Dynamic Conditional Correlation Models for Realized Covariance Matrices


Luc Bauwens
Luc Bauwens
  • Speaker
Louvain School of Management, Catholic University of Louvain

Event Information

Type
Research Seminar
Programme
Finance
Date
Thu. 13 Dec. 2012
Contact
Andreas Pick
Time
16:00-17:00 hours
Location
H10-31


Abstract

New dynamic models for realized covariance matrices are proposed. The expected value of the realized covariance matrix is specified in two steps: a model for each realized variance, and a model for the realized correlation matrix. The realized correlation model is a 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. Moreover, the model is applicable to large matrices since estimation can be done by the composite likelihood method.

Andreas Pick
  • Coordinator
Wing Wah Tham
  • Coordinator