Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/89540 
Erscheinungsjahr: 
2007
Schriftenreihe/Nr.: 
LEM Working Paper Series No. 2006/13
Verlag: 
Scuola Superiore Sant'Anna, Laboratory of Economics and Management (LEM), Pisa
Zusammenfassung: 
We propose a new model for volatility forecasting which combines the Generalized Dynamic Factor Model (GDFM) and the GARCH model. The GDFM, applied to a large number of series, captures the multivariate information and disentangles the common and the idiosyncratic part of each series of returns. In this financial analysis, both these components are modeled as a GARCH.We compare GDFM+GARCH and standard GARCH performance on two samples up to 171 series, providing one-step-ahead volatility predictions of returns. The GDFM+GARCH model outperforms the standard GARCH in most cases. These results are robust with respect to different volatility proxies.
Schlagwörter: 
Dynamic Factors
GARCH
volatility forecasting
JEL: 
C32
C52
C53
Dokumentart: 
Working Paper

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