This paper aims to explore a method of constructing dynamically adjusted investment portfolios through the combination of rolling windows and mean-variance models. The construction of investment portfolios plays a crucial role in financial markets by effectively diversifying risks and achieving stable investment returns. This study analyzed adjusted closing price data from five stocks (AAPL, JPM, JNJ, XOM, and PG), sourced from Yahoo Finance. The rolling window method was employed to predict future stock prices and construct investment portfolios based on these predictions. This study calculated annualized average return and covariance matrix for each window. The mean-variance model and optimization algorithms were then used to determine the optimal weights for daily portfolio composition. The results demonstrate the high accuracy of the rolling window method in predicting short-term stock prices. Notably, Procter & Gamble (PG) and Johnson & Johnson (JNJ) exhibited the lowest prediction errors. Investment portfolios based on rolling window predictions performed well over a certain period. Nevertheless, the S&P 500 index did not show a substantial disadvantage compared to their long-term performance. This research provides dynamic portfolio optimization methods of practical value for investors in financial markets.

Affected by the epidemic and geopolitics, global economic growth has slowed down, trade protectionism has begun to emerge, and anti-globalization sentiment has begun to sprout. With the pace of the Federal Reserve's interest rate hike, the global exchange rate, especially the RMB exchange rate, is gradually under pressure, which has a great impact on the economy and financial sector of the whole country. The research topic of this paper is the influencing factors of the RMB exchange rate in the background of anti-globalization, and the empirical analysis of the VAR model based on Stata software. The study found that rising domestic interest rates, a rising balance between import and export trade and rising uncertainty about US economic policy will lead to the appreciation of the RMB, while the growth of money supply will lead to the depreciation of RMB. It is worth noting that the RMB exchange rate is less affected by the uncertain economic policy factors in the United States, which shows that under the current anti-globalization and international game background, China still has a relatively independent control of the foreign exchange market.

With the increasing incidence of hypertension, it is particularly important to understand and prevent hypertension. To prevent hypertension, we need to know what factors may lead to its occurrence. This article aims to explore the influence of smoking, diabetes, BMI and other factors on hypertension. Through the analysis of the data provided by Kaggle website, the single factor and multi factor logistic regression analysis methods were used to study the impact of eight variables on hypertension, including gender, age, BMI, recent smoking status, daily smoking volume, diabetes, cholesterol level and heart rate. The results showed that in the univariate analysis, except for gender, all other factors were significantly correlated with hypertension. In this study, smoking was negatively correlated with hypertension, while other factors were positively correlated. However, in the multivariate analysis, smoking status, daily smoking and diabetes decreased significantly. In conclusion, diabetes and smoking still have an impact on hypertension, but this effect may not be so important. People should pay more attention to weight control, but smoking and diabetes also affect hypertension, and we should also pay attention to the impact of smoking and diabetes. For example, smoking will affect cardiovascular disease, and diabetes is still positively related to hypertension in this study.