How do you make a time series sing like a choir? Using the Hilbert-Huang transform to extract embedded frequencies from economic or financial time series
The Hilbert-Huang transform (HHT) was developed late last century but has still to be introduced to the vast majority of economists. The HHT transform is a way of extracting the frequency mode features of cycles embedded in any time series using an adaptive data method that can be applied without making any assumptions about stationarity or linear data-generating properties. This paper introduces economists to the two constituent parts of the HHT transform, namely empirical mode decomposition (EMD) and Hilbert spectral analysis. Illustrative applications using HHT are also made to two financial and three economic time series.
|Date of creation:||21 Nov 2009|
|Date of revision:|
|Contact details of provider:|| Postal: Bank of Finland, P.O. Box 160, FI-00101 Helsinki, Finland|
Web page: http://www.suomenpankki.fi/en/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:hhs:bofrdp:2009_032. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Minna Nyman)
If references are entirely missing, you can add them using this form.