Abstract

  


 



Model and Distribution Uncertainty in Multivariate GARCH Estimation: A Monte Carlo Analysis


Eduardo Rossi


University of Pavia - Department of Political Economy and Quantitative Methods

Filippo Spazzini


affiliation not provided to SSRN
August 19, 2009

Computational Statistics & Data Analysis, Vol. 54, No. 11, pp. 2786-2800, November 1, 2010

Abstract:     
Multivariate GARCH models are in principle able to accommodate the features of the dynamic conditional covariances; nonetheless the interaction between model parametrization of the second conditional moment and the conditional density of asset returns adopted in the estimation determines the fitting of such models to the observed dynamics of the data. Alternative MGARCH specifications and probability distributions are compared on the basis of forecasting performances by means of Monte Carlo simulations, using both statistical and financial forecasting loss functions.

Accepted Paper Series


Date posted: August 25, 2009 ; Last revised: April 15, 2011

Suggested Citation

Rossi, Eduardo and Spazzini, Filippo, Model and Distribution Uncertainty in Multivariate GARCH Estimation: A Monte Carlo Analysis (August 19, 2009). Computational Statistics & Data Analysis, Vol. 54, No. 11, pp. 2786-2800, November 1, 2010. Available at SSRN: http://ssrn.com/abstract=1457659

Contact Information

Eduardo Rossi (Contact Author)
University of Pavia - Department of Political Economy and Quantitative Methods ( email )
Via San Felice 5
27100 Pavia
Italy
++ (Phone)
Filippo Spazzini
affiliation not provided to SSRN ( email )
Feedback to SSRN (Beta)


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