Application of Modern Portfolio Theory in Stock Market based on Empirical analysis

Abstract

With the rapid growth of the stock market, stocks have been viewed as one of the most popular investments. Investors then face a problem that is how to allocate resources among the variety of stocks with the aim to increase their wealth through investment activities. The paper aims to design an investment strategy for risk-averse investors. We study the modern portfolio theory and apply the mean-variance analysis to quantify expected portfolio returns and acceptable levels of portfolio risk. We would like to obtain an optimal portfolio and provide investors with investment strategies. We consider the daily adjusted closing stock prices between January 2010 and January 2021 of 5 companies: Facebook, Amazon, Apple, Netflix, and Google. Our results show that such mean-variance optimization is applicable. Furthermore, we can achieve a minimum variance portfolio with the lowest possible level of the risk of 23% (standard deviation), while the expected return is approximately 28%. Additionally, the best risk-adjusted portfolio can be achieved with a higher return of 33% at risk of 23%.