Hierarchical Risk Parity as an Alternative to Conventional Methods of Portfolio Optimization: (A Study of Tehran Stock Exchange)

Abstract

One of the most critical investment issues faced by different investors is choosing an optimal investment portfolio and balancing risk and return in a way that, maximizes investment returns and minimize the investment risk. So far, many methods have been introduced to form a portfolio, the most famous of the Markowitz approach. The Markowitz mean-variance approach is widely known in the world of finance and, it marks the foundation of every portfolio theory. The mean-variance theory has many practical drawbacks due to the difficulty in estimating the expected return and covariance for different asset classes. In this study, we use the Hierarchical Risk Parity (HRP) machine learning technique and compare the results with the three methods of Minimum Variance (MVP), Uniform Distribution (UNIF), and Risk Parity (RP). To conduct this research, the adjusted price of 50 listed companies of the Tehran Stock Exchange for 2018-07-01 to 2020-09-29 has been used. 70% of the data are considered as in-sample and the remaining 30% as out-of-sample. We evaluate the results using four criteria: Sharp, Maximum Drawdown, Calmer, Sortino. The results show that the MVP and, UNIF approach within the insample and, the UNIF and HRP approach out-of-sample have the best performance in sharp measure.

Formation of an Optimal Portfolio of Lq45 Shares Using Markowitz Method

“…The expected return results were greater than the random stock selection method which, if an equal weighting was used, namely 0.25 for the four selected stocks, was 0.00133. According to research of Nourahmadi & Sadeqi (2023), the results of grouping shares using the clustering method and portfolio formation were better than the random share management method.…”

Using hierarchical risk parity in the Brazilian market: An out-of-sample analysis

“…HRP portfolios bring a new, innovative way to deal with portfolio allocation. This procedure has been applied in different markets with encouraging results (Burggraf, 2021;Nourahmadi and Sadeqi, 2022;Sen et al, 2021;Sen and Dutta, 2022) but its effectiveness in the Brazilian market has not been well established yet. In order to investigate its effectiveness, this study performs an out-of-sample comparison of HRP portfolio against other wellknown portfolio allocation techniques using data from the Brazilian stock market.…”