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Dynamic conditional correlation models for realized covariance matrices

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Bauwens, Luc [UCL] Storti, Giuseppe [Università di Salerno, Italy] Violante, Francesco [Maastricht University]

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.

Document type Document de travail (Working Paper)
Access type Accès libre
Publication date 2012
Language Anglais
Collection CORE Discussion Paper - 2012/60
Affiliation UCL - SSH/LIDAM/CORE - Center for operations research and econometrics
Keywords realized covariance ; dynamic conditional correlations ; covariance targeting ; Wishart distribution ; composite likelihood
Links
Bibliographic reference Bauwens, Luc ; Storti, Giuseppe ; Violante, Francesco. Dynamic conditional correlation models for realized covariance matrices. CORE Discussion Paper ; 2012/60 (2012)
Permanent URL http://hdl.handle.net/2078.1/122203