Characterizing Correlation Matrices that Admit a Clustered Factor Representation
Econometrics
2023-08-14 v1 Methodology
Abstract
The Clustered Factor (CF) model induces a block structure on the correlation matrix and is commonly used to parameterize correlation matrices. Our results reveal that the CF model imposes superfluous restrictions on the correlation matrix. This can be avoided by a different parametrization, involving the logarithmic transformation of the block correlation matrix.
Cite
@article{arxiv.2308.05895,
title = {Characterizing Correlation Matrices that Admit a Clustered Factor Representation},
author = {Chen Tong and Peter Reinhard Hansen},
journal= {arXiv preprint arXiv:2308.05895},
year = {2023}
}