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A Multivariate Generalized Orthogonal Factor GARCH Model

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  • Lanne, Markku
  • Saikkonen, Pentti

Abstract

The paper studies a factor GARCH model and develops test procedures which can be used to test the number of factors needed to model the conditional heteroskedasticity in the considered time series vector. Assuming normally distributed errors the parameters of the model can be straightforwardly estimated by the method of maximum likelihood. Inefficient but computationally simple preliminary estimates are first obtained and used as initial values to maximize the likelihood function. Maximum likelihood estimation with nonnormal errors is also straightforward. Motivated by the empirical application of the paper a mixture of normal distributions is considered. An interesting feature of the implied factor GARCH model is that some parameters of the conditional covariance matrix which are not identifiable in the case of normal errors become identifiable when the mixture distribution is used. As an empirical example we consider a system of four exchange rate return series.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 23714.

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Date of creation: May 2005
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Handle: RePEc:pra:mprapa:23714

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Keywords: Multivariate GARCH model; mixture of normal distributions; exchange rate;

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References

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  1. Mencía, Javier & Sentana, Enrique, 2005. "Estimation and Testing of Dynamic Models with Generalized Hyperbolic Innovations," CEPR Discussion Papers 5177, C.E.P.R. Discussion Papers.
  2. 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.
  3. Philip Hans Franses & Dick van Dijk & Andre Lucas, 2004. "Short patches of outliers, ARCH and volatility modelling," Applied Financial Economics, Taylor & Francis Journals, vol. 14(4), pages 221-231.
  4. BAUWENS, Luc & LAURENT, Sébastien & ROMBOUTS, Jeroen VK, . "Multivariate GARCH models: a survey," CORE Discussion Papers RP -1847, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  5. Robert F. Engle & Victor Ng & Michael Rothschild, 1988. "Asset Pricing with a Factor Arch Covariance Structure: Empirical Estimates for Treasury Bills," NBER Technical Working Papers 0065, National Bureau of Economic Research, Inc.
  6. Comte, F. & Lieberman, O., 2003. "Asymptotic theory for multivariate GARCH processes," Journal of Multivariate Analysis, Elsevier, vol. 84(1), pages 61-84, January.
  7. Hafner, C.M. & Herwartz, H., 2003. "Analytical quasi maximum likelihood inference in multivariate volatility models," Econometric Institute Research Papers EI 2003-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  8. Klaassen, F.J.G.M., 1999. "Have Exchange Rates Become More Closely Tied? Evidence from a New Multivariate GARCH Model," Discussion Paper 1999-10, Tilburg University, Center for Economic Research.
  9. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(01), pages 122-150, February.
  10. Donald W.K. Andrews, 1985. "Asymptotic Results for Generalized Wald Tests," Cowles Foundation Discussion Papers 761R, Cowles Foundation for Research in Economics, Yale University, revised Apr 1986.
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