Properties and estimation of garch(1,1) model

Posedel, Petra (avtor)

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.

• Jezik: Angleški jezik
• Vrsta gradiva: Delo ni kategorizirano
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: FDV - Fakulteta za družbene vede
• Leto izida: 2005
• Št. strani: Str. 243-257
• Številčenje: no. 2
• PID: 20.500.12556/RUL-22455
• UDK: 303
• ISSN pri članku: 1854-0023
• COBISS.SI-ID: 24315997
• Datum objave v RUL: 11.07.2014

Gradivo je del revije

• Naslov: Metodološki zvezki
• Skrajšan naslov: Metodol. zv.
• Založnik: Fakulteta za družbene vede
• ISSN: 1854-0023
• COBISS.SI-ID: 215795712