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
AbstractThe 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.
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Bibliographic InfoPaper provided by Bank of Finland in its series Research Discussion Papers with number 32/2009.
Length: 37 pages
Date of creation: 21 Nov 2009
Date of revision:
business cycles; growth cycles; Hilbert-Huang transform (HHT); empirical mode decomposition (EMD); economic time series; non-stationarity; spectral analysis;
Find related papers by JEL classification:
- C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
- E00 - Macroeconomics and Monetary Economics - - General - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-12-11 (All new papers)
- NEP-ECM-2009-12-11 (Econometrics)
- NEP-ETS-2009-12-11 (Econometric Time Series)
- NEP-ORE-2009-12-11 (Operations Research)
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