Towards a framework for combining stochastic and deterministic descriptions of nonstationary financial time series

Ragnar H. Lesch, David Lowe

    Research output: Chapter in Book/Published conference outputChapter

    Abstract

    We present in this paper ideas to tackle the problem of analysing and forecasting nonstationary time series within the financial domain. Accepting the stochastic nature of the underlying data generator we assume that the evolution of the generator's parameters is restricted on a deterministic manifold. Therefore we propose methods for determining the characteristics of the time-localised distribution. Starting with the assumption of a static normal distribution we refine this hypothesis according to the empirical results obtained with the methods anc conclude with the indication of a dynamic non-Gaussian behaviour with varying dependency for the time series under consideration.
    Original languageEnglish
    Title of host publicationProceedings of the 1998 IEEE Signal Processing Society Workshop Neural Networks for Signal Processing VIII, 1998
    EditorsTony Constantinides, S. Y. Kung, Mahesan Niranjan, Elizabeth Wilson
    Place of PublicationCambridge, UK
    PublisherIEEE
    Pages587-596
    Number of pages10
    Volume8
    ISBN (Print)078035060
    DOIs
    Publication statusPublished - 2 Sept 1998
    EventNeural Networks for Signal Processing -
    Duration: 2 Sept 19982 Sept 1998

    Publication series

    NameProceedings of the 1998 IEEE Signal Processing Society Workshop
    PublisherInstitute of Electrical and Electronics Engineers (IEEE)

    Other

    OtherNeural Networks for Signal Processing
    Period2/09/982/09/98

    Bibliographical note

    ©1998 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

    Keywords

    • forecasting
    • non-stationary
    • time series
    • financial domain
    • stochastic nature
    • data generator
    • deterministic manifold
    • time-localised distribution
    • non-Gaussian behaviour

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