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Characterizing Correlation Matrices that Admit a Clustered Factor Representation

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  • Chen Tong
  • Peter Reinhard Hansen

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.

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  • Chen Tong & Peter Reinhard Hansen, 2023. "Characterizing Correlation Matrices that Admit a Clustered Factor Representation," Papers 2308.05895, arXiv.org.
    • Handle: RePEc:arx:papers:2308.05895
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    References listed on IDEAS

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