In the process of investment, the primary investment objectives for investors are undoubtedly risk minimization and return maximization. This paper fo-cuses on the US investment market and, in the context of the Federal Re-serve's continuous interest rate hikes, avoids the currently popular artificial intelligence sectors, and focuses on the analysis of representative stocks in the manufacturing, pharmaceutical, technology, and financial industries. This paper selects 10 stocks from the above-mentioned industries for analy-sis. This paper collects stock prices, financial data (including P/E ratio, BPS, etc.), risk-free rates, market indices, and other data, and uses multiple linear regression models to predict the return data from January 1st, 2023, to March 10th, 2023. Next, the mean-variance framework is employed for the purpose of selecting both the portfolio with the highest Sharpe ratio and the one with the lowest volatility. Once the weights for both groups are ob-tained, this study tests the portfolio's performance using actual stock price data spanning from January 1st, 2023, to March 10th, 2023. After obtaining the performance data of the two groups, this paper further compares the per-formance of the portfolio with the 1/N portfolio and the market performance. The results show that the market performance is the best, followed by the 1/N portfolio and the minimum volatility portfolio, and the maximum Sharpe ratio model is the worst. This result may provide some guidance for portfolio management for some investors in this special period.