• DocumentCode
    2994270
  • Title

    Research on daily exchange rate forecasting with multivariate singular spectrum analysis

  • Author

    Zhang Yi ; Hui Xiao-feng

  • Author_Institution
    Sch. of Manage., Harbin Inst. of Technol., Harbin, China
  • fYear
    2012
  • fDate
    20-22 Sept. 2012
  • Firstpage
    1365
  • Lastpage
    1370
  • Abstract
    This article offered an effective method to forecast daily exchange rate. Based on the inspecting and discriminating the nonlinearity structure of the exchange rate system, we use univariate and multivariate singular spectrum analysis for predicting the value and the direction of changes in the daily pound/dollar exchange rate. In prediction of daily pound/dollar rate, we use the rescaled and bootstrapped daily euro/dollar rate as a guidepost for the singular spectrum analysis method. We use the random walk model as a benchmark to evaluate performances of the singular spectrum analysis as a prediction method. Empirical results show that the forecast based on the multivariate singular spectrum analysis compares favorably to the forecast of the random walk model both for predicting the value and the direction of changes in the daily pound/dollar exchange rate.
  • Keywords
    economic forecasting; foreign exchange trading; statistical analysis; bootstrapped daily euro-dollar rate; daily exchange rate forecasting; multivariate singular spectrum analysis; nonlinearity structure; pound-dollar exchange rate; random walk model; univariate singular spectrum analysis; Exchange rates; Forecasting; Market research; Matrix decomposition; Predictive models; Spectral analysis; Time series analysis; forecasting exchange rate; nonlinear system; random walk model; singular spectrum analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management Science and Engineering (ICMSE), 2012 International Conference on
  • Conference_Location
    Dallas, TX
  • ISSN
    2155-1847
  • Print_ISBN
    978-1-4673-3015-2
  • Type

    conf

  • DOI
    10.1109/ICMSE.2012.6414352
  • Filename
    6414352