Support Vector Machine for Predicting Stock Price Based on RBF Kernel

Abstract

In current stock market,people are concerned more about the stock price prediction in recent years due to price fluctuation in the stock market and rapidly changing the prices. Therefore, in this paper we have proposed a price prediction solution by using Support Vector Machine(SVM) and Radial Basis Function(RBF) kernel to predict and the price of the stock from the previous values. To be exact, comparing with different parameters which are used in this model, we can get a set of optimum parameters to fit the regression and predict which is very close to the real value i.e. Price. We have applied our proposed approach on real time existing cases of stock market to ensure the correctness of results. Our experimental results show that percentage of the prediction success more than 70% which is very close to the previously existing values.