Centrality Measures for Shariah-Compliant Stocks Network during Global Financial Crisis: A Case of Bursa Malaysia

The correlation of stocks can be classified as a complex system in which have difficulties to visualize as a whole. In addition, the main challenge is to identify which stock plays a crucial stock in the financial market. Thus, the objective of this study is to construct a financial network of 121 s...

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Bibliographic Details
Main Authors: Bahaludin, Hafizah, Mahamood, Fatin Nur Amirah, Abdullah, Mimi Hafizah
Format: Conference or Workshop Item
Language:English
English
English
English
Published: 2020
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Online Access:http://irep.iium.edu.my/92237/8/Acceptance%20Letter_OR-6246_Centrality.pdf
http://irep.iium.edu.my/92237/25/92237_Centrality%20Measures%20for%20Shariah-Compliant.pdf
http://irep.iium.edu.my/92237/26/92237_Centrality%20Measures%20for%20Shariah-Compliant%20Stocks%20Network.pdf
http://irep.iium.edu.my/92237/27/92237_Centrality%20Measures%20for%20Shariah-Compliant%20Stocks%20Network%20during%20Global%20Financial%20Crisis.pdf
http://irep.iium.edu.my/92237/
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Institution: Universiti Islam Antarabangsa Malaysia
Language: English
English
English
English
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Summary:The correlation of stocks can be classified as a complex system in which have difficulties to visualize as a whole. In addition, the main challenge is to identify which stock plays a crucial stock in the financial market. Thus, the objective of this study is to construct a financial network of 121 shariah-compliant securities traded in Bursa Malaysia from the year 2008 to the year 2009, by focusing on the global financial crisis. This paper used the minimum spanning tree (MST) approach to construct the network. Further, this study employed various centrality measures such as degree, betweenness, closeness, eigenvector, and eccentricity centrality in order to identify the most influential stock in the network. Then, the principal component analysis (PCA) is used to summarise the performance of centrality measure to select the central node of the network. This finding helps investors by providing an overview of the relationship of each stock as a whole and identifies the key stock in the market during a turbulent period.