Arbeitspapier
Volatility models with innovations from new maximum entropy densities at work
Generalized autoregressive conditional heteroskedasticity (GARCH) processes have become very popular as models for financial return data because they are able to capture volatility clustering as well as leptokurtic unconditional distributions which result from the assumption of conditionally normal error distributions. In contrast, Bollerslev (1987) and several follow-ups provided evidence that starting with leptokurtic and possibly skewed (conditional) error distributions will achieve better results. Parallel to these exible but to some extend arbitrary chosen parametric distributions, recent years saw a rise in suggestions for maximum entropy distributions (e.g. Rockinger and Jondeau, 2002, Park and Bera, 2009 or Fischer and Herrmann, 2010). Within this contribution we provide a comprehensive comparison between both different ME densities and their parametric competitors within different generalized GARCH models such as APARCH and GJR-GARCH.
- Sprache
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Englisch
- Erschienen in
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Series: IWQW Discussion Papers ; No. 03/2010
- Klassifikation
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Wirtschaft
- Thema
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GARCH
APARCH
Entropy density
Skewness
Kurtosis
Börsenkurs
Volatilität
ARCH-Modell
Entropie
Statistische Verteilung
Theorie
- Ereignis
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Geistige Schöpfung
- (wer)
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Fischer, Matthias J.
Gao, Yang
Herrmann, Klaus
- Ereignis
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Veröffentlichung
- (wer)
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Friedrich-Alexander-Universität Erlangen-Nürnberg, Institut für Wirtschaftspolitik und Quantitative Wirtschaftsforschung (IWQW)
- (wo)
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Nürnberg
- (wann)
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2010
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:44 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Fischer, Matthias J.
- Gao, Yang
- Herrmann, Klaus
- Friedrich-Alexander-Universität Erlangen-Nürnberg, Institut für Wirtschaftspolitik und Quantitative Wirtschaftsforschung (IWQW)
Entstanden
- 2010