In this period of modernization, the stock costs act as the narrator of all the financial and economic activities of the nation. But high fluctuations in the cost of a stock, the stock market turns into the spot of high hazard and vulner ability. But still, it is drawing great attention due to its exceptional yielding esteem. The stock market gives a clear image of the current economic state, financial stability, and also the growth rate of any country. Therefore, it has become the greatest speculation place for the overall population. This manu script targets to perform Univariate analysis on a historical dataset of Bombay stock exchange (BSE) SENSEX open value and compares the results of the ARIMA model, deep learning model, FBProhet model to predict the value of BSE SENSEX Open value, ie, opening cost of stocks, with high exact ness and accuracy. The performed analysis validates that FbProphet model developed by Facebook, gives the best possible predicted values of BSE SENSEX, provided that the dataset used contains the historical values of BSE SENSEX on a daily basis.