- Maximum Likelihood Estimator for a general nonlinear conditional mean model with first-order GARCH errors. …

- Maximum Likelihood Estimator for a general nonlinear conditional mean model with first-order GARCH errors. …

- Maximum Likelihood Estimator for a general nonlinear conditional mean model with first-order GARCH errors. …

- Maximum Likelihood Estimator for a general nonlinear conditional mean model with first-order GARCH errors. …

This study estimates the SETAR and STAR models and examines the regime-switching and asymmetric dynamics of economic … hypothesis of linearity against the alternative hypothesis of threshold nonlinearity for all the sample countries. The STAR model … reinforces the evidence and rejects the null hypothesis of linearity against STAR nonlinearity for all the sample countries …

-Generalized Autoregressive Conditional Heteroskedasticity (STAR-GARCH) can be problematic due to computational difficulties. Conventional … makes Quasi-Maximum Likelihood Estimator (QMLE) difficult to obtain for STAR-GARCH models in practice. Curiously, there has … STAR-GARCH using QMLE. The aim of the paper is to investigate the nature of the numerical difficulties using Monte Carlo …

and GARCH models with general t-distributed innovations. The results hold for joint estimation of (G)ARCH effects and the …

, GARCH dynamics with nonlinearity are added to a nonlinear time series regression model. An adaptive Bayesian Markov chain …

variables with a time varying mean given by a GARCH type equation. After that, in 2000, Engle incorporated duration into a … volatility context (UHF-GARCH). Then, in 2001, Zhang, Russell and Tsay extended the original models (Exponencial and Weibull ACD …