We study the strong consistency and asymptotic normality of the maximum likelihood estimator for a class of time series … processes. We formulate primitive conditions for global identification, invertibility, strong consistency, asymptotic normality …

robust filtering and forecasting. We provide sufficient conditions for the strong consistency and asymptotic normality of the …

as a general nonlinear first order generalized autoregressive conditional heteroskedasticity (GARCH(1,1)) model. Strong … consistency and asymptotic normality of the global Gaussian quasi maximum likelihood (QML) estimator are established under … the first results on consistency and asymptotic normality of the QML estimator in nonlinear autoregressive models with …

GARCH (1,1) models are widely used for modelling processes with time varying volatility. These include financial time …) for the GARCH (1,1) model. The asymptotic properties of the LSE are studied under very mild moment conditions for the … errors. We establish the consistency, asymptotic normality at the standard convergence rate of square root-of-n for our …

We study the strong consistency and asymptotic normality of the maximum likelihood estimator for a class of time series … processes. We formulate primitive conditions for global identification, invertibility, strong consistency, asymptotic normality …

A least squares estimation approach for the estimation of a GARCH (1,1) modelis developed. The asymptotic properties of … t of some order. We establish the consistency, asymptotic normality and the law of iterated logarithm for our estimate …

serial correlation in the form of AR(1) for the idiosyncratic or time-specific error component. The consistency and …