Date of Award
5-2019
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Mathematical Sciences
First Advisor
Munevver Mine Subasi
Second Advisor
Luis Daniel Otero
Third Advisor
Jewgeni Dshalalow
Fourth Advisor
Nezammoddin Nezammoddini-Kachouie
Abstract
We consider a two-stage stochastic bond portfolio optimization problem, where an investor aims to optimize the cost of bond portfolio under different scenarios while ensuring predefined liabilities during a given planning horizon. The investor needs to optimally decide whether to buy, hold, or sell bonds based upon present market conditions under different scenarios and varying assumptions, where the scenarios are determined based on interest rates and buying prices of the bonds. Three stochastic integer programming models are proposed and applied to real-data from Saudi Sukuk (Bond) Market. The case-study results demonstrate the varying optimal decisions made to manage bond portfolio over the two stages. In addition, the three stochastic programming models for bond portfolio optimization, are tested on a large set of randomly generated instances similar to the Saudi Sukuk (Bond) Market. The results of computational experiments attest the efficiency of the proposed models.
Recommended Citation
Alreshidi, Nasser Aedh, "Two-Stage Mixed Integer Stochastic Programming and Its Application to Bond Portfolio Optimization" (2019). Theses and Dissertations. 956.
https://repository.fit.edu/etd/956