Title: Robust M-estimation of multivariate GARCH models
Authors: Boudt, Kris ×
Croux, Christophe #
Issue Date: Nov-2010
Publisher: North-Holland Pub. Co.
Series Title: Computational Statistics & Data Analysis vol:54 issue:11 pages:2459-2469
Abstract: The Gaussian quasi-maximum likelihood estimator of Multivariate GARCH models is shown to be very sensitive to outliers in the data. A class of robust M-estimators for MGARCH models is developed. To increase the robustness of the estimators, the use of volatility models with the property of bounded innovation propagation is recommended. The Monte Carlo study and an empirical application to stock returns document the good robustness properties of the M-estimator with a fat-tailed Student t loss function.
ISSN: 0167-9473
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Research Center Finance, Leuven
Research Center for Operations Research and Business Statistics (ORSTAT), Leuven
Faculty of Economics and Business (FEB) - miscellaneous
Department of Financial Management, Campus Carolus Antwerp
× corresponding author
# (joint) last author

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