of ARCH effect has been tried to predict with conditional variance models such as ARCH (1), ARCH (2), ARCH (3), GARCH (1 …,1), GARCH (1,2), GARCH (1,3), GARCH (2,1), GARCH (2,2), EGARCH (1,1) and EGARCH (1,2). While the obtained findings indicate that … the best model is in the direction of GARCH (1,1) according to Akaike info criterion, it was found that GARCH (1,1) model …

Both unconditional mixed-normal distributions and GARCH models with fat-tailed conditional distributions have been … employed for modeling financial return data. We consider a mixed-normal distribution coupled with a GARCH-type structure which …

This paper proposes efficient estimators of risk measures in a semiparametric GARCH model defined through moment …

(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 …

validate this result. The last twenty eight days out-of-sample forecast adjudged Power-GARCH (1, 1, 1) in student's t error …

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

Volatility (SV) and Generalised Autoregressive Conditional Heteroskedasticity (GARCH) models which are both extended to include … outperforms the GARCH model. …