Notice of RetractionDetecting the regime shift via wavelet transform

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

Recently, regime shifts or structure breaks had acquired very high attention in analyzing financial time series data. Abrupt of changes in the government policy, financial crises and many of challenges lead to change in the behavior of the financial time series data. In addition, wavelet transform also becomes very famous in the financial sector and it has better advantages than the other filtering methods such as the traditional technique Fourier transform. Therefore, to prove the high ability for the wavelet transform, Haar wavelet transform (HWT) and fast Fourier transform are used to capture the possibility of regime shifts or structure breaks. Apart from detecting precisely the change, this paper also discuss advantages and disadvantages for each method using Amman stocks market (Jordan) between 1992 and 2008. Some numerical and statistical results will be presented in this paper.