Wavelets in Time Series Analysis
AbstractThis article reviews the role of wavelets in statistical time series analysis. We survey work that emphasises scale such as estimation of variance and the scale exponent of a process with a specific scale behaviour such as 1/f processes. We present some of our own work on locally stationary wavelet (LSW) processes which model both stationary and some kinds of non-stationary processes. Analysis of time series assuming the LSW model permits identification of an evolutionary wavelet spectrum (EWS) that quantifies the variation in a time series over a particualr state and at a particular time. We address estimation of the EWS and show how our methodology reveals phenomena of interest in an infant electrocardiogram series.
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Bibliographic InfoPaper provided by Catholique de Louvain - Institut de statistique in its series Papers with number 9901.
Length: 16 pages
Date of creation: 1999
Date of revision:
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Postal: Universite Catholique de Louvain, Institut de Statistique, Voie du Roman Pays, 34 B-1348 Louvain- La-Neuve, Belgique.
TIME SERIES ; STATISTICAL ANALYSIS ; ESTIMATION OF PARAMETERS;
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- C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
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- Debashis Mondal & Donald Percival, 2010. "Wavelet variance analysis for gappy time series," Annals of the Institute of Statistical Mathematics, Springer, vol. 62(5), pages 943-966, October.
- Jammazi, Rania & Aloui, Chaker, 2010. "Wavelet decomposition and regime shifts: Assessing the effects of crude oil shocks on stock market returns," Energy Policy, Elsevier, vol. 38(3), pages 1415-1435, March.
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"Modeling long-term memory effect in stock prices: A comparative analysis with GPH test and Daubechies wavelets,"
Studies in Economics and Finance,
Emerald Group Publishing, vol. 25(1), pages 38-48, March.
- Ozun, Alper & Cifter, Atilla, 2007. "Modeling Long-Term Memory Effect in Stock Prices: A Comparative Analysis with GPH Test and Daubechies Wavelets," MPRA Paper 2481, University Library of Munich, Germany.
- Amato, U. & Antoniadis, A. & De Feis, I., 2006. "Dimension reduction in functional regression with applications," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2422-2446, May.
- Christoph Schleicher, 2002. "An Introduction to Wavelets for Economists," Working Papers 02-3, Bank of Canada.
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