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Wake me up before you GO-GARCH

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  • Roy van der Weide

Abstract

"The `holy grail' in multivariate GARCH modelling is without any doubt a parameterization of the covariance matrix that is feasible in terms of estimation at a minimum loss of generality" (van der Weide, 2002). Recent models that aspire such favourable position in this trade-off are the DCC model by Engle (2002) and the GO-GARCH model by van der Weide (2002). These models have gained generality on the earliest models designed to be feasible, CCC and O-GARCH, without losing too much of their practical attractiveness. Generality may be measured by the ability to model the key stylized facts of multivariate data:(i) Persistence in volatility and covariation; (ii) Time-varying correlation; and (iii) Spill-over effects in volatility. The DCC model incorporates the first two items, but trades the third for particular ease of estimation. On the other hand, GO-GARCH which is nested in the general BEKK model meets all three key aspects of empirical data, while it may seem to give in a little on DCC in terms of practicability. This paper proposes an alternative method of estimating GO-GARCH that will substantially increase feasibility while preserving generality. In effect, the approach does not become more complicated than estimating a Vector Autoregressive Model along the way. As the procedure may easily be implemented in any popular software package, such as EViews, it should meet the convenience of DCC

Suggested Citation

  • Roy van der Weide, 2004. "Wake me up before you GO-GARCH," Computing in Economics and Finance 2004 316, Society for Computational Economics.
  • Handle: RePEc:sce:scecf4:316
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    References listed on IDEAS

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    1. I. D. Vrontos & P. Dellaportas & D. N. Politis, 2003. "A full-factor multivariate GARCH model," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 312-334, December.
    2. Roy van der Weide, 2002. "GO-GARCH: a multivariate generalized orthogonal GARCH model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 549-564.
    3. Lanne, Markku & Saikkonen, Pentti, 2007. "A Multivariate Generalized Orthogonal Factor GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 61-75, January.
    4. Luc Bauwens & Sébastien Laurent, 2002. "A New Class of Multivariate skew Densities, with Application to GARCH Models," Computing in Economics and Finance 2002 5, Society for Computational Economics.
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    Citations

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    Cited by:

    1. Xin Zhang & Drew Creal & Siem Jan Koopman & Andre Lucas, 2011. "Modeling Dynamic Volatilities and Correlations under Skewness and Fat Tails," Tinbergen Institute Discussion Papers 11-078/2/DSF22, Tinbergen Institute.
    2. Peter Boswijk, H. & van der Weide, Roy, 2011. "Method of moments estimation of GO-GARCH models," Journal of Econometrics, Elsevier, vol. 163(1), pages 118-126, July.
    3. Zolotko, Mikhail & Okhrin, Ostap, 2014. "Modelling the general dependence between commodity forward curves," Energy Economics, Elsevier, vol. 43(C), pages 284-296.
    4. Hafner, Christian M. & Linton, Oliver, 2010. "Efficient estimation of a multivariate multiplicative volatility model," Journal of Econometrics, Elsevier, vol. 159(1), pages 55-73, November.
    5. Płuciennik Piotr, 2012. "Influence of the American Financial Market on Other Markets During the Subprime Crisis," Folia Oeconomica Stetinensia, De Gruyter Open, vol. 12(2), pages 19-30, December.
    6. Chakraborty, Sandip & Kakani, Ram Kumar, 2016. "Institutional investment, equity volume and volatility spillover: Causalities and asymmetries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 1-20.
    7. Basher, Syed Abul & Sadorsky, Perry, 2016. "Hedging emerging market stock prices with oil, gold, VIX, and bonds: A comparison between DCC, ADCC and GO-GARCH," Energy Economics, Elsevier, vol. 54(C), pages 235-247.
    8. Alexios Ghalanos & Eduardo Rossi & Giovanni Urga, 2015. "Independent Factor Autoregressive Conditional Density Model," Econometric Reviews, Taylor & Francis Journals, vol. 34(5), pages 594-616, May.

    More about this item

    Keywords

    multivariate GARCH; BEKK; DCC; GO-GARCH; Three Step Estimation;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • 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
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

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