Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/176051 
Erscheinungsjahr: 
2010
Schriftenreihe/Nr.: 
Texto para discussão No. 568
Verlag: 
Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio), Departamento de Economia, Rio de Janeiro
Zusammenfassung: 
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.
Schlagwörter: 
Financial econometrics
volatility forecasting
neural networks
nonlinear models
realized volatility
bagging.
Dokumentart: 
Working Paper

Datei(en):
Datei
Größe
200 kB





Publikationen in EconStor sind urheberrechtlich geschützt.