(untitled) (Journal of Computational Innovation and Analytics (JCIA), 2024)
This study develops a practical yet robust Mean Absolute Deviation (MAD) Mixed-Integer Linear Programming (MILP) model for a global investment portfolio tailored to the constraints faced by Malaysian retail investors, such as transactional fees and foreign currency exchange spreads, to provide more accurate estimations of portfolio returns. The MAD ILP model is modified to address these factors, aiming to enhance utility and efficiency. The study utilizes a Maybank 12-month fixed deposit cash account and ten selected Exchange-Traded Funds (ETFs) from iShares, Vanguard, and State Street Global Advisors for global portfolio construction. Forecasting techniques were utilized to generate expected returns for the ETFs and foreign currency exchange spreads. Based on the MAD model proposed by Konno and Wijayanayake (2001), the study introduces three modifications: incorporating transaction cost elements specific to Malaysian investors, including foreign currency exchange spreads in return calculations, and transforming the model from mixed-integer to pure integer model to accommodate minimum transaction lot constraint. Verification and validation exercises demonstrate the model’s ability to replicate real-world portfolio construction and reliable simulations. The model offers a practical tool for self-ascribed investors aiming to optimize global investment portfolios while considering unique constraints and transaction costs.