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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.
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; Subasi Munevver Mine 4
1 Department of Mathematics and Systems Engineering, Florida Institute of Technology, Melbourne, FL 32901, USA; [email protected], Department of Mathematics, College of Science, Turabah University College, Taif University, Turbah 29731-9086, Saudi Arabia
2 Essect School of Business, University of Tunis, Tunis 1089, Tunisia; [email protected], Business Analytics and Decision Making Lab, Tunis Business School, University of Tunis, Bir El Kassaa 2059, Tunisia
3 Department of Industrial Engineering, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia; [email protected]
4 Department of Mathematics and Systems Engineering, Florida Institute of Technology, Melbourne, FL 32901, USA; [email protected]