Detecting the Fluctuations in Large Samples Using Wavelet Transform

structure break is a famous features in stock market data that gain consideration from many kind of researchers. Generally, it occurs because of unexpected variations in the strategy of the government. Recently, wavelet method (WT) is more popular in the stock market data analysis since it has signi...

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Bibliographic Details
Published inModern applied science Vol. 12; no. 12; p. 245
Main Authors Wadi, S. AL, Obeidat, Ghassan
Format Journal Article
LanguageEnglish
Published 26.11.2018
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Summary:structure break is a famous features in stock market data that gain consideration from many kind of researchers. Generally, it occurs because of unexpected variations in the strategy of the government. Recently, wavelet method (WT) is more popular in the stock market data analysis since it has significant benefits than the other traditional methods. In this research paper, the discrete wavelet transform (DWT) based on Daubechies model will be used to capture the structure break in Amman stocks market /Jordan (ASE) using dataset from 2010 until 2018.
ISSN:1913-1844
1913-1852
DOI:10.5539/mas.v12n12p245