Trading stocks on the stock market are one of the major investment activities. In the past, investors developed a number of a stock analysis method that could help them predict the direction of stock price movement. Modelling and predicting of equity future price, based on the current financial information and news, is of enormous use to the investors. Introduction of machine learning caused that new models can be developed based on the past data. Our main hypothesis was that by applying machine learning and training it on the past data, it is possible to predict the movement of the stock price. Particularly, we want to determine the percentage of growth or fall in a stock price for the next day which can be variable. Usually, investors want to select the stocks which will grow in price substantially.