Evaluating power-law properties from data using a wavelet
transform correlation method with applications to
foreign exchange rates
Wei, H.L. and Billings, S.A.
(2008)
Evaluating power-law properties from data using a wavelet
transform correlation method with applications to
foreign exchange rates.
Research Report.
ACSE Research Report no. 979
.
Automatic Control and Systems Engineering, University of Sheffield
Abstract
Numerous studies in the literature have shown that the dynamics of many time series including observations in foreign exchange markets exhibit scaling behaviours. A novel statistical method, derived from the concept of the continuous wavelet transform correlation function (WTCF),
is proposed for the evaluation of power-law properties from observed data. The new method reveals that foreign exchange rates obey power-laws and thus belong to the class of self-similarity processes.
Metadata
Item Type:
Monograph
Authors/Creators:
Wei, H.L.
Billings, S.A.
Copyright, Publisher and Additional Information:
The Department of Automatic Control and Systems Engineering research reports offer a forum for the research output of the academic staff and research students of the Department at the University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. Some papers in the series may have been subsequently published elsewhere and you are advised to cite the later published version in these instances.
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