ORIGINAL RESEARCH article

Front. Appl. Math. Stat.

Sec. Mathematical Finance

Volume 11 - 2025 | doi: 10.3389/fams.2025.1585187

This article is part of the Research TopicFinancial Modeling with FrictionsView all 7 articles

On Transaction Costs in Minimum-Risk Portfolios: Insights into Risk Parity and Asset Allocation

Provisionally accepted
  • 1Metropolitan University of Tirana, Tirana, Albania
  • 2Department of Methods and Models for Economics, Territory and Finance, Faculty of Economics, Sapienza University of Rome, Rome, Lazio, Italy

The final, formatted version of the article will be published soon.

In minimal risk portfolios, costs associated with transactions are essential in calculating the net performance. The transaction costs of maintaining such portfolios are predominantly negative due to the fact that traditional portfolio optimization strategies, which focus solely on risk and return, neglecting transaction costs typically incurred through rebalancing. This research analyzes the impact of costs associated with transactions while constructing minimum risk portfolios centered around risk parity models and provides a way to control those costs. We investigate the performance of portfolios under fixed and flexible costs and include these parameters in the optimization model to achieve more realistic results. Applying real-world data on conventional stock portfolios and highly volatile cryptocurrency markets, we demonstrate the performance of mean-variance optimization (M-V), risk parity with standard deviation (RP-Std), and risk parity with Conditional Value at Risk (RP-CVaR) through empirical data for both stock portfolios and cryptocurrencies. We found that potential transaction costs can cause portfolio returns to change by anywhere between 0.5% to 2% per year depending on how often one trades, and market conditions. By highlighting how crucial it is to incorporate transaction costs into the decision-making process, this study contributes to the expanding literature of research on portfolio optimization. For investors looking to create and manage their portfolios in a way that balances risk, return, and cost effectiveness, our findings offer useful insights. Future studies might investigate adaptive models that dynamically adapt to shifting cost structures and market situations, or they could generalize these findings to other asset classes.

Keywords: portfolio optimization1, transaction cost2, cryptocurrency3, risk parity4, asset allocation5

Received: 28 Feb 2025; Accepted: 23 Apr 2025.

Copyright: © 2025 Veliu, Shkurti and Martire. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Denis Veliu, Metropolitan University of Tirana, Tirana, Albania

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