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Mixed normal conditional heteroskedasticity
- Both unconditional mixed-normal distributions and GARCH models with fat-tailed conditional distributions have been employed for modeling financial return data. We consider a mixed-normal distribution coupled with a GARCH-type structure which allows for conditional variance in each of the components as well as dynamic feedback between the components. Special cases and relationships with previously proposed specifications are discussed and stationarity conditions are derived. An empirical application to NASDAQ-index data indicates the appropriateness of the model class and illustrates that the approach can generate a plausible disaggregation of the conditional variance process, in which the components' volatility dynamics have a clearly distinct behavior that is, for example, compatible with the well-known leverage effect. Klassifikation: C22, C51, G10
Verfasserangaben: | Markus HaasGND, Stefan MittnikORCiDGND, Marc S. Paolella |
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URN: | urn:nbn:de:hebis:30-10005 |
Titel des übergeordneten Werkes (Deutsch): | Center for Financial Studies (Frankfurt am Main): CFS working paper series ; No. 2002,10 |
Schriftenreihe (Bandnummer): | CFS working paper series (2002, 10) |
Dokumentart: | Arbeitspapier |
Sprache: | Englisch |
Jahr der Fertigstellung: | 2002 |
Jahr der Erstveröffentlichung: | 2002 |
Veröffentlichende Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Datum der Freischaltung: | 13.06.2005 |
Freies Schlagwort / Tag: | Finance; GARCH; Kurtosis; Skewness; Stationarity |
GND-Schlagwort: | USA; ARCH-Prozess; GARCH-Prozess; Volatilität; Stochastischer Prozess; Börsenkurs; Kapitalertrag; Kapitalgewinn; Schätzung |
Ausgabe / Heft: | Version September 2002 |
Seitenzahl: | 35 |
HeBIS-PPN: | 202108821 |
Institute: | Wissenschaftliche Zentren und koordinierte Programme / Center for Financial Studies (CFS) |
DDC-Klassifikation: | 3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft |
Lizenz (Deutsch): | Deutsches Urheberrecht |