Allameh Tabataba'i University Press Journal of Mathematics and Modeling in Finance 2783-0578 5 1 2025 07 01 On data-driven robust portfolio optimization with semi mean absolute deviation via support vector clustering 155 165 18955 10.22054/jmmf.2025.84881.1170 EN Eftekhar Kosarinia Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran Maziar Salahi Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran Tahereh Khodamoradi Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran Journal Article 2025 03 13 In [14] the authors have studied robust semi-mean absolute deviation portfolio optimization model when assets expected returns involve uncertainty. They applied a data driven approach via support vector clustering to construct the uncertainty set using support vector clustering. In this paper, we show that their robust formulation is not the worst case counterpart of the original model. Then we give the true robust model of the underlying problems in the best an worst cases. Experiments are conducted to show the optimal objective value of the robust model in [14] belongs to the interval generated by our best and worst case models. https://jmmf.atu.ac.ir/article_18955_9ae41455251f66177bc4c598617b1c96.pdf