Research on Display of Stock Trading Reversal Points and Abnormal Points Based on Hurst Model

With the development of the global financial market and the advancement of information technology, stock trading has become an important part of the economy of various countries. In stock trading, it is very important for investors to accurately identify trading reversal points and abnormal points. Accurately identifying these points can help investors make timely buying and selling decisions, thereby maximizing investment returns. However, traditional stock trading methods have certain limitations in identifying trading reversal points and outliers. Traditional methods often rely on a single technical indicator and subjective experience, and cannot fully consider the dynamic changes and nonlinear characteristics of the market. In order to solve these problems, this paper proposes a stock trading analysis method based on computer platform combined with Hurst model. The use of computer platforms can improve the efficiency of data processing and analysis, and the Hurst model can more accurately describe the long-term trend of stock prices. Through comparative experiments, this paper finds that the computer platform combined with the Hurst model has higher accuracy, recall and F1 scores in identifying trading reversal points and abnormal points, and has better performance than traditional methods. This paper verifies the advantages of computer platform combined with Hurst model in stock trading analysis through comparative experiments, which has higher accuracy and comprehensiveness than traditional methods. The research method of this paper also provides new ideas and methods for the field of stock trading analysis, and provides a reference for future research and practice.