Detecting the Fluctuations in Large Samples Using Wavelet Transform


  •  S. AL Wadi    
  •  Ghassan Obeidat    

Abstract

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.



This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1913-1844
  • ISSN(Online): 1913-1852
  • Started: 2007
  • Frequency: monthly

Journal Metrics

(The data was calculated based on Google Scholar Citations)

h-index (January 2018): 30

i10-index (January 2018): 163

h5-index (January 2018): 19

h5-median(January 2018): 25

Contact