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  • 标题:Detecting the Fluctuations in Large Samples Using Wavelet Transform
  • 本地全文:下载
  • 作者:S. AL Wadi ; Ghassan Obeidat
  • 期刊名称:Modern Applied Science
  • 印刷版ISSN:1913-1844
  • 电子版ISSN:1913-1852
  • 出版年度:2018
  • 卷号:12
  • 期号:12
  • 页码:245-248
  • DOI:10.5539/mas.v12n12p245
  • 语种:English
  • 出版社:Canadian Center of Science and Education
  • 摘要: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.
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