Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/22039
Authors: 
Herwartz, Helmut
Golosnoy, Vasyl
Year of Publication: 
2007
Series/Report no.: 
Economics working paper / Christian-Albrechts-Universität Kiel, Department of Economics 2007,23
Abstract: 
We consider the problem of ex-ante forecasting conditional correlation patterns using ultra high frequency data. Flexible semiparametric predictors referring to the class of dynamic panel and dynamic factor models are adopted for daily forecasts. The parsimonious set up of our approach allows to forecast correlations exploiting both estimated realized correlation matrices and exogenous factors. The Fisher-z transformation guarantees robustness of correlation estimators under elliptically constrained departures from normality. For the purpose of performance comparison we contrast our methodology with prominent parametric and nonparametric alternatives to correlation modeling. Based on economic performance criteria, we distinguish dynamic factor models as having the highest predictive content.
Subjects: 
Correlation forecasting
Epps effect
Fourier method
Dynamic panel model
Dynamic factor model
JEL: 
C13
C14
C53
G12
Document Type: 
Working Paper

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