most citedSchur Complementary Allocation: A Unification of Hierarchical Risk Parity and Minimum Variance Portfolios

1 citations · 1 across the 5 of their papers we have counts for

collaborators

6 papers

q-fin.MF2026

Nested Clustered Optimization Is One End of a Schur Bridge, and the Interior Is Sometimes Provably Better

Peter Cotton

Nested clustered optimization allocates within each cluster from the cluster's own covariance block and then across the resulting cluster portfolios. Block inversion says the uncon…

stat.ME2026

Scalable Inversion of Contests with Correlated Performances, Including Softmax and Multinomial Probit

Peter Cotton

Multinomial probit choice probabilities over n alternatives are Gaussian orthant integrals, computed by simulation for thirty years, one expensive integral per alternative. Inversi…

q-fin.ST2026

Marginally Useful: An Information-Gap Identity in Conformal Prediction

Peter Cotton

Conformal prediction has been touted as a more formal, rigorous approach to adding uncertainty to a forecast. The sole objective of this note is to point out that rigor cuts both w…

q-fin.TR2026

On a Simple Relationship Between Order Imbalance, Skew and Width in Over-The-Counter Trading

Peter Cotton

We consider a market maker who can only obtain and dispose of inventory by responding to a sequence of sealed-bid enquiries, and whose customers arrive with imbalanced intent: sell…

q-fin.RM2026

Two Sides of Schur Damping: High-Dimensional Pseudo-Likelihoods and Portfolio Allocation

Peter Cotton

Two communities that rarely cite each other -- spatial statisticians fitting high-dimensional weather fields, and quantitative investors building portfolios -- have independently a…

q-fin.PM2024★ 1 cited

Schur Complementary Allocation: A Unification of Hierarchical Risk Parity and Minimum Variance Portfolios

Peter Cotton

Despite many attempts to make optimization-based portfolio construction in the spirit of Markowitz robust and approachable, it is far from universally adopted. Meanwhile, the colle…