2006/13 | LEM Working Paper Series | |
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Generalized Dynamic Factor Model + GARCH Exploiting Multivariate Information for Univariate Prediction | ||
Lucia Alessi, Matteo Barigozzi, Marco Capasso |
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Keywords | ||
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Dynamic Factors, GARCH, Volatility Forecasting.
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JEL Classifications | ||
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C32, C52, C53.
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Abstract | ||
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We propose a new model for multivariate forecasting which combines the Generalized
Dynamic Factor Model (GDFM)and the GARCH model. The GDFM, applied to a huge
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 samples up to 475 series, predicting both levels and volatility of returns.
While results on levels are not significantly different, on volatility the GDFM+GARCH
model outperforms the standard GARCH in most cases. These results are robust with
respect to different volatility proxies.
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Downloads | ||
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