Smooth Transition GARCH and the Markov-Switching GARCH models. Simulation experiments reveal that information criteria and …

Estimation of GARCH models can be simplified by augmenting quasi-maximum likelihood (QML) estimation with variance … volatility equation and corresponding value-at-risk predictions. We find that most GARCH coefficients and associated predictions …

. After showing that the expectation of the sum of the estimates of the autoregressive coefficients of a GARCH(1,1) model is …

exhibiting leptokurtosis, asymmetry and conditional heteroskedasticity. It is based on a GARCH-type process driven by noncentral …

follow GARCH and stochastic volatility (SV). Under certain regularity conditions, we give asymptotic results for the … approximate maximum likelihood estimator for the GARMA-GARCH model. We discuss a Monte Carlo likelihood method for the GARMA …

properties of adaptive tail index estimators under the class of student-t marginal distribution functions including GARCH and …

factor models with GARCH dynamics (GARCH(1,1)-M, IGARCH(1,1)-M, Nonlinear Asymmetric GARCH(1,1)-M and Glosten …-Jagannathan-Runkle GARCH(1,1)-M) and three different distributions for the disturbances (Normal, Student's t and Generalized Error Distribution … compared with forecasts based on individual GARCH(1,1)-M models, static factor models, naive, random walk and exponential …