Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/99972 
Authors: 
Year of Publication: 
2014
Series/Report no.: 
BGPE Discussion Paper No. 144
Publisher: 
Friedrich-Alexander-Universität Erlangen-Nürnberg, Bavarian Graduate Program in Economics (BGPE), Nürnberg
Abstract: 
We propose exible models for multivariate realized volatility dynamics which involve generalizations of the Box-Cox transform to the matrix case. The matrix Box-Cox model of realized covariances (MBC-RCov) is based on transformations of the covariance matrix eigenvalues, while for the Box-Cox dynamic correlation (BC-DC) specification the variances are transformed individually and modeled jointly with the correlations. We estimate transformation parameters by a new multivariate semiparametric estimator and discuss bias-corrected point and density forecasting by simulation. The methods are applied to stock market data where excellent in-sample and out-of-sample performance is found.
Subjects: 
Realized covariance matrix
dynamic correlation
semiparametric estimation
density forecasting
JEL: 
C14
C32
C51
C53
C58
Document Type: 
Working Paper

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