Arbeitspapier
Semiparametric estimation of the intensity of long memory in conditional heteroskedasticity
The paper is concerned with the estimation of the long memory parameter in a conditionally heteroskedastic model proposed by Giraitis, Robinson and Surgailis (1999). We consider methods based on the partial sums of the squared observations which are similar in spirit to the classical R/S analysis as well as spectral domain approximate maximum likelihood estimators. The finite sample performance of the estimators is examined by means of a Monte Carlo study.
- Sprache
-
Englisch
- Erschienen in
-
Series: SFB 373 Discussion Paper ; No. 1999,81
- Klassifikation
-
Wirtschaft
- Thema
-
long memory
ARCH models
semiparametric estimation
modified R/S
KPSS and V/S statistics
periodogram
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Giraitis, Liudas
Kokoszka, Piotr
Leipus, Remigijus
Teyssière, Gilles
- Ereignis
-
Veröffentlichung
- (wer)
-
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes
- (wo)
-
Berlin
- (wann)
-
1999
- Handle
- URN
-
urn:nbn:de:kobv:11-10046689
- Letzte Aktualisierung
-
10.03.2025, 11:45 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Giraitis, Liudas
- Kokoszka, Piotr
- Leipus, Remigijus
- Teyssière, Gilles
- Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes
Entstanden
- 1999
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