suggest a superiority of the one-step method when the innovations are heavy-tailed. For standard GARCH models, the comparison …

Conditional quantile estimation is an essential ingredient in modern risk management. Although GARCH processes have … distributions. In this paper, we study estimation of conditional quantiles for GARCH models using quantile regression. Quantile … regression estimation of GARCH models is highly nonlinear; we propose a simple and effective two-step approach of quantile …

enables to examine simultaneous dependencies between them. Proposed models are compared with benchmark GARCH and range …-based GARCH (RGARCH) models in terms of prediction accuracy. All models are estimated with maximum likelihood method, using time …

quarterly basis - for commonly used GARCH models in a large-scale study, using more than twelve years (2000-2012) of daily … following conclusions. First, updating the parameter estimates of the GARCH equation on a daily frequency improves only … overlap, reflecting that the performance is not significantly different. Second, the asymmetric GARCH model with non …

-maximum likelihood (QML) estimation of GARCH models. It relies on a reparameterization of the model and a first-step estimation of the … distribution of the estimators obtained by this method in univariate GARCH models. Comparisons with the standard QML are provided …