Prediction of Stock Prices is already a complex issue in financial institutions. These prices depend on various factors like history of the Company, its present news, countries policies, social and economic conditions, natural disasters and many other factors. So, the prediction tasks require not only mathematical analysis but a neural network to make it more accurate.
Here in this project I had compared top 5 companies of top 10 sectors of Bombay Stock Exchange(BSE) in India from 2017 on the basis of their Market Capitalization. The comparison is done on historical prices from 1st Jan 2018 to 13th June 2018, this prediction can also be done in real time also. This project mainly uses the pandas library for analysis and matplotlib library for plotting in Python. With the use of Ordinary Least Squares Model the prediction can be analyzed easily just observing some values.