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.
Highlights
A network can be defined as a set of items, called vertices or nodes and connections between the nodes as links or edges
The data collected consists of 125 stocks which are consistently classified in eight economic sectors based on Shariah Advisory Council (SAC)’s list traded since the year 2000 until 2017
During crisis period, only 124 companies are used since Teo Guan Lee Construction (9396) from the consumer sector is removed due to the unavailability of data
Summary
A network can be defined as a set of items, called vertices or nodes and connections between the nodes as links or edges. A financial market is a trading floor where transaction of securities consists of equities, bonds, currencies, and derivatives take place. A financial market network consists of nodes which represent the stocks and the links represent the correlation between stocks. The fluctuation of a stock’s price from time to time exhibits a very complicated and complex system since the changes occur in the stock prices will affect other stock prices too. This complexity makes the financial network a fascinating network which attracted much attention from many researchers to further investigate its structures and characterizations. The complex correlation elements make the financial network difficult to visualize
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