• DocumentCode
    3164529
  • Title

    Prediction of foreign exchange rate by local fuzzy reconstruction method

  • Author

    Iokibe, Tadashi ; Murata, Shoji ; Koyama, Masaya

  • Author_Institution
    Syst. Dev. Sect., Meidensha Corp., Tokyo, Japan
  • Volume
    5
  • fYear
    1995
  • fDate
    22-25 Oct 1995
  • Firstpage
    4051
  • Abstract
    Several systems for the purpose of predicting trends in the foreign exchange market and stocks have been developed. They are either knowledge based expert systems or fuzzy expert systems. The disadvantage of these systems is that it mainly depends on knowledge base. It is not easy to obtain the know-how of dealers completely. This paper presents the method of predicting time series data, which is considered as a deterministic chaos, based on the deterministic dynamical system. The key technology is embedding and local reconstruction. At first, we explain about deterministic chaos. Next, we show the Takens´ embedding theorem briefly, and discuss the local reconstruction especially the local fuzzy reconstruction method in detail. Finally. we apply the local fuzzy reconstruction method to the prediction of foreign exchange rate, and the results obtained are included
  • Keywords
    chaos; foreign exchange trading; fuzzy logic; fuzzy set theory; investment; prediction theory; time series; Takens´ embedding theorem; deterministic chaos; deterministic dynamical system; foreign exchange rate prediction; local fuzzy reconstruction; stock market; time series; Chaos; Delay effects; Difference equations; Differential equations; Exchange rates; Expert systems; Fuzzy systems; Hybrid intelligent systems; Reconstruction algorithms; State-space methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 1995. Intelligent Systems for the 21st Century., IEEE International Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-2559-1
  • Type

    conf

  • DOI
    10.1109/ICSMC.1995.538424
  • Filename
    538424