heteroskedastic environment. This is done by a simulation procedure where asset returns are generated from a GARCH (1,1)-t model. In … shown that the variance of the returns on the hedged position is considerably higher in a GARCH (1,1) environment than in a …

testing parameter constancy. Furthermore, various existing ways of testing the EGARCH model against GARCH one are investigated …

This paper is concerned with efficient GMM estimation and inference in GARCH models. Sufficient conditions for the … estimator to be consistent and asymptotically normal are established for the GARCH(1,1) conditional variance process. In … addition efficiency results are obtained in the general framework of the GARCH(1,1)-M regression model. …

mentioned, and various extensions of the standard GARCH model are highlighted. This includes the Exponential GARCH model …

We consider a family of GARCH(1,1) processes introduced in He and Teräsvirta (1999a). This family contains various … popular GARCH models as special cases. A necessary and sufficient condition for the existence of a strictly stationary …

. Its performance is compared with that of standard models of conditional heteroskedasticity such as GARCH. This has …

We consider a family of GARCH(1,1) processes introduced in He and Teräsvirta (1999a). This family contains various … popular GARCH models as special cases. A necessary and sufficient condition for the existence of a strictly stationary …

This paper is concerned with efficient GMM estimation and inference in GARCH models. Sufficient conditions for the … estimator to be consistent and asymptotically normal are established for the GARCH(1,1) conditional variance process. In … addition efficiency results are obtained in the general framework of the GARCH(1,1)-M regression model. …

Conditional Heteroskedasticity (GARCH), the Exponential GARCH and the Autoregressive Stochastic Volatility model. The focus is on …