Giovanni & Lillo, Fabrizio & N. Mantegna, Rosario, 2003. "Degree stability of a minimum spanning tree of price return and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 66-73.
    2. Gilmore, Claire G. & Lucey, Brian M. & Boscia, Marian W., 2010. "Comovements in government bond markets: A minimum spanning tree analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4875-4886.
    3. Zhou, Wei-Xing & Sornette, Didier, 2009. "A case study of speculative financial bubbles in the South African stock market 2003–2006," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(6), pages 869-880.
    4. Gilmore, Claire G. & Lucey, Brian M. & Boscia, Marian, 2008. "An ever-closer union? Examining the evolution of linkages of European equity markets via minimum spanning trees," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(25), pages 6319-6329.
    5. Mustafa Keskin & Bayram Deviren & Yusuf Kocakaplan, 2010. "Topology of the correlation networks among major currencies using hierarchical structure methods," Papers 1010.5653,
    6. Coelho, R. & Hutzler, S. & Repetowicz, P. & Richmond, P., 2007. "Sector analysis for a FTSE portfolio of stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 615-626.
    7. Sornette, Didier & Woodard, Ryan & Zhou, Wei-Xing, 2009. "The 2006–2008 oil bubble: Evidence of speculation, and prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1571-1576.
    8. Lee, Sun Young & Hwang, Dong Il & Kim, Min Jae & Koh, In Gyu & Kim, Soo Yong, 2011. "Cross-correlations in volume space: Differences between buy and sell volumes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(5), pages 837-846.
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