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Multivariate GARCH models: software choice and estimation issues
Author(s) -
Brooks Chris,
Burke Simon P.,
Persand Gita
Publication year - 2003
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.717
Subject(s) - multivariate statistics , econometrics , estimation , autoregressive conditional heteroskedasticity , computer science , software , statistics , multivariate analysis , economics , mathematics , volatility (finance) , management , programming language
A large number of important practical tasks can be accomplished using a multivariate GARCH model. This paper examines the relatively small number of software packages that are currently available for estimating such models, in spite of their widespread use. The review focuses upon estimation issues and differences in available options for controlling the optimisation, and the review then considers an application to the estimation of optimal hedge ratios. Large differences in estimated parameters and standard errors are observed, but these are found to generate only modest differences in optimal hedge ratios and virtually indiscernible differences in model performance measures.