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Matrix Box-Cox Models for Multivariate Realized Volatility

Roland Weigand

No 478, University of Regensburg Working Papers in Business, Economics and Management Information Systems from University of Regensburg, Department of Economics

Abstract: We propose flexible 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.

Keywords: Realized covariance matrix; dynamic correlation; semiparametric estimation; density forecasting (search for similar items in EconPapers)
JEL-codes: C14 C32 C51 C53 C58 (search for similar items in EconPapers)
Date: 2014-03
New Economics Papers: this item is included in nep-ecm, nep-for and nep-ore
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