Chapter 17: Portfolio Construction

Hierarchical Risk Parity: Clustering, Quasi-Diagonalization, and Recursive Bisection advanced

HRP replaces covariance-matrix inversion with a tree-based allocation that is more stable out of sample, at the cost of a long-only constraint and sensitivity to clustering choices.

HRP replaces covariance-matrix inversion with a tree-based allocation that is more stable out of sample, at the cost of a long-only constraint and sensitivity to clustering choices.

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References

Building Diversified Portfolios that Outperform Out-of-Sample
Marcos Lopez de Prado (2016)
Overcoming Markowitz's Instability with the Help of the Hierarchical Risk Parity (HRP): Theoretical Evidence
Alexandre Antonov, Alex Lipton, Marcos Lopez de Prado (2024)