"时序分析应用于短期股价预测:基于中石化股票数据的实证研究"

The short-term stock price prediction based on time series analysis is an essential tool in the field of economics, providing valuable insights into historical data trends and forecasting economic variables. This method is commonly used in the stock market to predict stock price trends and assist investors and market regulators in making informed decisions. This study, conducted by Wang Hongfang from Class 1 of Mathematics and Applied Mathematics under the guidance of Teacher Wei Youhua, emphasizes the advantages of time series analysis through a comparison of various prediction methods. Starting from the concept of time series, the study introduces the basics of time series analysis for forecasting and its simple application models. Using historical closing price data of Sinopec's stock, the study predicts the closing price for the next five trading days using time series forecasting methods. By comparing the predicted prices with the actual prices, the study demonstrates the effectiveness of time series forecasting in predicting stock prices accurately. Keywords: time series; stock price; prediction. In conclusion, the study highlights the significance of time series analysis in predicting stock prices accurately and providing valuable insights for investors and market regulators. By utilizing historical data and applying time series forecasting methods, investors can make informed decisions and seize opportunities in the stock market. The study showcases the effectiveness of time series analysis in predicting stock prices, emphasizing its importance in the field of economics and finance.