Stock Prediction by Analyzing the Past Market Trend

Abstract

In contrast to the sudden change in global scenario with respect to shifting of things to online on a vast scale and unprecedented fluctuation of the global market, stocks have gained a lot of attention. Market prediction has always been an enigma for investors. Whether it be decoding the way market repeats itself or analyzing the trends that could help get better value for the investment, investors have always been keen on finding an efficient solution that could predict the price with utmost accuracy. This paper presents a study of different technologies that are currently being used for analyzing and predicting the stock market trend. The analysis of past trends has been done using the values for previous close, open, high, low, and close of the stock for a period of six years from the data that has been gathered from the stocks registered on the National Stock Exchange (NSE). For handling such a huge dataset and analyzing the trend in it, Python and R programming languages have been extensively used.