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
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, Eworking papers series
Date posted: November 28, 2009
© 2013 Social Science Electronic Publishing, Inc. All Rights Reserved.
This page was processed by apollo4 in 0.313 seconds