Portfolio Optimization of Five Stocks Based on the Mean-Variance Model

Abstract

Portfolio optimization, as an essential part of asset allocation, has become a core issue in the financial investment field in recent years. This paper focuses on the diversification of assets in semiconductor and integrated circuits, commodities, fast-moving consumer goods, air transportation, and streaming services industries, aiming to provide investors with a portfolio that optimizes risk and return. The mean-variance analysis, capital asset pricing model, and Fama-French three-factor model are applied to construct the portfolio. According to the asset weight allocation, the results are analyzed by maximizing the Sharpe ratio and minimizing variance. The results demonstrate that UL contributes the most proportion to the maximum Sharpe ratio and minimum variance under the capital asset pricing model. In the Fama-French three-factor model, DAL and UL provide the highest weight for the maximum Sharpe Ratio and minimum variance, respectively. Since KLIC is negatively correlated with UL and DAL has a negative correlation with NFLX, comprising these assets in the portfolio can function as a diversification. Therefore, the results are helpful for investors interested in portfolios in related industries.