Stock Price Prediction Model Based on RBF-SVM Algorithm

At this stage, China’s economic development continues to progress, and the emergence of various emerging industries has caused the stock market to show strong volatility. However, people’s research and prediction on the stock market have never stopped. In order to improve the accuracy of stock prediction, this paper studies the network model based on the improved support vector machine (SVM) algorithm to realize the correct judgment of the stock price trend, so as to achieve the purpose of accurate stock price prediction, and improve the accuracy of the prediction while ensuring the speed of the model. Experiments show that the proposed prediction model can approximate the short-term price trend of the stock market, and provide a more reliable data basis for the accurate prediction of stock prices, which benefit the high-tech development and progress of the stock market.