Importance of the macroeconomic variables for variance prediction A GARCH-MIDAS approach

Hossein Asgharian, Ai Jun Hou and Farrukh Javed

No 2013/4, Knut Wicksell Working Paper Series from Lund University, Knut Wicksell Centre for Financial Studies

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.

Keywords: Mixed data sampling; long-term variance component; macroeconomic variables; principal component; variance prediction. (search for similar items in EconPapers)
JEL-codes: G17 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2013-02-24
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Citations: View citations in EconPapers (11)

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