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

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

Posted: 25 Aug 2009 Last revised: 15 Apr 2011

See all articles by Eduardo Rossi

Eduardo Rossi

Department of Economics and Management

Filippo Spazzini

affiliation not provided to SSRN

Date Written: August 19, 2009

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.

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: https://ssrn.com/abstract=1457659

Eduardo Rossi (Contact Author)

Department of Economics and Management ( email )

Via San Felice 5
27100 Pavia
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Filippo Spazzini

affiliation not provided to SSRN ( email )

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