Is the hierarchical risk parity (HRP) portfolio the optimal choice for passive investors? A comparative analysis of 60/40, HRP, and allweather portfolio

Abstract

In a world shaped by economic instability, geopolitical conflicts, and volatile interest rates, many investors are gravitating towards more passive investment strategies in search of stability. This thesis explores a compelling question: Can innovative portfolio methods such as the Hierarchical Risk Parity (HRP) beat conventional models in this time of unpredictability while providing a secure refuge for passive investors? Through a detailed analysis of three distinct portfolios, covering the period from January 1, 2014, to January 1, 2024 — a decade marked by both economic crisis and recoveries — this research investigates whether the HRP model, with its automated, riskparity-driven structure, provides a superior solution compared to more conventional approaches like the All-Weather portfolio and the 60/40 one. Advanced libraries such as arch, pandas, numpy, scikit-learn and Yfinance were used along with Python to achieve a meticulous and meticulous numerical analysis. Key performance metrics including returns and maximum drawdown were used to evaluate the portfolios at first. Further, more complex statistical analyses were performed, including VaR and CVaR testing, stress testing, quantile regression, the Fama-French five-factor model, CAPM, and ARCH-GARCH models. The findings revealed that the HRP portfolio not only exceeded expectations but also demonstrated superior resilience and risk management, outperforming the other two portfolios across various market conditions. These results lead to a fascinating insight: Innovating portfolio strategies with an emphasis on risk parity might present a new path for passive investors seeking better outcomes