Hierarchical Risk Parity for Portfolio Allocation in the Latin American NUAM Market

This study applies the Hierarchical Risk Parity (HRP) portfolio allocation methodology to the NUAM market, a regional holding that integrates the markets of Chile, Colombia and Peru. As one of the first empirical analyses of HRP in this newly formed Latin American context, the paper addresses a gap in the literature on portfolio construction under cross-border, emerging market conditions. HRP leverages hierarchical clustering and recursive bisection to allocate risk in a manner that is both interpretable and robust--avoiding the need to invert the covariance matrix, a common limitation in the traditional mean-variance optimization. Using daily data from 54 constituent stocks of the MSCI NUAM Index from 2019 to 2025, we compare the performance of HRP against two standard benchmarks: an equally weighted portfolio (1/N) and a maximum Sharpe ratio portfolio. Results show that while the Max Sharpe portfolio yields the highest return, the HRP portfolio delivers a smoother risk-return profile, with lower drawdowns and tracking error. These findings highlight HRP's potential as a practical and resilient asset allocation framework for investors operating in the integrated, high-volatility markets like NUAM.

Publication Details

Journal
ArXiv.org
Published
2025-09-03
Primary Topic
Geochemistry and Geologic Mapping
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article
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article

Hierarchical Risk Parity for Portfolio Allocation in the Latin American NUAM Market

ArXiv.org
Geochemistry and Geologic Mapping
article

Hierarchical Risk Parity for Portfolio Allocation in the Latin American NUAM Market

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Abstract

This study applies the Hierarchical Risk Parity (HRP) portfolio allocation methodology to the NUAM market, a regional holding that integrates the markets of Chile, Colombia and Peru. As one of the first empirical analyses of HRP in this newly formed Latin American context, the paper addresses a gap in the literature on portfolio construction under cross-border, emerging market conditions. HRP leverages hierarchical clustering and recursive bisection to allocate risk in a manner that is both interpretable and robust--avoiding the need to invert the covariance matrix, a common limitation in the traditional mean-variance optimization. Using daily data from 54 constituent stocks of the MSCI NUAM Index from 2019 to 2025, we compare the performance of HRP against two standard benchmarks: an equally weighted portfolio (1/N) and a maximum Sharpe ratio portfolio. Results show that while the Max Sharpe portfolio yields the highest return, the HRP portfolio delivers a smoother risk-return profile, with lower drawdowns and tracking error. These findings highlight HRP's potential as a practical and resilient asset allocation framework for investors operating in the integrated, high-volatility markets like NUAM.

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Geochemistry and Geologic Mapping
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Hierarchical Risk Parity for Portfolio Allocation in the Latin American NUAM Market · ArXiv.org (2025) | TGRS Research Map | TGRS