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 Sep 1998
EventNeural Networks for Signal Processing -
Duration: 2 Sep 19982 Sep 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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