Statistical Analysis and Forecasting Models for Stock Market

In the present era of the world, 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. Today, Stock market has become one of the biggest investment place for general public. In this manuscript we put forward the various forecasting approaches for predicting the BSE SENSEX using various forecasting models like ARIMA, BoxCox, Exponential Smoothing, Mean Forecasting, Naive, Seasonal Naive, Neural Network, and then comparing their mean error for deducing the best suitable model. The analysis is done on the Bombay Stock Exchange(BSE) SENSEX. Results of this analysis shows that, the Exponential smoothing and Neural network gives the best results if we compare the mean error of the both models with the other models.