Daniel Carpenter
June 2022
This project outlines how Modern Portfolio Theory can be implemented using notable financial engineering techniques. The generated algorithm discussed within this project combines a dynamic implementation of Modern Portfolio Theory with a robust metaheuristic solver to find the globally minimum risk portfolio, given the desired set of stocks and sample date range. Specifically, the metaheuristic called “Particle Swarm Optimization” intends to overcome issues with local optima in non-linear modeling. The model delivers the optimal weights to invest in a certain set of stocks, defined by the user of the tool. Additionally, the model displays key summary statistics like the risk and expected return of the portfolio.