This study explores the benefits of incorporating fat-tailed innovations, asymmetric volatility response, and an … extended information set into crude oil return modeling and forecasting. To this end, we utilize standard volatility models … such as Generalized Autoregressive Conditional Heteroskedastic (GARCH), Generalized Autoregressive Score (GAS), and …

This paper investigates the forecasting performance of three popular variants of the non-linear GARCH models, namely VS-GARCH …, GJR-GARCH and Q-GARCH, with the symmetric GARCH(1,1) model as a benchmark. The application involves ten European stock … price indexes. Forecasts produced by each non-linear GARCH model and each index are evaluated using a common set of …

, the study strikes a note of caution on account of the volatility in petroleum prices. If the recent decline in global …

cointegration techniques in modelling the conditional mean, as well as multivariate GARCH models for the conditional variances. We … specifiy the conditional variances of VECM residuals with the Constant Conditional Correlation (CCC) multivariate GARCH model … of Bollerslev (1990) and the Dynamic Conditional Correlation (DCC) multivariate GARCH model of Engle (2002). The within …

-form GARCH-in-mean model assigned to six globally leading financial markets. The obtained results support Keynes's theory - the …