Abstract
In this paper a pattern recognition procedure for time series using wavelets is developed. This is done by means of a randomization test based on the ratio of the sum of squared wavelet coefficients of pairs of time series at different scales. A simulation study using pairs of stationary and non-stationary time series and using the Haar and Daubechies wavelets reveals that the test performs fairly well at scales where there are a sufficient number of wavelet coefficients. The test is applied to a set of financial time series.
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© 2002 Springer-Verlag Berlin Heidelberg
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Maharaj, E.A. (2002). Pattern Recognition of Time Series using Wavelets. In: Härdle, W., Rönz, B. (eds) Compstat. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-57489-4_76
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DOI: https://doi.org/10.1007/978-3-642-57489-4_76
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1517-7
Online ISBN: 978-3-642-57489-4
eBook Packages: Springer Book Archive