Journal article | Zeitschriftenartikel
Local Likelihood Estimators in a Regression Model for Stock Returns
We consider a non-stationary regression type model for stock returns in which the innovations are described by four-parameter distributions and the parameters are assumed to be smooth, deterministic functions of time. Incorporating also normal distributions for modelling the innovations, our model is capable of adapting to light-tailed innovations as well as to heavy-tailed ones. Thus, it turns out to be a very flexible approach. Both, for the fitting of the model and for forecasting the distributions of future returns, we use local likelihood methods for estimation of the parameters. We apply our model to the S&P 500 return series, observed over a period of twelve years. We show that it fits these data quite well and that it yields reasonable one-day-ahead forecasts.
- Umfang
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Seite(n): 619-635
- Sprache
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Englisch
- Anmerkungen
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Status: Postprint; begutachtet (peer reviewed)
- Erschienen in
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Quantitative Finance, 8(6)
- Thema
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Wirtschaft
Wirtschaftsstatistik, Ökonometrie, Wirtschaftsinformatik
Allgemeines, spezielle Theorien und Schulen, Methoden, Entwicklung und Geschichte der Wirtschaftswissenschaften
Theorieanwendung
- Ereignis
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Geistige Schöpfung
- (wer)
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Jönck, Uwe Christian
- Ereignis
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Veröffentlichung
- (wo)
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Vereinigtes Königreich
- (wann)
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2008
- DOI
- URN
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urn:nbn:de:0168-ssoar-221111
- Rechteinformation
-
GESIS - Leibniz-Institut für Sozialwissenschaften. Bibliothek Köln
- Letzte Aktualisierung
-
21.06.2024, 16:26 MESZ
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GESIS - Leibniz-Institut für Sozialwissenschaften. Bibliothek Köln. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Zeitschriftenartikel
Beteiligte
- Jönck, Uwe Christian
Entstanden
- 2008
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