Distributionally robust mean-absolute deviation portfolio optimization using wasserstein metric

• Published in: Journal of global optimization Vol. 87; no. 2; pp. 783 - 805
• Main Authors: Chen, Dali, Wu, Yuwei, Li, Jingquan, Ding, Xiaohui, Chen, Caihua
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.11.2023; Springer; Springer Nature B.V
• Subjects: Comparative analysis; Computer Science; Deviation; Investment analysis; Mathematics; Mathematics and Statistics; Operations Research/Decision Theory; Optimization; Real Functions; Robustness; Uncertainty; MAD portfolio model; 90C90; 90C15; Nonconvex optimization; Wasserstein distributionally robust optimization; Uncertainty modelling

Data uncertainty has a great impact on portfolio selection. Based on the popular mean-absolute deviation (MAD) model, we investigate how to make robust portfolio decisions. In this paper, a novel Wasserstein metric-based data-driven distributionally robust mean-absolute deviation (DR-MAD) model is p...