2009
32/2009
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
Author(s): Patrick M Crowley
2009. 37 pages.
Publisher: Bank of Finland
ISBN 978-952-462-552-4 (Printed publication)
ISBN 978-952-462-553-1 (Web publication)
Search words: business cycles, growth cycles, Hilbert-Huang transform (HHT), empirical mode decomposition (EMD), economic time series, non-stationarity, spectral analysis, C49, E0, Patrick M Crowley
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.