The Application of Investment Portfolio in Practice

Research in portfolio optimization has become increasingly crucial in financial studies. While extensive research exists in this field, there remains a gap in examining specific industry sectors alongside real-world investment constraints. The research methodology involves selecting the SPX500 index and ten representative companies from these sectors to construct a correlation coefficient matrix. Using the Mean-Variance Model, the study calculates key metrics, including the maximum Sharpe Ratio, minimum variance, and capital allocation line. A solver table is then employed to determine the minimum variance frontier under various constraints. The findings reveal two key insights: firstly, the SPX500 demonstrates a strong correlation with the selected companies, suggesting its effectiveness as a portfolio component for balancing risk and return; secondly, both the minimum variance frontier and capital allocation line show reduced performance when additional constraints are introduced. These results provide valuable guidance for investors with varying risk preferences in making informed investment decisions. Furthermore, the study highlights the trade-offs involved when incorporating investment constraints into portfolio decisions.