PARTICLE SWARM OPTIMIZATION IMPLEMENTATIONON PORTFOLIO OPTIMIZATION PROBLEMS - Arkaputra Azis, Rheznandya
The Markowitz portfolio model has become the cornerstone of modern portfolio theory because it is able to provide an overview of how to build an optimal portfolio. Over time, this model was then expanded with a variety of additional constraints to get closer to real-world investment problems, such as buy-in threshold and roundlot constraints. The buy-in threshold constraint provides a minimum limit for the proportion of asset purchases and the roundlot constraint provides a portfolio arrangement in accordance with the lot unit. There are additional constraints and variations of assets that may be included in the portfolio, presenting its own complexity in calculating the Markowitz portfolio model analytically. These more complex problems can be solved numerically more effectively and efficiently. One method that can be used is the Particle Swarm Optimization algorithm which is a metaheurestic method. In this final project, an optimal portfolio will be developed based on the Markowitz portfolio model buy-in threshold and roundlot constraints metaheurestically using Particle Swarm Optimization.