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Multimodality in the GARCH Regression Model

Author

Listed:
  • Jurgen A. Doornik

    (Nuffield College, University of Oxford)

  • Marius Ooms

    (Dept of Econometrics, Free University Amsterdam)

Abstract

Several aspects of GARCH(p,q) models that are relevant for empirical applications are investigated. In particular, it is noted that the inclusion of dummy variables as regressors can lead to multimodality in the GARCH likelihood. This invalidates standard inference on the estimated coefficients. Next, the implementation of different restrictions on the GARCH parameter space is considered. A refinement to the Nelson and Cao (1992) conditions for a GARCH(2,q) model is presented, and it is shown how these can then be implemented by parameter transformations. It is argued that these conditions may also be too restrictive, and a simpler alternative is introduced which is formulated in terms of the unconditional variance. Finally, examples show that multimodality is a real concern for models of the £/$ exchange rate, especially when p>2.

Suggested Citation

  • Jurgen A. Doornik & Marius Ooms, 2003. "Multimodality in the GARCH Regression Model," Economics Papers 2003-W20, Economics Group, Nuffield College, University of Oxford.
    • Handle: RePEc:nuf:econwp:0320
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    File URL: http://www.nuff.ox.ac.uk/economics/papers/2003/W20/GarchMode1.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Dummy variable; EGARCH; GARCH; Multimodality.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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