ASSESSMENT ON STOCK MARKET PREDICTION USING MACHINE LEARNING BASED METHODOLOGIES FOR HIGHLY VOLATILE MARKET

Abstract

The efficient prediction algorithm gives the traders more benefit. The accuracy of prediction
models be contingent proceeding the selected features which will be contribution to the forecast
method. In this paper we were analyzed some stock prediction models. This research has described
the qualified scrutiny on stock prediction models: one of the major investment activities in stock
market is trading of stocks. In a volatile market environment, a precise prediction of market trend
is very essential. Investors developed a number of stock analysis method that could help them
predict the direction of stock price movement. Prediction of equity price, based on the current
financial statistics, is vital for investors. It helps the investors to know which stock will rise or fall
over certain period of time. For this purpose, numerous methods have been devised which have
been successful partially. Hence, this proves that process of stock prediction is not an easy task.
So in this paper an additional component of measurement is discussed which could be added to
the existing methods. The traditional market movement based prediction when combined with the
sentiments or opinions of investors and experts will give better results. This ideology has been
explored in this paper.