Portfolio Optimization with Application in Python

Abstract

Portfolio optimization is the process of selecting the best portfolio from all the portfolios to be considered. The goal of this thesis is to compare the performance of different models of portfolios. We have selected 30 stocks from the Yahoo website based on the DAX 30 index as our research sample for this thesis. Based on the sample size requirement, we have selected weekly adjusted closing prices from 2011 to 2020. We applied Python as a computational tool to analyze the Naive Strategy, Markowitz mean-variance model, and the Black-Litterman model. The thesis can be divided into five chapters. The first chapter is an introduction. The second chapter introduces the basics of Python. The third chapter introduces the portfolio optimization models that we use in the thesis. The fourth chapter is the application section. We use Python to apply all the models mentioned in the previous chapter to perform portfolio optimization calculations. The fifth chapter is the conclusion.