International Journal of Information Engineering and Electronic Business (IJIEEB)
IJIEEB Vol. 10, No. 2, 8 Mar. 2018
Cover page and Table of Contents: PDF (size: 1062KB)
Analysis and Prediction of Individual Stock Prices of Financial Sector Companies in NIFTY50
Full Text (PDF, 1062KB), PP.33-41
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Author(s)
Index Terms
Neural network, Stock Forecasting, Backpropagation, NIFTY50
Abstract
Prediction of the stock market is currently a big business opportunity for the data analytic solution providers. As the vast range of factors influencing the stock market index are available, it is essential to find the relation between those macroeconomic variables with company share prices and predict the accurate results. Our research is analyzing different relation between the prediction and individual stock prices of financial sector companies in National Stock Exchange 50(NIFTY 50). To make a strong portfolio the selection of different companies is one of the vital decisions we should attempt for a good investment. Trending researches regarding financial forecast are based on the accuracy of the models that how well National Stock Exchange (NSE) index values can be predicted. There is significant literature survey available on the prediction of the stock market as well as its pricing. NIFTY 50 is one of the well-known indexes in India for the investors seeking a good investment. In our research, we attempt, to forecast the stock values of different organizations of Banking and Financial sectors in NIFTY 50. Before including the factors to forecast share market index we are trying to find the relation between different factors and indices of those companies. The study empirically proves that the proposed model is precise to be used in real time stock prediction which can benefit the sellers, investors and stakeholders in their real time savings, investment, and speculation.
Cite This Paper
Vikalp Ravi Jain, Manisha Gupta, Raj Mohan Singh, "Analysis and Prediction of Individual Stock Prices of Financial Sector Companies in NIFTY50", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.10, No.2, pp. 33-41, 2018. DOI:10.5815/ijieeb.2018.02.05
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