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Characterizing correlation matrices that admit a clustered factor representation

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  • Tong, Chen
  • Hansen, Peter Reinhard

Abstract

The Clustered Factor (CF) model is commonly used to parametrize block correlation matrices. We show that the CF model imposes additional superfluous restrictions. This can be avoided by a different parametrization, based on the logarithmic block correlation matrix.

Suggested Citation

  • Tong, Chen & Hansen, Peter Reinhard, 2023. "Characterizing correlation matrices that admit a clustered factor representation," Economics Letters, Elsevier, vol. 233(C).
    • Handle: RePEc:eee:ecolet:v:233:y:2023:i:c:s0165176523004597
    DOI: 10.1016/j.econlet.2023.111433
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    More about this item

    Keywords

    Block correlation matrix; Copula; Clustering; Factor models;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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    Access and download statistics

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