Optimization of Portfolio using Markowitz’s Modern Portfolio Theory and Computational Techniques Using Python

Optimization of Portfolio using Markowitz’s Modern Portfolio Theory and Computational Techniques Using Python/span>

Authors- Sandesh Ravindra Bhat

Abstract-This research paper applies Markowitz’s Modern Portfolio Theory (MPT) to optimize investment portfolios by achieving an optimal balance between risk and return through computational techniques. Utilizing Python, we develop and test a portfolio model using real-world stock data, focusing on mean-variance optimization. The model generates random portfolios with varying asset allocations and employs quadratic programming to explore the efficient frontier—a representation of the best possible risk-return trade-offs. Through this approach, we demonstrate how computational methods can enhance portfolio management by identifying portfolios that either minimize risk for a given return or maximize return for a given risk level.

DOI: /10.61463/ijset.vol.12.issue5.270