Predictive analytics in stock markets with special reference to BSE sensex

Abstract

Predictive analytics in finance is the art and science of using substantial quantities of data to find arrays. An Array can be termed as pattern or movement. Predictive analytics identifies patterns in large data volumes and helps to minimize future uncertainties. Predicting stock market returns is a puzzling task due to the multifaceted nature of the data. The present study is an applied application of the prediction and random walk theory on SENSEX behavior at an advanced level. Stock Market is the most dynamic element in the financial system and will play a crucial role in the progress of any country. The focus is on how much more on how to improve the forecasting models in terms of the performance of indices. The present model shows some commendable results in the prediction modelling reference to Indian stock market (BSE SENSEX). The designed model is also having utility for traders and investors estimating price movements of stocks at near future. Generally, the Fundamental Analysis comprises of evaluating the company’s profitability on the basis of its current business environment and financial performance in the future. Technical Analysis includes interpreting the charts and using statistical figures to identify the patterns in the stock market. A number of market indicators are believed to offer signals which are beneficial in anticipating future prices. For this purpose data of BSE Sensex data has been taken (January 2010-September 2018) from bseindia.com. The results exhibit that the Sensex would also gain momentum in the year 2019.