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 …

(GARCH) models, of differing lag and parameter terms, to forecast the variance of the market used in the denominator of the … squared forecast error (MSE) were used to compare the forecasting ability of the ex-ante GARCH models, Artificial Neural …

error distribution were incorporated in the GARCH (2,1) and EGARCH (2,1) models. Result reveals that day-of-the-week effects …

This paper attempts to fit the best Generalized Autoregressive Conditional Heteroscedastic (GARCH) model for All Share … Index (ASI) of Nigerian Stock Exchange (NSE) returns. A search is made on various GARCH variants specified on the … and non-normality of GARCH innovations, with models and forecasts evaluated using information criteria and loss functions …

This paper examines exchange-rate volatility with GARCH models using monthly exchange-rate return series from 1985:1 to … compare estimates of variants of GARCH models with break in respect of the US dollar rates with exogenously determined break … estimation of volatility models with breaks as against those of GARCH models without volatility breaks and that the introduction …

nonlinear volatility models (symmetric and asymmetric Generalized AutoRegressive Conditional Heteroskedasticity [GARCH …

-day periods are considered. It is studies whether the same GARCH type model can be applied for the whole period, or whether the …

Heteroskedasticity (ARCH) effects existence. For this reason Generalized GARCH models are estimated. Two approaches are followed. The … higher seasonality in volatility rather on average returns. For this reason the Periodic-GARCH (1,1) is estimated. The …

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

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