@article{(Open Science Index):https://publications.waset.org/pdf/165,
	  title     = {Statistical Computational of Volatility in Financial Time Series Data},
	  author    = {S. Al Wadi and  Mohd Tahir Ismail and  Samsul Ariffin Abdul Karim},
	  country	= {},
	  institution	= {},
	  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
	    journal   = {International Journal of Mathematical and Computational Sciences},
	  volume    = {4},
	  number    = {2},
	  year      = {2010},
	  pages     = {287 - 291},
	  ee        = {https://publications.waset.org/pdf/165},
	  url   	= {https://publications.waset.org/vol/38},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 38, 2010},