Asset allocation optimization based on linear and quadratic programming models

Abstract

The aim of this paper is to provide a detailed insight into two mathematical models, one linear and one non-linear, that tackles the asset allocation optimization problem. We have collected data for seven different investment options in the last decade. The data are then analyzed with python, including visualizing them with several different graphs and computing their covariance and means. Our models are solved by python as well, admitting two different asset allocation plans according to application scenarios.