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Nonlinear Shift Contagion Modeling: Further Evidence from High Frequency Stock Data

Author

Listed:
  • M.H. Arouri
  • F. Jawadi

    (EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique, CERAG - Centre d'études et de recherches appliquées à la gestion - CNRS - Centre National de la Recherche Scientifique - UPMF - Université Pierre Mendès France - Grenoble 2 - UGA - Université Grenoble Alpes)

  • Waël Louhichi

    (CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR1 - Université de Rennes 1 - UNIV-RENNES - Université de Rennes - CNRS - Centre National de la Recherche Scientifique)

  • D. K. Nguyen

Abstract

This paper investigates the contagion hypothesis for the French and German stock markets using a combination of a Switching Transition Error Correction model and a Generalized Autoregressive Conditional Heteroscedasticity (STEC-GARCH) model. The main advantage of this double nonlinear error-correction modeling is to specify a time-varying process that apprehends the dynamic evolution of the contagion and reproduces its speed, its extreme regimes as well as its intermediate states, by taking into account the possible linkages between these markets. More importantly, these techniques capture two kinds of nonlinearity: nonlinearity in the mean and nonlinearity in the variance. Applying this modeling on the intraday data of the CAC40 and DAX100 indices over the pre-crisis period (2004-2006) and the post-crisis period (2007-2009), our results indicate significant shift contagion between studied markets. There is also evidence of nonlinear time-varying error correcting-mechanism toward the long-run equilibrium.

Suggested Citation

  • M.H. Arouri & F. Jawadi & Waël Louhichi & D. K. Nguyen, 2011. "Nonlinear Shift Contagion Modeling: Further Evidence from High Frequency Stock Data," Post-Print halshs-00601428, HAL.
  • Handle: RePEc:hal:journl:halshs-00601428
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00601428
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