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A Hierarchical View of a National Stock Market as a Complex Network

Author

Listed:
  • Yusuf Yargı BAYDİLLİ

    ()

  • Şafak BAYIR

    ()

  • İlker TÜRKER

    () (Karabuk University)

Abstract

We created a financial network for Borsa Istanbul 100 Index (BIST–100) which forms of N=100 stocks that bargained during T=2 years (2011– 2013). We analyzed the market via minimum spanning tree (MST) and hierarchical tree (HT) by using filtered correlation matrix. While using hierarchical methods in order to investigate factors that affecting grouping of stocks, we have taken account the other statistical and data mining methods to examine success of stock correlation network concept for portfolio optimization, risk management and crisis analysis. We observed that financial stocks, especially Banks, are central position of the network and control information flow. Besides the sectoral and sub-sectoral behavior, corporations play role at grouping of stocks. Finally, this technique provided important tips for determining risky stocks in market.

Suggested Citation

  • Yusuf Yargı BAYDİLLİ & Şafak BAYIR & İlker TÜRKER, 2017. "A Hierarchical View of a National Stock Market as a Complex Network," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 51(1), pages 205-222.
  • Handle: RePEc:cys:ecocyb:v:50:y:2017:i:1:p:205-222
    as

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    References listed on IDEAS

    as
    1. G. Bonanno & F. Lillo & R. N. Mantegna, 2001. "High-frequency cross-correlation in a set of stocks," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 96-104.
    2. E. Kantar & B. Deviren & M. Keskin, 2011. "Investigation of major international and Turkish companies via hierarchical methods and bootstrap approach," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 84(2), pages 339-350, November.
    3. Huang, Wei-Qiang & Zhuang, Xin-Tian & Yao, Shuang, 2009. "A network analysis of the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2956-2964.
    4. Heimo, Tapio & Saramäki, Jari & Onnela, Jukka-Pekka & Kaski, Kimmo, 2007. "Spectral and network methods in the analysis of correlation matrices of stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 147-151.
    5. Çukur, Sadik & Eryiğit, Mehmet & Eryiğit, Resul, 2007. "Cross correlations in an emerging market financial data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 555-564.
    6. Kantar, Ersin & Keskin, Mustafa & Deviren, Bayram, 2012. "Analysis of the effects of the global financial crisis on the Turkish economy, using hierarchical methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2342-2352.
    7. Coelho, Ricardo & Gilmore, Claire G. & Lucey, Brian & Richmond, Peter & Hutzler, Stefan, 2007. "The evolution of interdependence in world equity markets—Evidence from minimum spanning trees," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 455-466.
    8. Hokky Situngkir & Yohanes Surya, 2005. "On Stock Market Dynamics through Ultrametricity of Minimum Spanning Tree," Macroeconomics 0505010, EconWPA.
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    More about this item

    Keywords

    Stock correlation network; stock market; financial network; correlation-based clustering; degree distribution; Istanbul Stock Exchange; minimum spanning tree; hierarchical tree.;

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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