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- W1832839239 abstract "This paper applies the GARCH-MIDAS (Mixed Data Sampling) model to examine whether information contained in macroeconomic variables can help to predict short-term and long-term components of the return variance. A principal component analysis is used to incorporate the information contained in different variables. Our results show that including low-frequency macroeconomic information in the GARCH-MIDAS model improves the prediction ability of the model, particularly for the long-term variance component. Moreover, the GARCH-MIDAS model augmented with the first principal component outperforms all other specifications, indicating that the constructed principal component can be considered as a good proxy of the business cycle." @default.
- W1832839239 created "2016-06-24" @default.
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- W1832839239 date "2013-02-24" @default.
- W1832839239 modified "2023-09-27" @default.
- W1832839239 title "Importance of the macroeconomic variables for variance prediction A GARCH-MIDAS approach" @default.
- W1832839239 hasPublicationYear "2013" @default.
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