• DocumentCode
    3209443
  • Title

    Forecasting volatility data based on Wavelet transforms and ARIMA model

  • Author

    Al Wadi, S. ; Ismail, Mohd Tahir ; Altaher, Alsaidi M. ; Karim, Samsul Ariffin Addul

  • Author_Institution
    School of Mathematical science, Universiti sains Malaysia, 11800 Minden, Penang, Malaysia
  • fYear
    2010
  • fDate
    5-7 Dec. 2010
  • Firstpage
    86
  • Lastpage
    90
  • Abstract
    This article suggests a novel technique for forecasting the volatility data based on Wavelet transforms and ARIMA model. The volatility data are decomposed via Wavelet transforms. Then, the future observations of this series are forecasted using a suitable and best fitted ARIMA model. Daily prices from Amman Stocks Market (Jordan) from 1993 until 2009 are used in this study.
  • Keywords
    Analytical models; Approximation methods; Biological system modeling; Forecasting; Mathematical model; Predictive models; Wavelet analysis; ARIMA model; Wavelet transform; forecasting; volatility data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Science and Social Research (CSSR), 2010 International Conference on
  • Conference_Location
    Kuala Lumpur, Malaysia
  • Print_ISBN
    978-1-4244-8987-9
  • Type

    conf

  • DOI
    10.1109/CSSR.2010.5773909
  • Filename
    5773909
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3209443