Forecasting of Indian stock market using time-series models

Abstract

In the present era, stock market has become the storyteller of all the financial activities of any country. Therefore, stock market has become the place of high risks, but even then it is attracting the mass because of its high return value. Stock market tells about the economy of any country and has become one of the biggest investment places for the general public. In this manuscript, we present the various forecasting approaches and linear regression algorithm to successfully predict the Bombay Stock Exchange (BSE) SENSEX value with high accuracy. Depending upon the analysis performed, it can be said successfully that linear regression in combination with different mathematical functions produces the best results. This model gives the best output with BSE SENSEX values and gross domestic product (GDP) values as it shows the least p-value as 5.382e−10 when compared with other model’s p-values.