The Causal Relationship Between Stock Markets: Awavelet Transform-Based Approach

Dalam tahun kebelakangan ini, harga pasaran saham adalah salah satu daripada petunjuk ekonomi yang paling penting yang mendedahkan status ekonomi sesuatu negara serta menerokai hubungan kalangan negara-negara di dunia. Seperti yang sedia maklum, harga pasaran saham adalah tidak menentu dan mengan...

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Main Author: Ahmed Dghais, Amel Abdoullah
Format: Thesis
Language:English
Published: 2016
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Online Access:http://eprints.usm.my/32102/1/AMEL_ABDOULLAH_AHMED_DGHAIS_24%28NN%29.pdf
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spelling my-usm-ep.321022019-04-12T05:25:15Z The Causal Relationship Between Stock Markets: Awavelet Transform-Based Approach 2016-08 Ahmed Dghais, Amel Abdoullah QA1 Mathematics (General) Dalam tahun kebelakangan ini, harga pasaran saham adalah salah satu daripada petunjuk ekonomi yang paling penting yang mendedahkan status ekonomi sesuatu negara serta menerokai hubungan kalangan negara-negara di dunia. Seperti yang sedia maklum, harga pasaran saham adalah tidak menentu dan mengandungi data hingar yang memberi kesan kepada ketepatan dan kesahihan keputusan sesuatu model. Oleh itu, para penyelidik semasa memberi tumpuan kepada memeriksa kaedah penguraian untuk menyelesaikan masalah data hingar dan menentukan kemeruapan pasaran saham dengan lebih tepat. Terkini, penurasan wavelet telah digunakan sebagai alat yang berkesan untuk mengurangkan hingar dalam siri masa kewangan. Selain itu, penurasan wavelet mempunyai beberapa ciri-ciri yang lebih berbanding penuras yang lain. Maka dari sudut ini, tesis ini mencadangkan teknik yang berbeza untuk menyiasat hubungan antara pasaran saham dengan menggabungkan penurasan wavelet dan model tradisional dalam usaha menyelesaikan masalah kesan hingar dalam data siri masa kewangan, dan mendapatkan keputusan lebih tepat. Stock market index has recently become one of the most important economic indicators that reveals the economic status of a country and explores the causal relationship among countries. Stock market indices are typically chaotic and contain noise data, which affect the accuracy and validity of the results of some models. Therefore, this study focuses on decomposition methods to solve the problem on noisy data and to determine stock market volatilities accurately. Recently, wavelet filtering has been applied as an efficient tool for reducing noise in financial time series. Wavelet filtering exhibits several properties that are not found in other filters. Thus, this thesis proposes different techniques to investigate causal relationships among stock markets by combining wavelet filtering and traditional models to solve the noise problem in financial time series data and therefor to obtain accurate results. 2016-08 Thesis http://eprints.usm.my/32102/ http://eprints.usm.my/32102/1/AMEL_ABDOULLAH_AHMED_DGHAIS_24%28NN%29.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Matematik (School of Mathematical Sciences)
institution Universiti Sains Malaysia
collection USM Institutional Repository
language English
topic QA1 Mathematics (General)
spellingShingle QA1 Mathematics (General)
Ahmed Dghais, Amel Abdoullah
The Causal Relationship Between Stock Markets: Awavelet Transform-Based Approach
description Dalam tahun kebelakangan ini, harga pasaran saham adalah salah satu daripada petunjuk ekonomi yang paling penting yang mendedahkan status ekonomi sesuatu negara serta menerokai hubungan kalangan negara-negara di dunia. Seperti yang sedia maklum, harga pasaran saham adalah tidak menentu dan mengandungi data hingar yang memberi kesan kepada ketepatan dan kesahihan keputusan sesuatu model. Oleh itu, para penyelidik semasa memberi tumpuan kepada memeriksa kaedah penguraian untuk menyelesaikan masalah data hingar dan menentukan kemeruapan pasaran saham dengan lebih tepat. Terkini, penurasan wavelet telah digunakan sebagai alat yang berkesan untuk mengurangkan hingar dalam siri masa kewangan. Selain itu, penurasan wavelet mempunyai beberapa ciri-ciri yang lebih berbanding penuras yang lain. Maka dari sudut ini, tesis ini mencadangkan teknik yang berbeza untuk menyiasat hubungan antara pasaran saham dengan menggabungkan penurasan wavelet dan model tradisional dalam usaha menyelesaikan masalah kesan hingar dalam data siri masa kewangan, dan mendapatkan keputusan lebih tepat. Stock market index has recently become one of the most important economic indicators that reveals the economic status of a country and explores the causal relationship among countries. Stock market indices are typically chaotic and contain noise data, which affect the accuracy and validity of the results of some models. Therefore, this study focuses on decomposition methods to solve the problem on noisy data and to determine stock market volatilities accurately. Recently, wavelet filtering has been applied as an efficient tool for reducing noise in financial time series. Wavelet filtering exhibits several properties that are not found in other filters. Thus, this thesis proposes different techniques to investigate causal relationships among stock markets by combining wavelet filtering and traditional models to solve the noise problem in financial time series data and therefor to obtain accurate results.
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Ahmed Dghais, Amel Abdoullah
author_facet Ahmed Dghais, Amel Abdoullah
author_sort Ahmed Dghais, Amel Abdoullah
title The Causal Relationship Between Stock Markets: Awavelet Transform-Based Approach
title_short The Causal Relationship Between Stock Markets: Awavelet Transform-Based Approach
title_full The Causal Relationship Between Stock Markets: Awavelet Transform-Based Approach
title_fullStr The Causal Relationship Between Stock Markets: Awavelet Transform-Based Approach
title_full_unstemmed The Causal Relationship Between Stock Markets: Awavelet Transform-Based Approach
title_sort causal relationship between stock markets: awavelet transform-based approach
granting_institution Universiti Sains Malaysia
granting_department Pusat Pengajian Sains Matematik (School of Mathematical Sciences)
publishDate 2016
url http://eprints.usm.my/32102/1/AMEL_ABDOULLAH_AHMED_DGHAIS_24%28NN%29.pdf
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