Novel Approach for Multi Period Portfolio Selection with Different Rates for Borrowing and Lending, Using Chance Constrained Programming

This paper introduces a novel methodology for multi-period portfolio selection incorporating varying rates for borrowing and lending. The study focuses on determining optimal investment amounts across different planning horizons when the borrowing rate exceeds the lending rate. The research employs chance constrained programming to handle the inherent uncertainties in portfolio selection. A genetic algorithm is utilized to solve the nonlinear programming model. Numerical experiments validate the proposed methodology, offering insights into its effectiveness and robustness.