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

40 Pages Posted: 28 Nov 2009

See all articles by Patrick M. Crowley

Patrick M. Crowley

Texas A&M University - Corpus Christi; Bank of Finland/Suomen Pankki

Date Written: November 25, 2009

Abstract

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.

Keywords: business cycles, growth cycles, Hilbert-Huang transform (HHT), empirical mode decomposition (EMD), economic time series, non-stationarity, spectral analysis

JEL Classification: C49, E

Suggested Citation

Crowley, Patrick M., 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 (November 25, 2009). Bank of Finland Research Discussion Paper No. 32/2009. Available at SSRN: https://ssrn.com/abstract=1513265 or http://dx.doi.org/10.2139/ssrn.1513265

Patrick M. Crowley (Contact Author)

Texas A&M University - Corpus Christi ( email )

6300 Ocean Drive, Unit #5808
Corpus Christi, TX 78412
United States

HOME PAGE: http://patrickmcrowley.com

Bank of Finland/Suomen Pankki ( email )

P.O. Box 160
FIN-00101 Helsinki
Finland

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