A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ten lectures on wavelets
An introduction to wavelets
Testing for multivariate autoregressive conditional heteroskedasticity using wavelets
Computational Statistics & Data Analysis
Introduction to the special issue on statistical signal extraction and filtering
Computational Statistics & Data Analysis
Multivariate denoising using wavelets and principal component analysis
Computational Statistics & Data Analysis
Wavelet analysis of long-range-dependent traffic
IEEE Transactions on Information Theory
Editorial: Special Issue on Statistical and Computational Methods in Finance
Computational Statistics & Data Analysis
Expert Systems with Applications: An International Journal
Study on the WCC method for time series data analysis
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 3
Expert Systems with Applications: An International Journal
The Price and Trading Volume Dynamics Relationship in the EEX Power Market: A Wavelet Modeling
Computational Economics
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The relationship between stock market returns and economic activity is investigated using signal decomposition techniques based on wavelet analysis. After the application of the maximum overlap discrete wavelet transform (MODWT) to the DJIA stock price index and the industrial production index for the US over the period 1961:1-2006:10 wavelet variance and cross-correlations analyses are used to investigate the scaling properties of the series and the lead/lag relationship between them at different time scales. The results show that stock market returns tend to lead the level of economic activity, but only at the highest scales (lowest frequencies) corresponding to periods of 16 months and longer, and that the leading period increases as the wavelet time scale increases.