Work

Dynamic conditional correlation models for realized covariance matrices

Year: 2012

Type: report

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.

Source: Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B))

Authors: Luc Bauwens, Giuseppe Storti, Francesco Violante

Language: English

Topic: Financial Risk and Volatility Modeling

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: green

Funders: Fédération Wallonie-Bruxelles, Università degli Studi di Sassari, Università degli Studi di Salerno, Académie Universitaire ‘Louvain

Awards: G4945682112, G6116740745

OpenAlex ID: W2154490874

Cites: 32

Cited by: 35

Related to: 10