Wavelet analysis of stock returns and aggregate economic activity
AbstractThe 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.
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Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 52 (2008)
Issue (Month): 6 (February)
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