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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


Patrick M. Crowley


Texas A&M University - Department of Finance, Economics, & Decision Sciences; Bank of Finland - Research

November 25, 2009

Bank of Finland Research Discussion Paper No. 32/2009

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.

Number of Pages in PDF File: 40

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

JEL Classification: C49, E

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Date posted: November 28, 2009  

Suggested Citation

Crowley, Patrick M. 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: http://ssrn.com/abstract=1513265 or http://dx.doi.org/10.2139/ssrn.1513265

Contact Information

Patrick M. Crowley (Contact Author)
Texas A&M University (TAMU) - Department of Finance, Economics, & Decision Sciences ( email )
Corpus Christi, TX 78412
United States
Bank of Finland - Research ( email )
P.O. Box 160
FIN-00101 Helsinki
Finland
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