Time-localized wavelet multiple regression and correlation
Physica A: Statistical Mechanics and its Applications, 2018, vol. 492, issue C, 1226-1238
This paper extends wavelet methodology to handle comovement dynamics of multivariate time series via moving weighted regression on wavelet coefficients. The concept of wavelet local multiple correlation is used to produce one single set of multiscale correlations along time, in contrast with the large number of wavelet correlation maps that need to be compared when using standard pairwise wavelet correlations with rolling windows. Also, the spectral properties of weight functions are investigated and it is argued that some common time windows, such as the usual rectangular rolling window, are not satisfactory on these grounds.
Keywords: Comovement dynamics; Euro zone; Local regression; Multiscale analysis; Multivariate time series; Non-stationary time series; Stock markets; Wavelet transform; Weighted least squares (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:492:y:2018:i:c:p:1226-1238
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