Behaviours of Bursa Malaysia: a multidimensional network analysis

In current practice, the similarities between two or more univariate time series of stocks are determined by using the Pearson correlation coefficient (PCC). However, the economic information might be misleading if the analysis applies only the univariate time series of stock price, as each stock is...

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Main Authors: Y., Lim San, Mohd Salleh, Rohayu, Mohd Asrah, Norhaidah
Format: Article
Published: Science Publishing Corporation 2018
Subjects:
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author Y., Lim San
Mohd Salleh, Rohayu
Mohd Asrah, Norhaidah
author_facet Y., Lim San
Mohd Salleh, Rohayu
Mohd Asrah, Norhaidah
author_sort Y., Lim San
collection UTHM
description In current practice, the similarities between two or more univariate time series of stocks are determined by using the Pearson correlation coefficient (PCC). However, the economic information might be misleading if the analysis applies only the univariate time series of stock price, as each stock is denoted by four types of prices. Therefore, multidimensional of stocks are taken into account in this paper. The similarities between two or more multi-dimensional of stocks are quantified by using Random Vector (RV) coefficient. Additionally, an algorithm is proposed due to the computational of RV coefficient is tedious and time-consuming when a large number of stocks are included. In this paper, the Malaysian stock network analysis in univariate and multivariate setting are conducted and analysed by using the PCC, RV coefficient, forest of all possible MSTs and centrality measures. In summary, there is some important economic information could not be brought out by univariate network analysis alone.
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spelling uthm.eprints-43852021-12-02T04:24:02Z http://eprints.uthm.edu.my/4385/ Behaviours of Bursa Malaysia: a multidimensional network analysis Y., Lim San Mohd Salleh, Rohayu Mohd Asrah, Norhaidah HF5691-5716 Business mathematics. Commercial arithmetic Including tables, etc. In current practice, the similarities between two or more univariate time series of stocks are determined by using the Pearson correlation coefficient (PCC). However, the economic information might be misleading if the analysis applies only the univariate time series of stock price, as each stock is denoted by four types of prices. Therefore, multidimensional of stocks are taken into account in this paper. The similarities between two or more multi-dimensional of stocks are quantified by using Random Vector (RV) coefficient. Additionally, an algorithm is proposed due to the computational of RV coefficient is tedious and time-consuming when a large number of stocks are included. In this paper, the Malaysian stock network analysis in univariate and multivariate setting are conducted and analysed by using the PCC, RV coefficient, forest of all possible MSTs and centrality measures. In summary, there is some important economic information could not be brought out by univariate network analysis alone. Science Publishing Corporation 2018 Article PeerReviewed Y., Lim San and Mohd Salleh, Rohayu and Mohd Asrah, Norhaidah (2018) Behaviours of Bursa Malaysia: a multidimensional network analysis. International Journal of Engineering and Technology, 7 (4.3). pp. 229-233. ISSN 2227-524X
spellingShingle HF5691-5716 Business mathematics. Commercial arithmetic Including tables, etc.
Y., Lim San
Mohd Salleh, Rohayu
Mohd Asrah, Norhaidah
Behaviours of Bursa Malaysia: a multidimensional network analysis
title Behaviours of Bursa Malaysia: a multidimensional network analysis
title_full Behaviours of Bursa Malaysia: a multidimensional network analysis
title_fullStr Behaviours of Bursa Malaysia: a multidimensional network analysis
title_full_unstemmed Behaviours of Bursa Malaysia: a multidimensional network analysis
title_short Behaviours of Bursa Malaysia: a multidimensional network analysis
title_sort behaviours of bursa malaysia a multidimensional network analysis
topic HF5691-5716 Business mathematics. Commercial arithmetic Including tables, etc.
work_keys_str_mv AT ylimsan behavioursofbursamalaysiaamultidimensionalnetworkanalysis
AT mohdsallehrohayu behavioursofbursamalaysiaamultidimensionalnetworkanalysis
AT mohdasrahnorhaidah behavioursofbursamalaysiaamultidimensionalnetworkanalysis