Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/89540
Authors: 
Alessi, Lucia
Barigozzi, Matteo
Capasso, Marco
Year of Publication: 
2007
Series/Report no.: 
LEM Working Paper Series 2006/13
Abstract: 
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.
Subjects: 
Dynamic Factors
GARCH
volatility forecasting
JEL: 
C32
C52
C53
Document Type: 
Working Paper

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