Dynamic conditional correlation models for realized covariance matrices

Luc Bauwens, Giuseppe Storti and Francesco Violante ()

No 2012060, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

Abstract: New dynamic models for realized covariance matrices are proposed. The expected value of the realized covariance matrix is specified in two steps: one for each realized variance, and one for the realized correlation matrix. The realized correlation model is a scalar dynamic conditional correlation model. Estimation can be done in two steps as well, and a QML interpretation is given to each step, by assuming a Wishart conditional distribution. The model is applicable to large matrices since estimation can be done by the composite likelihood method.

Keywords: realized covariance; dynamic conditional correlations; covariance targeting; Wishart distribution; composite likelihood (search for similar items in EconPapers)
JEL-codes: C13 C32 C58 (search for similar items in EconPapers)
Date: 2012-12-31
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Citations: View citations in EconPapers (26)

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Persistent link: https://EconPapers.repec.org/RePEc:cor:louvco:2012060

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