Analysis and Forecasting of Individual Stock Prices of Various Constituents in NIFTY 50

Abstract

Financial forecasting is one of the trending research going on in the current market. Researchers are mainly focused on the parameters that are affecting share market. Presently researchers are able to discover the relation between macroeconomic variables and different indices. We are driving our research by discovering the relationship between macroeconomic variables and individual share prices, but before proceeding for the prediction, we firstly analyze each individual company and their dependence on raw products for the improvement in predicting the individual share prices. Each individual companies produce different units used by consumers. To compose those elements companies necessitate raw materials and because of those materials their share prices are being affected. We did an analysis that how strongly they need those raw materials in their production and how these companies are related. From that relation, we are able to parameterize our neural network for the prediction of different individual companies share prices.