Inverse Multi-Objective Optimization for Portfolio Allocation in Commercial Banks
Keywords:
Linear programming, Multi-objective linear programming, Inverse optimization, Efficiency, Pareto optimality, Inverse multi-objective linear programming.
Abstract
Optimal portfolio allocation in commercial banks is a critical decision for financial institutions. This paper proposes a multi-objective linear programming model to address this challenge. To ensure the model's feasibility and efficiency, we employ a generalized inverse optimization approach, replacing regular optimality with Pareto optimality. We apply our proposed models to real data from Bank Misr, an Egyptian bank, during the finance year 2020/2021. The multi-objective model was solved using LINGO 19, while the inverse multi-objective model was solved using R programming. Our analysis of the results provides valuable insights into optimal portfolio distribution for commercial banks.
Published
2025-01-09
How to Cite
Albehery, N., Helal, M. A., & Ghania, A. F. (2025). Inverse Multi-Objective Optimization for Portfolio Allocation in Commercial Banks. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-2188
Issue
Section
Research Articles
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