Please use this identifier to cite or link to this item:
Title: Evidence for deterministic nonlinear dynamics in financial time series data
Authors: Small, M
Tse, CK 
Keywords: Economic cybernetics
Nonlinear dynamical systems
Stock markets
Time series
Issue Date: 2003
Publisher: IEEE
Source: 2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003 : proceedings : 20-23 March 2003, p. 339-346 How to cite?
Abstract: Intra-day measurements of three time series (DJIA, gold fixings and USD-JPY exchange rates) are examined for evidence of deterministic nonlinear dynamics. Standard linear surrogate techniques and estimation of dynamic invariants demonstrate that linear noise models are insufficient to explain dynamic variability in intra-day returns. Therefore, the data may not be modeled as a monotonic nonlinear transformation of linearly filtered noise. Furthermore, a new nonlinear surrogate technique is employed to demonstrate that conditional heteroskedastic models are also insufficient to model this data. We conclude that the most likely model of the data is a nonlinear dynamical system driven by high dimensional dynamics (noise).
ISBN: 0-7803-7654-4
DOI: 10.1109/CIFER.2003.1196280
Appears in Collections:Conference Paper

View full-text via PolyU eLinks SFX Query
Show full item record


Last Week
Last month
Citations as of Aug 17, 2018

Page view(s)

Last Week
Last month
Citations as of Aug 13, 2018

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.