20.500.12556/RUL-22455 Properties and estimation of garch(1,1) model We study in depth the properties of the GARCH(1,1) model and the assumptions on the parameter space under which the process is stationary. In particular, we prove ergodicity and strong stationarity for the conditional variance (squared volatility) of the process. We show under which conditions higher order moments of the GARCH(1,1) process exist and conclude that GARCH processes are heavy-tailed. We investigate the sampling behavior of the quasi-maximum likelihood estimator of the Gaussian GARCH(1,1) model. A boundedconditional fourth moment of the rescaled variable (the ratio of the disturbance to the conditional standard deviation) is sufficient for the result. Consistent estimation and asymptotic normality are demonstrated, as well as consistent estimation of the asymptotic covariance matrix. true false false Angleški jezik Neznan jezik Delo ni kategorizirano 2014-07-11 14:26:40 2014-07-11 14:26:40 2022-06-02 03:50:31 0000-00-00 00:00:00 2005 0 0 Str. 243-257 no. 2 2005 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 303 1854-0023 24315997 http://mrvar.fdv.uni-lj.si/pub/mz/mz2.1/posedel.pdf 1 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=22455 Fakulteta za družbene vede Metodološki zvezki 0 0 0