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 …

, such as GARCH models, are investigated, to determine if they are more appropriate for predicting future return volatility …

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 …

over a small time frame (e.g., a crisis period). We apply our method to test GARCH model specifications for a large panel …

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

heteroscedasticity (GARCH)-type models to forecast oil price volatility over the time periods from January 02, 1875 to December 31, 1895 … outperformed by other models, with long memory GARCH-type models coming out second best. …

In this paper we show the validity of the adaptive LASSO procedure in estimating stationary ARDL(p,q) models with GARCH …

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 …