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Asymptotic Theory Of General Multivariate Garch Models, Weibin Jiang

Electronic Thesis and Dissertation Repository

Generalized autoregressive conditional heteroscedasticity (GARCH) models are widely used in financial markets. Parameters of GARCH models are usually estimated by the quasi-maximum likelihood estimator (QMLE). In recent years, economic theory often implies equilibrium between the levels of time series, which makes the application of multivariate models a necessity. Unfortunately the asymptotic theory of the multivariate GARCH models is far from coherent since many algorithms on the univariate case do not extend to multivariate models naturally. This thesis studies the asymptotic theory of the QMLE under mild conditions. We give some counterexamples for the parameter identifiability result in Jeantheau [1998] and …