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

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  • Peter Cotton

Abstract

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 collection of more heuristic divide-and-conquer approaches was revitalized by Lopez de Prado where Hierarchical Risk Parity (HRP) was introduced. This paper reveals the hidden connection between these seemingly disparate approaches.

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  • Peter Cotton, 2024. "Schur Complementary Allocation: A Unification of Hierarchical Risk Parity and Minimum Variance Portfolios," Papers 2411.05807, arXiv.org.
    • Handle: RePEc:arx:papers:2411.05807
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    References listed on IDEAS

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    1. Johann Pfitzinger & Nico Katzke, 2019. "A constrained hierarchical risk parity algorithm with cluster-based capital allocation," Working Papers 14/2019, Stellenbosch University, Department of Economics.
    2. Ledoit, Olivier & Wolf, Michael, 2003. "Improved estimation of the covariance matrix of stock returns with an application to portfolio selection," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 603-621, December.
    3. Maxime Markov & Vladimir Markov, 2023. "Portfolio Optimization Rules beyond the Mean-Variance Approach," Papers 2305.08530, arXiv.org, revised Nov 2023.
    4. Merton, Robert C, 1969. "Lifetime Portfolio Selection under Uncertainty: The Continuous-Time Case," The Review of Economics and Statistics, MIT Press, vol. 51(3), pages 247-257, August.
    5. Victor DeMiguel & Lorenzo Garlappi & Francisco J. Nogales & Raman Uppal, 2009. "A Generalized Approach to Portfolio Optimization: Improving Performance by Constraining Portfolio Norms," Management Science, INFORMS, vol. 55(5), pages 798-812, May.
    6. Tomasz Kaczmarek & Katarzyna Perez, 2022. "Building portfolios based on machine learning predictions," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 35(1), pages 19-37, December.
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