🤖 AI Summary
This study addresses the lack of suitable portfolio construction methodologies for the Latin American NUAM regional market (Chile, Colombia, Peru) under cross-border and highly volatile emerging-market conditions. Methodologically, it pioneers the application of Hierarchical Risk Parity (HRP) to this market, integrating hierarchical clustering with recursive bisection to circumvent covariance matrix inversion—thereby achieving robust, interpretable, and risk-balanced allocation. Empirical backtesting on daily returns of the 54 constituents of the MSCI NUAM Index demonstrates that HRP significantly reduces maximum drawdown and tracking error relative to equal-weighted and maximum-Sharpe-ratio portfolios, while maintaining competitive absolute returns and improving risk-adjusted performance. This work fills a critical gap in the literature by providing the first empirical validation of HRP in a regional emerging-market context and offers a replicable methodological framework for cross-national asset allocation in such environments.
📝 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.