Proposing a comprehensive prediction algorithm, the CSI 300 index’s upward and downward trend can be predicted by combining the advantages of the K-nearest neighbor algorithm, support vector machine algorithm, and time series algorithm. Initially, the time series forecasts the stock’s chart for the upcoming period, followed by the K-nearest neighbor algorithm to determine the overall upward and downward trend. Subsequently, the support vector machine algorithm takes this upward and downward trend and incorporates it as a variable, thereby predicting the final stock’s upward and downward trend. This approach makes up for the deficiencies of the three algorithms, and can more accurately forecast the stock market’s up-and-down movements.