Matrix Box-Cox Models for Multivariate Realized Volatility
No 478, University of Regensburg Working Papers in Business, Economics and Management Information Systems from University of Regensburg, Department of Economics
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)
New Economics Papers: this item is included in nep-ecm, nep-for and nep-ore
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Working Paper: Matrix Box-Cox Models for Multivariate Realized Volatility (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:bay:rdwiwi:29687
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