The selection of a suitable forecasting technique is of prime importance in order to obtain a better prediction result. The market with a huge volume of investors with good enough knowledge and have a prediction as well as control over their investments. Occasionally, the stock market fails to attract new investors. The reason states that unaware and also people don’t want to come forward to fall into the risk. This research paper demonstrated the use of a statistical approach, and regression by using daily, weekly, and monthly historical ten-year data for NSE, BSE, and HUL from the FMCG sector. This model will automate the process of the direction of future stock market indices as well as stock price movement and provides assistance for financial specialists to choose the better timing for purchasing and/or selling of stocks. The results are presented using SPSS visualizations. The performance of the trained model is analyzed and it is also tested to find the trend and the market behavior for future forecasts

Stock Market, Time Series Data, Prediction, Regression, SPSS.