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The exact dimensional threshold for Spearman rank-correlation compatibility
Abstract
We show that, for a given dimension, the set of Spearman's rank correlation matrices and that of linear correlation matrices coincide if and only if the dimension is no larger than nine. For this, we construct an extreme rank-four counterexample in dimension ten and prove its incompatibility using moment identities and Cauchy-Schwarz. Appending unit directions produces counterexamples in every higher dimension. This, together with existing results, completes the dimensional classification and settles a long-standing open question in quantitative risk management.
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BibTeX
@misc{wang2026exact,
title = {{The exact dimensional threshold for Spearman rank-correlation compatibility}},
author = {Ruodu Wang and Zhenyuan Zhang},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.16278},
eprint = {2609.16278},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.16278},
}
RIS
TY - UNPB
TI - The exact dimensional threshold for Spearman rank-correlation compatibility
AU - Ruodu Wang
AU - Zhenyuan Zhang
PY - 2026
DA - 2026/09/01
PB - arXiv
DO - 10.48550/arxiv.2609.16278
UR - https://arxiv.org/abs/2609.16278
AB - We show that, for a given dimension, the set of Spearman's rank correlation matrices and that of linear correlation matrices coincide if and only if the dimension is no larger than nine. For this, we construct an extreme rank-four counterexample in dimension ten and prove its incompatibility using moment identities and Cauchy-Schwarz. Appending unit directions produces counterexamples in every higher dimension. This, together with existing results, completes the dimensional classification and settles a long-standing open question in quantitative risk management.
ER -