Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/85216 
Autor:innen: 
Erscheinungsjahr: 
2002
Schriftenreihe/Nr.: 
CoFE Discussion Paper No. 02/12
Verlag: 
University of Konstanz, Center of Finance and Econometrics (CoFE), Konstanz
Zusammenfassung: 
This paper proposes a semiparametric approach by introducing a smooth scale function into the standard GARCH model so that conditional heteroskedasticity and scale change in a financial time series can be modelled simultaneously. An estimation procedure combining kernel estimation of the scale function and maximum likelihood estimation of the GARCH parameters is proposed. Asymptotic proper- ties of the kernel estimator are investigated in detail. An iterative plug-in algorithm is developed for selecting the bandwidth. Practical performance of the proposal is illustrated by simulation. The proposal is applied to the daily S&P 500 and DAX 100 returns. It is shown that there are simultaneously significant conditional heteroskedasticity and scale change in these series.
Schlagwörter: 
Semiparametric GARCH
conditional heteroskedasticity
scale change
nonparametric regression with dependence
bandwidth selection
JEL: 
C22
C14
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

Datei(en):
Datei
Größe
502.43 kB





Publikationen in EconStor sind urheberrechtlich geschützt.