Mathematics and System Engineering Faculty Publications
Document Type
Article
Publication Title
Entropy
Abstract
This paper presents a Monte Carlo simulation-based approach for solving stochastic two-stage bond portfolio optimization problems. The main objective is to optimize the cost of the bond portfolio while making decisions on bond purchases, holdings, and sales under random market conditions such as interest rate fluctuations and liabilities. The proposed algorithm identifies the number of randomly generated scenarios required to convert the stochastic problem into a deterministic one, subsequently solving it as a Mixed-Integer Linear Program. The practical relevance of this research is shown through an application of the proposed method to a real-world bond market. The results indicate that the proposed approach successfully minimizes costs and meets liabilities, providing a robust solution for bond portfolio optimization. © 2025 by the authors.
DOI
10.3390/e27111118
Publication Date
2025
Recommended Citation
Albaqami, Hissah; Mrad, Mehdi; Gharbi, Anis; and Subasi, Munevver Mine, "A Monte Carlo-Based Framework for Two-Stage Stochastic Programming: Application to Bond Portfolio Optimization" (2025). Mathematics and System Engineering Faculty Publications. 221.
https://repository.fit.edu/math_faculty/221