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Nonlinear Dynamics and Wavelets for Business Cycle Analysis

Author

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  • Peter Martey Addo

    (University of Ca’ Foscari [Venice, Italy], CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Monica Billio

    (University of Ca’ Foscari [Venice, Italy])

  • Dominique Guegan

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

We provide a signal modality analysis to characterize and detect nonlinearity schemes in the US Industrial Production Index time series. The analysis is achieved by using the recently proposed "delay vector variance" (DVV) method, which examines local predictability of a signal in the phase space to detect the presence of determinism and nonlinearity in a time series. Optimal embedding parameters used in the DVV analysis are obtained via a differential entropy based method using Fourier and wavelet-based surrogates. A complex Morlet wavelet is employed to detect and characterize the US business cycle. A comprehensive analysis of the feasibility of this approach is provided. Our results coincide with the business cycles peaks and troughs dates published by the National Bureau of Economic Research (NBER).

Suggested Citation

  • Peter Martey Addo & Monica Billio & Dominique Guegan, 2014. "Nonlinear Dynamics and Wavelets for Business Cycle Analysis," PSE-Ecole d'économie de Paris (Postprint) hal-01310513, HAL.
    • Handle: RePEc:hal:pseptp:hal-01310513
    DOI: 10.1007/978-3-319-07061-2_4
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    Cited by:

    1. Marfatia, Hardik A., 2017. "A fresh look at integration of risks in the international stock markets: A wavelet approach," Review of Financial Economics, Elsevier, vol. 34(C), pages 33-49.
    2. Bilgili, Faik & Kassouri, Yacouba & Kuşkaya, Sevda & Majok Garang, Aweng Peter, 2024. "The dynamic nexus of oil price fluctuations and banking sector in China: A continuous wavelet analysis," Resources Policy, Elsevier, vol. 88(C).
    3. María del Carmen Valls Martínez & Pedro Antonio Martín Cervantes, 2021. "Testing the Resilience of CSR Stocks during the COVID-19 Crisis: A Transcontinental Analysis," Mathematics, MDPI, vol. 9(5), pages 1-24, March.
    4. Hardik A. Marfatia, 2017. "A fresh look at integration of risks in the international stock markets: A wavelet approach," Review of Financial Economics, John Wiley & Sons, vol. 34(1), pages 33-49, September.
    5. Vera Ivanyuk, 2021. "Modeling of Crisis Processes in the Financial Market," Economies, MDPI, vol. 9(4), pages 1-17, October.

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    Keywords

    business cycle;

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