Arbeitspapier
Forecasting Realized Volatility with Linear and Nonlinear Models
In this paper we consider a nonlinear model based on neural networks as well as linear models to forecast the daily volatility of the S&P 500 and FTSE 100 indexes. As a proxy for daily volatility, we consider a consistent and unbiased estimator of the integrated volatility that is computed from high frequency intra-day returns. We also consider a simple algorithm based on bagging (bootstrap aggregation) in order to specify the models analyzed in this paper.
- Sprache
-
Englisch
- Erschienen in
-
Series: Texto para discussão ; No. 568
- Klassifikation
-
Wirtschaft
- Thema
-
Financial econometrics
volatility forecasting
neural networks
nonlinear models
realized volatility
bagging.
Volatilität
Prognoseverfahren
Nichtlineare Regression
Neuronale Netze
Algorithmus
- Ereignis
-
Geistige Schöpfung
- (wer)
-
McAleer, Michael
Medeiros, Marcelo C.
- Ereignis
-
Veröffentlichung
- (wer)
-
Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio), Departamento de Economia
- (wo)
-
Rio de Janeiro
- (wann)
-
2010
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 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
- McAleer, Michael
- Medeiros, Marcelo C.
- Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio), Departamento de Economia
Entstanden
- 2010
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