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Multivariate GARCH models Author info | Abstract | Publisher info | Download info | Related research | Statistics Silvennoinen, Annastiina () (School of Finance and Economics, University of Technology, Sydney)
Teräsvirta, Timo () (CREATES, University of Aarhus and Department of Economic Statistics, Stockholm School of Economics)
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This article contains a review of multivariate GARCH models. Most common GARCH models are presented and their properties considered. This also includes semiparametric and nonparametric GARCH models. Existing specification and misspecification tests are discussed. Finally, there is an empirical example in which several multivariate GARCH models are fitted to the same data set and the results compared with each other.
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Paper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number
669.
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Length: 27 pages
Date of creation: 15 Jun 2007Date of revision:
18 Jan 2008Publication status: Published in Handbook of Financial Time Series, Andersen, Torben G., Davis, Richard A., Kreiss, Jens-Peter, Mikosch, Thomas (eds.), 2009, pages 201-229, Springer.Handle: RePEc:hhs:hastef:0669Note: This article has been written for Handbook of Financial Time Series, edited by T.G. Andersen, R.A. Davis, J.-P. Kreiss and T. MikoschContact details of provider: Postal: The Economic Research Institute, Stockholm School of Economics, P.O. Box 6501, 113 83 Stockholm, Sweden Phone: +46-(0)8-736 90 00 Fax: +46-(0)8-31 01 57 Email: Web page: http://www.hhs.se/ More information through EDIRC
For technical questions regarding this item, or to correct its listing, contact: (Helena Lundin).
Keywords: autoregressive conditional heteroskedasticity ; modelling volatility ; nonlinear GARCH ; nonparametric GARCH ; semiparametric GARCH ; Other versions of this item:
Find related papers by JEL classification: C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
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