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.
- Language
-
Englisch
- Bibliographic citation
-
Series: Texto para discussão ; No. 568
- Classification
-
Wirtschaft
- Subject
-
Financial econometrics
volatility forecasting
neural networks
nonlinear models
realized volatility
bagging.
Volatilität
Prognoseverfahren
Nichtlineare Regression
Neuronale Netze
Algorithmus
- Event
-
Geistige Schöpfung
- (who)
-
McAleer, Michael
Medeiros, Marcelo C.
- Event
-
Veröffentlichung
- (who)
-
Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio), Departamento de Economia
- (where)
-
Rio de Janeiro
- (when)
-
2010
- Handle
- Last update
-
10.03.2025, 11:42 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- McAleer, Michael
- Medeiros, Marcelo C.
- Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio), Departamento de Economia
Time of origin
- 2010
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