A COMPREHENSIVE HYBRID MACHINE LEARNING MODEL FOR STOCK PRICE PREDICTION

Abstract

 With increasing numbers of investors into the stock market, knowing how to reduce the risk associated with it has become a matter of high importance. Determinant predictive models for stock price movements using machine learning methods have been developed in this regard. This article uses data obtained from the National Stock Exchange of India to create a model which will predict the direction for stock price movement. The model should seek and make accurate and reliable predictions on the basis of mutual relationships between various market indicators. This all is based on identifying factors that have a significant impact on stocks and their futures as well as the better understanding of market dynamics that would lead to informed decisions by investors. The last part of this model is to explain how independent variables interact in order to ultimately influence future trends of the market which helps improve financial forecasting.