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A distributionally robust approach for the risk-parity portfolio selection problem | ||
| AUT Journal of Mathematics and Computing | ||
| مقاله 2، دوره 6، شماره 1، فروردین 2025، صفحه 9-17 اصل مقاله (586.32 K) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22060/ajmc.2023.22260.1145 | ||
| نویسندگان | ||
| Maryam Bayat؛ Farnaz Hooshmand* ؛ Seyed Ali MirHassani | ||
| Department of Mathematics and Computer Science, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran | ||
| چکیده | ||
| 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 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. | ||
| کلیدواژه‌ها | ||
| Portfolio selection problem؛ Risk-parity؛ Scenario-based stochastic model؛ Distributionally robust؛ Ambiguity sets | ||
| مراجع | ||
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