-of-sample forecasting performance of our outlier-corrected model is then compared to the classical forecasts of a GARCH model in which no … a financial series. It uses an AR(1)–GARCH(1,1) model to calculate interval forecasts for one-step ahead returns that … GARCH model, however, is only used as a filter and the identification algorithm remains robust to model misspecifications …

instrumenting various GARCH models, endogenous break tests, and rolling window estimations, our results overall suggest that the …

instrumenting various GARCH models, endogenous break tests, and rolling window estimations, our results overall suggest that the …

This paper considers GARCH(1,1) models in which the time-varying coefficients are functions of the realizations of an …

relationship exists between the three series. To take into account the influence of temperature on the gas volatility, a GARCH(1 …

literature review of univariate and multivariate GARCH-type models, the author establishes results for the existence and …

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 …

This paper discusses and documents G@RCH 2.0, an Ox package dedicated to the estimation and forecasting of various … univariate ARCH-type models including the GARCH, EGARCH, GJR, APARCH, IGARCH, FIGARCH, FIEGARCH and FIAPARCH specifications of …

Though multivariate GARCH models are widely used in empirical research, their computational aspects still represent a … simultaneous equations model (SEM) with GARCH errors was considered by Engle and Kroner (1995). While there are many applications … GARCH errors to compute the corresponding ML estimators. We compare different gradient algorithms in a simulation framework …