Abstract

The stock market has constituted a complex system since the interrelationships among the stocks are complicated and unpredictable. Moreover, the stock price does not stagnate at a certain price all the time but the price keeps changing from minute to minute during the transaction hours. Thus, it is quite difficult to indicate which stock influences the performances of other stocks as well as the behaviours of the stocks in a network. The economic information might be misleading and incomplete if the analysis applies with univariate time series of stock price only as each stock is represented by four features of the price. To obtain the complete information of the Bursa Malaysia stock network as well as the interrelationships among the stocks, multivariate time series of stocks are measured by using RV coefficient. Besides, minimum spanning tree and centrality measures are applied in this paper in order to construct the stock network virtually and determine the behaviours of the stocks by using the recent data of top 100 stocks in Bursa Malaysia.

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