@article{scholars1302,
           pages = {778--782},
            year = {2010},
         journal = {World Academy of Science, Engineering and Technology},
           title = {Statistical computational of volatility in financial time series data},
          volume = {62},
            note = {cited By 1},
        keywords = {Economic sectors; Filtering method; Financial crisis; Financial time series; Haar wavelet transform; MATLAB program; Statistical properties; Stocks market; Traditional techniques; Volatility; Volatil, Commerce; Financial data processing; Signal receivers; Time series; Wavelet transforms; Fast Fourier transforms; MATLAB, Fast Fourier transforms; Financial data processing},
          author = {Al Wadi, S. and Ismail, M. T. and Karim, S. A. A.},
            issn = {2010376X},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-78651561326&partnerID=40&md5=440c13e7d5c9dacd2d3eb94ab64fdd2c},
        abstract = {It is well known that during the developments in the economic sector and through the financial crises occur everywhere in the whole world, volatility measurement is the most important concept in financial time series. Therefore in this paper we discuss the volatility for Amman stocks market (Jordan) for certain period of time. Since wavelet transform is one of the most famous filtering methods and grows up very quickly in the last decade, we compare this method with the traditional technique, Fast Fourier transform to decide the best method for analyzing the volatility. The comparison will be done on some of the statistical properties by using Matlab program.}
}