Wake me up before you GO-GARCH
"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
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|Date of creation:||11 Aug 2004|
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- BAUWENS, Luc & LAURENT, Sébastien, 2002.
"A new class of multivariate skew densities, with application to GARCH models,"
CORE Discussion Papers
2002020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- 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.
- 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.
- 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.
- 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.
- Lanne, Markku & Saikkonen, Pentti, 2005. "A Multivariate Generalized Orthogonal Factor GARCH Model," MPRA Paper 23714, University Library of Munich, Germany.
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