Support Vector Machine-based Stock Prediction Analysis

Abstract

Changes in the stock market are closely related to the dynamics of the market development and economic research of the whole country. Correctly predicting the stock price trend is not only beneficial for investors to make correct investment management decisions but also of great importance to promote the effective allocation of resources and improve market effectiveness. To this end, the empirical prediction and analysis of a stock development market using a support vector machine show that the accuracy of stock prediction using a support vector classification machine is as high as about 90%, indicating that the accuracy of stock prediction based on support vector machine is ideal and meaningful.