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Correlation matrices with average constraints

Jan Tuitman, Steven Vanduffel and Jing Yao

Statistics & Probability Letters, 2020, vol. 165, issue C

Abstract: We develop an algorithm that makes it possible to generate all correlation matrices satisfying a constraint on their average value. We extend the results to the case of multiple constraints. These results can be used to assess the extent to which methodologies driven by correlation matrices are robust to misspecification thereof.

Keywords: Correlation matrix; Random correlation matrices; Average correlation; Simulation (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1016/j.spl.2020.108868

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