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Detecting Multiple Breaks in Time Series Covariance Structure: a Nonparametric Approach Based on the Evolutionary Spectral Density

Author

Listed:
  • Ibrahim Ahamada

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique, EUREQUA - Equipe Universitaire de Recherche en Economie Quantitative - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Jamel Jouini

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Mohamed Boutahar

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

Abstract

This article estimates the number of breaks and their locations in the covariance structure of a series based on the evolutionary spectral density and uses some standard information criteria. The adopted approach is non-parametric and does hot privilege a priori any modelling of the series. One carries out a Monte Carlo analysis and an empirical illustration using the daily return series of exchange rate euro/US dollar to support the relevance of the theory and to produce additional insights. The simulation results are globally adequate and show that the criteria having heavy penalty are more accurate in the selection of the number of breaks. The empirical results indicate that the covariance structure of the return series considerably varies between 30 March 2000 and 6 April 2001. The unconditional volatility appears non-constant over this interval.

Suggested Citation

  • Ibrahim Ahamada & Jamel Jouini & Mohamed Boutahar, 2004. "Detecting Multiple Breaks in Time Series Covariance Structure: a Nonparametric Approach Based on the Evolutionary Spectral Density," Post-Print halshs-00272867, HAL.
    • Handle: RePEc:hal:journl:halshs-00272867
    DOI: 10.1080/0003684042000246803
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    Cited by:

    1. Russell, Bill, 2011. "Non-stationary inflation and panel estimates of United States short and long-run Phillips curves," Journal of Macroeconomics, Elsevier, vol. 33(3), pages 406-419, September.
    2. Ibrahim Ahamada & Mohamed Boutahar, 2010. "The Power of some Standard tests of stationarity against changes in the unconditional variance," Documents de travail du Centre d'Economie de la Sorbonne 10028, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    3. An, Pengli & Li, Huajiao & Zhou, Jinsheng & Li, Yang & Sun, Bowen & Guo, Sui & Qi, Yajie, 2020. "Volatility spillover of energy stocks in different periods and clusters based on structural break recognition and network method," Energy, Elsevier, vol. 191(C).

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