Alessi, Lucia, Barigozzi, Matteo and Capasso, Marco (2007) Generalized dynamic factor model + GARCH: exploiting multivariant information for univariate prediction. LEM working paper series, 2006/13. Laboratory of Economics and Management (LEM), Pisa, Italy.
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.
|Item Type:||Monograph (Working Paper)|
|Additional Information:||© 2006 Sant'Anna School of Advanced Studies|
|Uncontrolled Keywords:||dynamic Factors, GARCH, volatility forecasting|
|Library of Congress subject classification:||H Social Sciences > HA Statistics
H Social Sciences > HB Economic Theory
|Journal of Economic Literature Classification System:||C - Mathematical and Quantitative Methods > C3 - Econometric Methods: Multiple; Simultaneous Equation Models; Multiple Variables; Endogenous Regressors > C32 - Time-Series Models
C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation and Selection
C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Other Model Applications
|Sets:||Departments > Statistics
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