IDEAS home Printed from https://ideas.repec.org/a/ibn/masjnl/v13y2019i7p80.html
   My bibliography  Save this article

A Network Analysis of Shariah-Compliant Stocks across Global Financial Crisis: A Case of Malaysia

Author

Listed:
  • Fatin Nur Amirah Mahamood
  • Hafizah Bahaludin
  • Mimi Hafizah Abdullah

Abstract

Financial network is a complex system in which transaction of securities take place. Due to its complexity, a minimum spanning tree (MST) technique is used to visualize the structure. This paper investigates the topological structure of 125 shariah-compliant stocks traded in Bursa Malaysia from the year 2000 until 2017. Financial networks of the shariah-compliant stocks are constructed using MST for three duration periods namely the pre-crisis, during crisis and post-crisis. To determine the important stocks in the networks, centrality measures are applied such as degree centrality, betweenness centrality, closeness centrality and eigenvector centrality. Lastly, overall centrality measures are computed to identify the overall characteristic of each node. The findings showed that, KUB Malaysia Berhad was the most influential stock in the pre-crisis and crisis periods. While, MK Land Holdings was the main stock in the post-crisis network.

Suggested Citation

  • Fatin Nur Amirah Mahamood & Hafizah Bahaludin & Mimi Hafizah Abdullah, 2019. "A Network Analysis of Shariah-Compliant Stocks across Global Financial Crisis: A Case of Malaysia," Modern Applied Science, Canadian Center of Science and Education, vol. 13(7), pages 1-80, July.
  • Handle: RePEc:ibn:masjnl:v:13:y:2019:i:7:p:80
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/mas/article/download/0/0/39962/41031
    Download Restriction: no

    File URL: https://ccsenet.org/journal/index.php/mas/article/view/0/39962
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. Djauhari, Maman Abdurachman & Gan, Siew Lee, 2015. "Optimality problem of network topology in stocks market analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 108-114.
    3. Djauhari, Maman A., 2012. "A robust filter in stock networks analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 5049-5057.
    4. Majapa, Mohamed & Gossel, Sean Joss, 2016. "Topology of the South African stock market network across the 2008 financial crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 35-47.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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.
    2. Coletti, Paolo, 2016. "Comparing minimum spanning trees of the Italian stock market using returns and volumes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 246-261.
    3. Cao, Guangxi & Zhang, Qi & Li, Qingchen, 2017. "Causal relationship between the global foreign exchange market based on complex networks and entropy theory," Chaos, Solitons & Fractals, Elsevier, vol. 99(C), pages 36-44.
    4. Djauhari, Maman Abdurachman & Gan, Siew Lee, 2015. "Optimality problem of network topology in stocks market analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 108-114.
    5. Cheng Juan Zhan & William Rea & Alethea Rea, 2016. "Stock Selection as a Problem in Phylogenetics—Evidence from the ASX," IJFS, MDPI, vol. 4(4), pages 1-19, September.
    6. Samuel Ugwu & Pierre Miasnikof & Yuri Lawryshyn, 2023. "Distance Correlation Market Graph: The Case of S&P500 Stocks," Mathematics, MDPI, vol. 11(18), pages 1-13, September.
    7. Zeitsch, Peter J. & Davis, Tom P., 2021. "The price determinants of contingent convertible bonds," Finance Research Letters, Elsevier, vol. 43(C).
    8. Hannah Cheng Juan Zhan & William Rea & Alethea Rea, 2015. "A Comparison of Three Network Portfolio Selection Methods -- Evidence from the Dow Jones," Working Papers in Economics 15/02, University of Canterbury, Department of Economics and Finance.
    9. Bilal Ahmed Memon & Rabia Tahir, 2021. "Examining Network Structures and Dynamics of World Energy Companies in Stock Markets: A Complex Network Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 11(4), pages 329-344.
    10. Papana, Angeliki & Kyrtsou, Catherine & Kugiumtzis, Dimitris & Diks, Cees, 2017. "Financial networks based on Granger causality: A case study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 65-73.
    11. Chuangxia Huang & Xian Zhao & Renli Su & Xiaoguang Yang & Xin Yang, 2022. "Dynamic network topology and market performance: A case of the Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1962-1978, April.
    12. Mbatha, Vusisizwe Moses & Alovokpinhou, Sedjro Aaron, 2022. "The structure of the South African stock market network during COVID-19 hard lockdown," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    13. Kalyagin, V.A. & Koldanov, A.P. & Koldanov, P.A. & Pardalos, P.M. & Zamaraev, V.A., 2014. "Measures of uncertainty in market network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 59-70.
    14. He, Chengying & Wen, Zhang & Huang, Ke & Ji, Xiaoqin, 2022. "Sudden shock and stock market network structure characteristics: A comparison of past crisis events," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    15. Nguyen, Q. & Nguyen, N.K. K. & Nguyen, L.H. N., 2019. "Dynamic topology and allometric scaling behavior on the Vietnamese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 235-243.
    16. khoojine, Arash Sioofy & Han, Dong, 2019. "Network analysis of the Chinese stock market during the turbulence of 2015–2016 using log-returns, volumes and mutual information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1091-1109.
    17. Dariusz Siudak, 2021. "Sectoral Analysis of the US Stock Market through Complex Networks," European Research Studies Journal, European Research Studies Journal, vol. 0(3B), pages 951-966.
    18. Huang, Chuangxia & Deng, Yunke & Yang, Xiaoguang & Cao, Jinde & Yang, Xin, 2021. "A network perspective of comovement and structural change: Evidence from the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 76(C).
    19. Biplab Bhattacharjee & Muhammad Shafi & Animesh Acharjee, 2016. "Investigating the Influence Relationship Models for Stocks in Indian Equity Market: A Weighted Network Modelling Study," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-33, November.
    20. Li, Jianxuan & Shi, Yingying & Cao, Guangxi, 2018. "Topology structure based on detrended cross-correlation coefficient of exchange rate network of the belt and road countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1140-1151.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ibn:masjnl:v:13:y:2019:i:7:p:80. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.