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Inference and testing on the boundary in extended constant conditional correlation GARCH models

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  • Rasmus Søndergaard Pedersen

    (Department of Economics, University of Copenhagen)

Abstract

We consider inference and testing in extended constant conditional correlation GARCH models in the case where the true parameter vector is a boundary point of the parameter space. This is of particular importance when testing for volatility spillovers in the model. The large-sample properties of the QMLE are derived together with the limiting distributions of the related LR, Wald, and LM statistics. Due to the boundary problem, these large-sample properties become nonstandard. The size and power properties of the tests are investigated in a simulation study. As an empirical illustration we test for (no) volatility spillovers between foreign exchange rates.

Suggested Citation

  • Rasmus Søndergaard Pedersen, 2015. "Inference and testing on the boundary in extended constant conditional correlation GARCH models," Discussion Papers 15-10, University of Copenhagen. Department of Economics.
  • Handle: RePEc:kud:kuiedp:1510
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Francq, Christian & Sucarrat, Genaro, 2017. "An equation-by-equation estimator of a multivariate log-GARCH-X model of financial returns," Journal of Multivariate Analysis, Elsevier, vol. 153(C), pages 16-32.
    2. repec:eee:intfor:v:34:y:2018:i:1:p:45-63 is not listed on IDEAS
    3. Rasmus Søndergaard Pedersen & Anders Rahbek, 2017. "Testing Garch-X Type Models," Discussion Papers 17-15, University of Copenhagen. Department of Economics.
    4. Annastiina Silvennoinen & Timo Teräsvirta, 3108. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," CREATES Research Papers 2017-28, Department of Economics and Business Economics, Aarhus University.
    5. repec:eee:econom:v:204:y:2018:i:2:p:223-247 is not listed on IDEAS
    6. Darolles, Serges & Francq, Christian & Laurent, Sébastien, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," MPRA Paper 83988, University Library of Munich, Germany.
    7. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    8. Francq, Christian & Sucarrat, Genaro, 2015. "Equation-by-Equation Estimation of a Multivariate Log-GARCH-X Model of Financial Returns," MPRA Paper 67140, University Library of Munich, Germany.

    More about this item

    Keywords

    ECCC-GARCH; QML; boundary; spillovers;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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