Amirkabir University of Technology AUT Journal of Mathematics and Computing 2783-2449 6 1 2025 01 01 A distributionally robust approach for the risk-parity portfolio selection problem 9 17 5269 10.22060/ajmc.2023.22260.1145 EN Maryam Bayat Department of Mathematics and Computer Science, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran Farnaz Hooshmand Department of Mathematics and Computer Science, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran 0000-0002-2449-3925 Seyed Ali MirHassani Department of Mathematics and Computer Science, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran 0000-0002-9894-7053 Journal Article 2023 03 09 Risk-parity is one of the most recent and interesting strategies in the portfolio selection area. Considering the mean-standard-deviation risk measure, this paper studies the risk-parity problem under the uncertainty of the covariance<br />matrix. Assuming that the uncertainty is represented by a finite set of scenarios, the problem is formulated as a scenario-based stochastic programming model. Then, since the occurrence probabilities of scenarios are not known with certainty, two ambiguity sets of distributions are considered, and corresponding to each one, a distributionally robust optimization model is presented. Computational experiments on real-world instances taken from the literature confirm the importance of the proposed models in terms of stability, volatility and Sharpe-ratio. https://ajmc.aut.ac.ir/article_5269_1dc3a89d0d440ba31729b0ba74b93a33.pdf