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Determination of Systemically Important Companies with Cross-Shareholding Network Analysis: A Case Study from an Emerging Market

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  • Hossein Dastkhan

    (Department of Industrial Engineering and Management Systems, AmirKabir University of Technology, Hafez St., Tehran 15916-34311, Iran)

  • Naser Shams Gharneh

    (Department of Industrial Engineering and Management Systems, AmirKabir University of Technology, Hafez St., Tehran 15916-34311, Iran)

Abstract

Systemic risk events constitute an important issue in current financial systems. A leading course of action used to mitigate such events is identification of systemically important agents in order to implement the prudential policies in a financial system. In this paper, a bi-level cross-shareholding network of the stock market is considered according to direct and integrated ownership structure. Furthermore, different systemic risk indices are applied to identify systemically important companies in an early warning system. Results of application of these indices on cross-shareholding data from Tehran Stock Exchange show that integrated network indices produce more reliable results. Moreover, results of statistical analysis of the networks indicated the existence of scale-free characteristics in the TSE cross-shareholding network.

Suggested Citation

  • Hossein Dastkhan & Naser Shams Gharneh, 2016. "Determination of Systemically Important Companies with Cross-Shareholding Network Analysis: A Case Study from an Emerging Market," IJFS, MDPI, vol. 4(3), pages 1-17, June.
    • Handle: RePEc:gam:jijfss:v:4:y:2016:i:3:p:13-:d:72715
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    Cited by:

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    3. Yun Feng & Xin Li, 2022. "The Cross-Shareholding Network and Risk Contagion from Stochastic Shocks: An Investigation Based on China’s Market," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 357-381, January.
    4. Li, Huajiao & Ren, Huijun & An, Haizhong & Ma, Ning & Yan, Lili, 2021. "Multiplex cross-shareholding relations in the global oil & gas industry chain based on multilayer network modeling," Energy Economics, Elsevier, vol. 95(C).
    5. Jose Arreola Hernandez & Sang Hoon Kang & Seong‐Min Yoon, 2022. "Interdependence and portfolio optimisation of bank equity returns from developed and emerging Europe," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 678-696, January.
    6. Hossein Dastkhan & Naser Shams Gharneh, 2019. "Simulation of Contagion in the Stock Markets Using Cross-Shareholding Networks: A Case from an Emerging Market," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1071-1101, March.
    7. Ömer Akgüller & Mehmet Ali Balcı & Larissa M. Batrancea & Lucian Gaban, 2023. "Path-Based Visibility Graph Kernel and Application for the Borsa Istanbul Stock Network," Mathematics, MDPI, vol. 11(6), pages 1-25, March.
    8. Hossein Dastkhan, 2021. "Network‐based early warning system to predict financial crisis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 594-616, January.
    9. Jung, Jihye & Choi, In-Chan, 2022. "A multi-objective optimization model for dissolving circular shareholdings in Korean conglomerates," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    10. Jose Arreola Hernandez & Sang Hoon Kang & Ron P. McIver & Seong-Min Yoon, 2021. "Network Interdependence and Optimization of Bank Portfolios from Developed and Emerging Asia Pacific Countries," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(4), pages 613-647, December.
    11. Li, Zhenghui & Chen, Bin & Lu, Siting & Liao, Gaoke, 2024. "The impact of financial institutions' cross-shareholdings on risk-taking," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 1526-1544.
    12. Yun Feng & Xin Li, 2021. "Does cross-shareholding lead to China's stock returns comovement? Evidence from a GMM-based spatial AR model," Empirical Economics, Springer, vol. 61(6), pages 3213-3237, December.

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