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Long-memory dynamics in a SETAR model - Applications to stock markets

Author

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  • Gilles Dufrénot

    (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)

  • Dominique Guegan

    (IDHE - Institutions et Dynamiques Historiques de l'Economie - ENS Cachan - École normale supérieure - Cachan - UP1 - Université Paris 1 Panthéon-Sorbonne - UP8 - Université Paris 8 - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

  • Anne Peguin-Feissolle

    (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 paper presents a 2-regime SETAR model with a long-memory process in the first regime and a short-memory process in the second regime. We briefly introduce the properties of this model and methods for locating the threshold parameter are proposed. Such a process is applied to stock indices and individual asset prices. A comparison with simple FARIMA models is made using some forecastibility criteria.

Suggested Citation

  • Gilles Dufrénot & Dominique Guegan & Anne Peguin-Feissolle, 2005. "Long-memory dynamics in a SETAR model - Applications to stock markets," Post-Print halshs-00179339, HAL.
    • Handle: RePEc:hal:journl:halshs-00179339
    DOI: 10.1016/j.intfin.2004.09.001
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00179339v1
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    Cited by:

    1. Gilles Dufrenot & Dominique Guegan & Anne Peguin-Feissolle, 2008. "Changing-regime volatility: a fractionally integrated SETAR model," Applied Financial Economics, Taylor & Francis Journals, vol. 18(7), pages 519-526.
    2. Boubaker Heni, 2018. "A Generalized ARFIMA Model with Smooth Transition Fractional Integration Parameter," Journal of Time Series Econometrics, De Gruyter, vol. 10(1), pages 1-20, January.
    3. Boubaker Heni & Canarella Giorgio & Gupta Rangan & Miller Stephen M., 2017. "Time-varying persistence of inflation: evidence from a wavelet-based approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-18, September.
    4. Heni Boubaker & Nadia Sghaier, 2014. "Wavelet based Estimation of Time- Varying Long Memory Model with Nonlinear Fractional Integration Parameter," Working Papers 2014-284, Department of Research, Ipag Business School.
    5. Aloy Marcel & Dufrénot Gilles & Tong Charles Lai & Peguin-Feissolle Anne, 2013. "A smooth transition long-memory model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(3), pages 281-296, May.
    6. Million, N., 2008. "Test simultan de la non-stationnarit et de la non-lin arit : une application au taux d.int r t r el am ricain," Working papers 201, Banque de France.
    7. Laurent Ferrara & Dominique Guégan, 2006. "Detection of the Industrial Business Cycle using SETAR Models," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2005(3), pages 353-371.

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