Stock Market Analysis and Prediction using Machine Learning Algorithm

Abstract

Abstract: The prediction of a stock market direction serves as an unseasonable recommendation of system for shortterm investors and before time financial distress warning system for long-term shareholders. Forecasting accuracy is the most important part in selecting any forecasting technique. Research efforts in upgrading the accuracy of forecasting models are increasing from the last decade. The appropriate stock selections those are fit for investment is a challenging task. The key factor for each investor is to be paid maximum profits on their investments. In this paper Support Vector Machine Algorithm (SVM) is handed down. SVM is a very specific kind of learning algorithms characterized by the volume control of the decision function, the work of the kernel functions and the scarcity of the compound. In this paper, we investigate the predictability of economic movement with SVM