Multivariate GARCH models
AbstractThis 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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Bibliographic InfoPaper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 669.
Length: 27 pages
Date of creation: 15 Jun 2007
Date of revision: 18 Jan 2008
Publication 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.
Note: This article has been written for Handbook of Financial Time Series, edited by T.G. Andersen, R.A. Davis, J.-P. Kreiss and T. Mikosch
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More information through EDIRC
autoregressive conditional heteroskedasticity; modelling volatility; nonlinear GARCH; nonparametric GARCH; semiparametric GARCH;
Other versions of this item:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-08-18 (All new papers)
- NEP-ECM-2007-08-18 (Econometrics)
- NEP-ETS-2007-08-18 (Econometric Time Series)
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