Artikel
A note on the asymptotic normality of the kernel deconvolution density estimator with logarithmic chi-square noise
This paper studies the asymptotic normality for the kernel deconvolution estimator when the noise distribution is logarithmic chi-square; both identical and independently distributed observations and strong mixing observations are considered. The dependent case of the result is applied to obtain the pointwise asymptotic distribution of the deconvolution volatility density estimator in discrete-time stochastic volatility models.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 3 ; Year: 2015 ; Issue: 3 ; Pages: 561-576 ; Basel: MDPI
- Klassifikation
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Wirtschaft
Estimation: General
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Specific Distributions; Specific Statistics
Financial Econometrics
- Thema
-
kernel deconvolution estimator
asymptotic normality
volatility density estimation
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Zu, Yang
- Ereignis
-
Veröffentlichung
- (wer)
-
MDPI
- (wo)
-
Basel
- (wann)
-
2015
- DOI
-
doi:10.3390/econometrics3030561
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 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
- Artikel
Beteiligte
- Zu, Yang
- MDPI
Entstanden
- 2015
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