Efficient local techniques in financial time series forecasting

D. A. Karras, B. G. Mertzios, Rallis Papademetriou

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

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    Several improvements for the local reconstruction method in time series prediction are developed and presented in this paper. More specifically, it is suggested that by augmenting the state vectors with informative features coming from second order
    information involving the topology of their neighbouring state vectors then, significantly better results could be obtained with respect to time series reconstruction. Also, the weighting methodology in the least square fitting procedure has been modified aiming at eliminating outliers. The validity of these new ideas is investigated by applying them to the reconstruction task of a time series representing stock price evolution.
    Original languageEnglish
    Title of host publicationProceedings of 16th IMACS World Congress
    Subtitle of host publicationscientific computation, applied mathematics and simulation
    EditorsM. Deville, R. Owens
    Place of PublicationNew Brunswick, New Jersey
    PublisherInternational Association for Mathematics and Computers in Simulation
    Number of pages5
    ISBN (Electronic)3952207519
    ISBN (Print)9783952207512
    Publication statusPublished - 18 Aug 2000
    Event16th IMACS World Congress - École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
    Duration: 21 Aug 200025 Aug 2000


    Conference16th IMACS World Congress


    • Time series prediction
    • Financial forecasting


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