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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

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  • Crowley, Patrick M.

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.

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  • Crowley, Patrick M., 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," Bank of Finland Research Discussion Papers 32/2009, Bank of Finland.
    • Handle: RePEc:zbw:bofrdp:rdp2009_032
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    References listed on IDEAS

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    1. Benati, Luca, 2009. "Long run evidence on money growth and inflation," Working Paper Series 1027, European Central Bank.
    2. Daniel Levy & Hashem Dezhbakhsh, 2003. "On the typical spectral shape of an economic variable," Applied Economics Letters, Taylor & Francis Journals, vol. 10(7), pages 417-423.
    3. Levy, Daniel & Dezhbakhsh, Hashem, 2003. "International Evidence on Output Fluctuation and Shock Persistence," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 50(7), pages 1499-1530.
    4. Patrick M. Crowley, 2007. "A Guide To Wavelets For Economists," Journal of Economic Surveys, Wiley Blackwell, vol. 21(2), pages 207-267, April.
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