A proposed algorithm of random vector in measuring similarity for network topology of Bursa Malaysia

The stock market is a complex system where the interrelationships between the stocks are complicated because it is in multivariate time series setting which consists of opening, highest, lowest and closing prices. Basically, the Pearson correlation coefficient (PCC) is applied to measure the similar...

Full description

Saved in:

Bibliographic Details
Main Author:	Lim, San Yee
Format:	Thesis
Language:	English English English
Published:	2018
Subjects:	QA Mathematics
Online Access:	http://eprints.uthm.edu.my/300/1/24p%20LIM%20SAN%20YEE.pdf http://eprints.uthm.edu.my/300/2/LIM%20SAN%20YEE%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/300/3/LIM%20SAN%20YEE%20WATERMARK.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-uthm-ep.300
record_format	uketd_dc
spelling	my-uthm-ep.3002021-07-21T03:30:19Z A proposed algorithm of random vector in measuring similarity for network topology of Bursa Malaysia 2018-10 Lim, San Yee QA Mathematics The stock market is a complex system where the interrelationships between the stocks are complicated because it is in multivariate time series setting which consists of opening, highest, lowest and closing prices. Basically, the Pearson correlation coefficient (PCC) is applied to measure the similarity between two or more univariate time series of stocks. However, the economic information from other variables may inaccurate if the analysis is conducted by applying single variable only. Therefore, multi-dimensional of stocks are considered in this thesis. The similarities between two or more multi-dimensional of stocks are quantified by using Random Vector (RV) coefficient. Based on the preliminary analysis, the computational of RV coefficient is difficult, time-consuming, and tedious when a large number of stocks are involved. Hence, to ease the calculation process and improve the computational efficiency of RV coefficient, an algorithm is proposed. The proposed algorithm is able to measure the similarities among all pairs of stocks in Bursa Malaysia at once. The calculation process of RV coefficient among all pairs of stocks can be shortened and eased as the proposed algorithm consists of time complexity of order of O(n2). The behaviors and interactions among the stocks in Bursa Malaysia are then determined by using the Forest of all possible minimum spanning trees. In this thesis, MK Land Holdings Berhad was found out to be the predominant stock in Bursa Malaysia as it displays a star-like structure and is located at the central hub of the network. 2018-10 Thesis http://eprints.uthm.edu.my/300/ http://eprints.uthm.edu.my/300/1/24p%20LIM%20SAN%20YEE.pdf text en public http://eprints.uthm.edu.my/300/2/LIM%20SAN%20YEE%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/300/3/LIM%20SAN%20YEE%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Faculty of Applied Sciences and Technology
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	QA Mathematics
spellingShingle	QA Mathematics Lim, San Yee A proposed algorithm of random vector in measuring similarity for network topology of Bursa Malaysia
description	The stock market is a complex system where the interrelationships between the stocks are complicated because it is in multivariate time series setting which consists of opening, highest, lowest and closing prices. Basically, the Pearson correlation coefficient (PCC) is applied to measure the similarity between two or more univariate time series of stocks. However, the economic information from other variables may inaccurate if the analysis is conducted by applying single variable only. Therefore, multi-dimensional of stocks are considered in this thesis. The similarities between two or more multi-dimensional of stocks are quantified by using Random Vector (RV) coefficient. Based on the preliminary analysis, the computational of RV coefficient is difficult, time-consuming, and tedious when a large number of stocks are involved. Hence, to ease the calculation process and improve the computational efficiency of RV coefficient, an algorithm is proposed. The proposed algorithm is able to measure the similarities among all pairs of stocks in Bursa Malaysia at once. The calculation process of RV coefficient among all pairs of stocks can be shortened and eased as the proposed algorithm consists of time complexity of order of O(n2). The behaviors and interactions among the stocks in Bursa Malaysia are then determined by using the Forest of all possible minimum spanning trees. In this thesis, MK Land Holdings Berhad was found out to be the predominant stock in Bursa Malaysia as it displays a star-like structure and is located at the central hub of the network.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Lim, San Yee
author_facet	Lim, San Yee
author_sort	Lim, San Yee
title	A proposed algorithm of random vector in measuring similarity for network topology of Bursa Malaysia
title_short	A proposed algorithm of random vector in measuring similarity for network topology of Bursa Malaysia
title_full	A proposed algorithm of random vector in measuring similarity for network topology of Bursa Malaysia
title_fullStr	A proposed algorithm of random vector in measuring similarity for network topology of Bursa Malaysia
title_full_unstemmed	A proposed algorithm of random vector in measuring similarity for network topology of Bursa Malaysia
title_sort	proposed algorithm of random vector in measuring similarity for network topology of bursa malaysia
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Faculty of Applied Sciences and Technology
publishDate	2018
url	http://eprints.uthm.edu.my/300/1/24p%20LIM%20SAN%20YEE.pdf http://eprints.uthm.edu.my/300/2/LIM%20SAN%20YEE%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/300/3/LIM%20SAN%20YEE%20WATERMARK.pdf
_version_	1747830576913580032

A proposed algorithm of random vector in measuring similarity for network topology of Bursa Malaysia

Similar Items