Author

A. Kuketayev

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Preprint Aug 2026

Connecting Riemannian Geometry and Statistical Inference for Correlation Matrices

The quotient-affine metric gives an intrinsic Riemannian geometry to full-rank correlation matrices, but its geodesic distance has no closed form and we are not aware of an analytic asymptotic null distribution for it. We connect this geometry, introduced in 2019, with Jennrich's 1970 asymptotic test for equality of co...

A. Kuketayev · 0 citations

Preprint Aug 2026

The Sampling Distribution of the Log-Euclidean Distance Between Sample Correlation Matrices

Comparing correlation matrices across time or stress scenarios is critical in quantitative finance and multivariate statistics, yet sample estimation noise often obscures whether an observed distance reflects a true structural shift. We derive the asymptotic sampling distribution of the intrinsic off-log (log-Euclidean...

A. Kuketayev · 0 citations