Analysing the Trend of Stock Marketand Evaluate the performance of Market Prediction using Machine Learning Approach

Abstract

The main focus of the research work is to explore the current Stock market data values based on a real-time data, in which stock market data value fluctuates depends on time. The stock market prediction and analysing the future stock values is still considered as the challenging task in research field. The motivation of the current research work is the stock market data values varies time to time according to the subject risk. so it is the need to develop a computational automated methodology for predict the stock market data values. The detailed information regarding the existence of stock market variations is identified by collecting the information from previous historical data for making the choice of predictions strategy by considering the data with the stock analyst's experts of the stock market analysis system. The performance improvement of the newly developed by machine learning classification approach method is analysed through the comparative analysis report, which ensures the accurate prediction of the proposed method. This machine learning classification algorithm have been used, this predicts the stock market price and stock market movementchanges from this performance can be evaluated and also proposed work suggested and recommended to the user, so user can easily find out the which stock will be in market longer period. The prediction accuracy of the stock exchange has analysed and improved to 94.17% using machine learning algorithms. As the results, this prediction will helpful to investor, to judge the current value and future prediction values of company's stock market rate.